football research paper examples

333 Football Research Topics & Essay Titles

Football is a game that millions of people around the world enjoy watching and playing. With 3.57 billion views of the 2018 FIFA World Cup, this sport appears to be the most popular. Besides, each match is more than just a game — football is all about passion, skill, and teamwork.

In this article, our expert team has collected great football topics to write about and research that you can use for your school or college assignments.

🔝 Top 12 Football Topics to Write About

✍️ football writing prompts, 📝 football titles for essays, 🗣️ football speech topics, 💡 football topics for presentation, 🔎 football research topics, ⚽ football essay outline, 🔗 references.

• The history of football.
• Football as the world’s most popular ball game.
• The development of modern football.
• The greatest football moments.
• Why do tactics play a vital role in football?
• Football as a traumatic kind of sport.
• What is football’s most prestigious competition?
• The legends of American football.
• The impact of football on society.
• Advantages of playing football.
• Men’s and women’s football.
• The issue of racism in football.

Are you looking for some prompts on the football topic? Then you are at the right place! Below, you can find ideas for writing your essay.

Why Football Is the Best Sport: Essay Prompt

Football is a global sport that connects practically everyone on the planet. It has the power to bring an entire city or nation to a standstill. In the essay that explains why football is the best game, you can share your own experience or the emotions of your friend who is passionate about this game. Also, you can list the reasons why people love this sport. For example:

• Football connects millions of people.
• There are no age restrictions to enjoy the match.
• The world’s best talents are football players, such as Lionel Messi.
• Watching or participating in football evokes genuine emotions.

Prompt for Panyee Football Club Essay

Have you ever heard about a football club that is floating on water? Panyee FC is one of them! Since there is not enough space on the island, football fans and players built a football pitch in the middle of the sea. Find the answers to the following questions about Panyee Football Club and use this information in your essay:

• What is the history behind Panyee Football Club?
• Why is a Panyee FC pitch built on water?
• What are the core values of Panyee Football Club?
• Can we say that Panyee FC is a symbol of passion for football?

Why Football Is Dangerous: Essay Prompt

The fact that football has the greatest injury rate of any other kind of sport should not come as a surprise. Football players often incur injuries like ankle sprains, knee injuries, concussions, and acromioclavicular sprains. In your essay on the dangers of football, you can raise the following questions:

• Why is it so easy for football players to get injured?
• What types of injuries are most common during a football game?
• What precautions must be taken to prevent trauma?
• How does injury impact the future career of a football player?

Prompt for Essay on Concussions in Football

While every sport has some risk of getting hurt, football, as a high-impact sport , is infamous for causing severe injuries. Concussions are a common injury among football players. They happen when the head is hit hard enough to cause a minor brain injury. To research the topic of concussions in football, write your essay based on the following aspects:

• The effect of concussion on the brain.
• Statistics on concussion in American football.
• Medical concussion protocol.
• The recovery process after a concussion.
• Screening procedures examining football players for brain damage.

If you’re looking for the most engaging football essay titles, check out the ideas we’ve collected below!

Topics for a Descriptive Essay on a Football Game

• The thrill of a last-minute goal in football.
• The intensity of the players’ warm-up and last-minute preparations.
• Sports psychologist: working with athletes .
• The different styles of play in football around the world.
• The rapid movement of players and the choreography of their tactics.
• The role of a coach in football.
• Capturing the joys and frustrations of the players and fans.
• The interaction between players and referees: decisions, protests, and resolutions.
• A description of a football stadium and its architecture.
• The art of dribbling in football.
• How do players and fans celebrate a goal?
• Describing pre-match rituals and superstitions in football.
• How do fans create a supportive atmosphere for their team during the game?
• The joy and excitement of attending a live football match.
• Describing how coaches handle their emotions on the sidelines.
• The description of food served during the football game.
• The magnetic pull of the scoreboard: watching the numbers change.
• The vibrant fan gear and merchandise in a football stadium.
• The drama of penalty kicks: tension, hope, and heartbreak.
• The description of a goalkeeper’s save.
• The sounds of the football match.

Football Argumentative Essay Topics

• Is football too dangerous for young children to play?
• Does football develop leadership skills and teamwork?
• Title IX in the female sports development .
• College football players should be paid for their performance on the field.
• Should football stadiums have stricter security measures?
• Is the use of performance-enhancing drugs in football acceptable?
• Reasons why the NFL should expand to include more teams.
• Why paying college athletes is beneficial .
• Is the NFL doing enough to prevent concussions and other injuries in players?
• Should football games be played on artificial turf or natural grass?
• Is it ethical for colleges to recruit high school football players?
• Should players be allowed to protest during games?
• Does youth sports play a part in the character formation ?
• Reasons why cheerleading should be considered a sport in football.
• Should the Super Bowl be considered a national holiday?
• The economic influence of football: the benefits and costs.
• Is football too focused on commercialization and profit?
• Should football players be allowed to use marijuana for medical purposes ?
• The NFL should have a shorter season to reduce the risk of injuries to players.
• Using performance-enhancing drugs in the world of sport .
• Should college football teams be allowed to schedule games against non-college teams, such as high school teams?
• Should the NFL have a salary cap to ensure fairness among teams?
• Football players should wear full body armor to reduce injuries.
• Is football too expensive for schools and communities to support?
• Should the NFL allow players to use alternative therapies for pain management ?
• Should football players be required to take regular drug tests ?
• Should the NFL have stricter penalties for players who break the rules, such as suspensions or fines?
• Children participation in sports .
• Football players should take classes on financial management to prepare for life after football.
• Should the NFL have a quota for hiring minority coaches and executives?
• High school football players should pass a physical exam before being allowed to play.
• Should the NFL have stricter rules on player conduct off the field?
• College football players should be allowed to transfer to other schools without penalty.
• Should the NFL have a policy on players using social media ?
• Football players should attend media training to prepare for interviews and press conferences.
• Sport psychology: biases and influence of external rewards .
• Should the NFL have a policy on players participating in political activism ?
• Football players should undergo regular psychological evaluations.
• Should the NFL have a policy on players using alcohol and drugs off the field?
• Should football players be required to wear protective eyewear to reduce eye injuries?
• College football teams should provide mental health resources for their players.
• Should high school football teams limit the number of weekly practices to reduce the risk of injuries?
• Paying college athletes: reinforcing privilege or promoting growth ?
• Should college football players be allowed to unionize?
• Should football be banned in schools to protect students from injuries?
• Is playing football in college detrimental to academics?
• Should college football players be allowed to hire agents?

Ideas for a Narrative Essay about Football

• The first time I stepped onto the football field: an unforgettable experience.
• Overcoming adversity: how I bounced back from a football injury.
• A story of teamwork : how football taught me the value of collaboration.
• The most memorable football match I have ever witnessed.
• Coping with stress in athletes .
• The importance of football in building lifelong friendships.
• From underdog to champion: my journey with the football team.
• A day in the life of a football player: behind the scenes.
• The role of football in shaping my identity.
• A tale of rivalry: the intense football match against our arch-nemesis.
• The impact of football on my physical fitness and well-being.
• How a football coach changed my life.
• The thrill of scoring the winning goal: a football victory to remember.
• The evolution of football: from my grandfather’s time to the modern era.
• A football match that taught me the importance of humility .
• The emotional rollercoaster of supporting a football team.
• Lessons learned from defeat: how football taught me resilience .
• A football game that tested my leadership skills.
• Football and community: how the sport brings people together.
• A football camp experience: training, team building , and friendship.
• From fan to player: fulfilling my football dream.

Football Essay Topics: Compare and Contrast

• Regular football vs. American football: a comparative analysis.
• Lionel Messi vs. Cristiano Ronaldo: contrasting two football legends.
• Comparing football and soccer .
• College football vs. professional football: similarities and differences.
• The World Cup vs. the Super Bowl: contrasting two major football events.
• The roles and impact of offensive and defensive players.
• The Premier League vs. La Liga: comparing two dominant football leagues.
• Contrasting playing styles and cultural significance of football in Europe and South America.
• Club football vs. international football: examining the differences in competition and loyalty.
• Football stadiums vs. arenas: comparing the experiences of live football events.
• The similarities and differences between Olympic football and FIFA World Cup.
• Football in the past vs. modern-day football.
• Comparing the roles and responsibilities of quarterbacks and goalkeepers.
• Football fan culture in Europe vs. the US: contrasting fan traditions and behaviors.
• Amateur football vs. professional football.
• Football uniforms vs. gear: analyzing the equipment used in the sport.
• Comparing and contrasting famous football team rivalries.
• Football team dynamics vs. individual brilliance: contrasting the impact of teamwork and individual performances.
• Football referees vs. video assistant referees (VAR).
• Club vs. country: comparing the passion and loyalty for club and national teams.
• Football and injuries: comparing the risk and types of injuries in the sport.
• Football leagues during the pandemic vs. regular seasons.
• Football commentary vs. live match experience: comparing the different ways of engaging with the sport.
• The impact of football on local vs. global economies.
• Football documentaries vs. fictional football movies.
• The role of football in promoting diversity vs. perpetuating stereotypes.
• Football fandom vs. player idolization: contrasting how fans engage with the sport.
• Comparing the traditional grass pitches vs. artificial turf.
• The impact of social media on football vs. traditional media.
• Comparing the challenges of football in different weather conditions .
• Football in mainstream culture vs. football subcultures.
• The health benefits of football vs. injuries and health risks.
• Betting in football vs. gambling .
• The cultural significance of football in different regions.
• Football literature vs. football films: contrasting different forms of storytelling about the sport.
• Football stadiums: traditional vs. modern architecture .
• College football vs. professional football: differences in gameplay and culture.
• Offensive vs. defensive strategies: which is more important?
• Comparing traditional and modern football training methods.
• The history of football in America and Europe.
• Injuries in football vs. soccer: which sport is more dangerous?

American Football Topics

• The evolution of American football: from its origins to the present day.
• The impact of race on American football.
• Concussions and brain injuries in American football.
• The psychology of football: understanding the mental game of players and coaches.
• The role of women in American football: from cheerleaders to coaches and executives.
• The strategies and tactics used in American football.
• The role of coaches in American football: leadership and game planning.
• The significance of the offensive line in American football.
• The impact of college football on the NFL.
• The influence of the media on American football.
• The role of the head coach in American football.
• The importance of physical fitness in American football.
• The impact of technology on American football: from instant replay to virtual reality training.
• The economic impact and financial aspects of American football.
• The history of Super Bowl halftime shows.
• American football and national identity.
• The impact of weather on American football games.
• The influence of player protests on American football.
• The role of American football in the entertainment industry (movies, TV shows, etc.).
• The development of American football youth programs: benefits and challenges.
• The importance of the running back in the offense in American football.
• The role of the defensive line in stopping the run and rushing the passer in American football.
• The influence of American football on sports marketing and sponsorship.
• The impact of fan behavior on American football.
• Exploring the legacy of American football’s great players and their impact on the sport.
• The influence of a new coach on team culture and performance in American football.
• The consequences of player suspensions in American football.
• Player trades in American football: exploring how teams acquire new talent.
• American football and sportsmanship: fair play and ethical considerations.
• The impact of player injuries on American football: exploring the recovery process.
• The role of American football in building teamwork and camaraderie.
• The impact of American football on society’s perception of masculinity .
• The history and cultural significance of American football rivalries.
• The role of American football in promoting community engagement and volunteerism.
• The influence of American football on US pop culture.
• American football and social justice : protests, activism, and athlete empowerment.
• The role of American football in public health and fitness initiatives.
• The ethics of sports gambling in American football.
• American football and sports diplomacy: international relations and competitions.
• The future of American football: challenges and opportunities.

Are you looking for exciting football topics to talk about? Check out our suggestions for persuasive and informative speeches about this sport!

Football Persuasive Speech Topics

• The benefits of playing football for overall physical fitness.
• The importance of youth football programs in fostering teamwork.
• Kids and sports: lack of professional sports guides .
• The positive impact of football on character development and leadership skills.
• The role of football in promoting gender equality and inclusion.
• The economic benefits of hosting major football events like the World Cup or Super Bowl.
• The need for increased safety measures and concussion protocols in football.
• The necessity of providing proper healthcare and support for retired football players.
• The role of football in breaking down cultural and racial barriers.
• Balancing college sports and academic mission .
• The benefits of investing in football infrastructure and facilities for communities.
• The positive influence of football in reducing youth involvement in crime and drugs.
• The potential of football as a tool for empowering disadvantaged communities.
• The role of football in promoting a healthy and active lifestyle among fans and spectators.
• The benefits of including football as part of the physical education curriculum in schools.
• The positive effects of football in promoting national pride.
• Corporate social responsibility in sports organizations .
• The use of football as a platform for raising awareness and funds for charitable causes.
• The importance of football in boosting tourism and international visibility of cities.
• The potential of football in fostering international diplomacy and cultural exchange.
• The importance of providing equal opportunities for females in football at all levels.
• The impact of football on local economies through job creation and tourism revenue.
• The significance of iconic moments in football history.

Football Informative Speech Topics

• The different positions in football and their roles.
• The psychology of football fans and their passion for the game.
• Agencies in the international football industry .
• Famous football stadiums around the world and their significance.
• The rules and regulations of football: understanding the game’s structure.
• The role of referees and their importance in enforcing the rules of football.
• Positive self-talk and its impact on athletes .
• The evolution of football equipment: from leather balls to high-tech gear.
• The most successful football clubs in history and their achievements.
• Exploring the tactics and strategies used in modern football.
• The science behind successful football coaching.
• Sports coaching career and its history .
• Football rivalries: the history and intensity behind classic match-ups.
• The art of scoring goals: techniques and skills of top goal scorers.
• Football and media: the influence of broadcasting and coverage on the sport.
• The psychological aspects of football: mental preparation and performance.
• The cultural impact of football around the world.
• The development and growth of women’s football.
• Physical therapy services for sports injuries .
• The importance of nutrition and fitness in football.
• The significance of football academies in nurturing young talent.
• The role of technology in modern football: VAR, goal-line technology, and more.
• Football hooliganism : understanding the causes and efforts to combat it.
• Famous football managers and their managerial styles: strategies for success.

If you need compelling topics about football for your presentation, here are some ideas you can consider:

• The FIFA World Cup: the most significant event in international football.
• Techniques and skills in football: dribbling, shooting, passing, and more.
• Leadership development in football management .
• The rules and regulations in football.
• Football tactics: exploring different formations and strategic approaches.
• Famous football players of all times: their achievements and impact on the sport.
• Football and sports injuries: common types, prevention, and treatment.
• Steroid use effects on professional young athletes .
• Football stadiums around the world: architecture and unique features.
• The business side of football: sponsorship, transfer fees, and revenue streams.
• Football and social media: the influence of digital platforms on the sport.
• Football documentaries and films: capturing the drama and passion of the sport.
• The effects of football on fashion and popular culture.
• Virtual reality technology in soccer referee training .
• The financial impact of football on cities and regions.
• Football and sports journalism: media coverage and analysis of the sport.
• Football stats and analytics: how data is revolutionizing the sport.
• The causes and consequences of fan violence in football.
• The cultural rituals and traditions associated with football matches.
• Football and the environment: sustainable practices and stadiums.
• The impact of football on tourism.
• Health care site: fitness, sports, and nutrition .
• Football and celebrity culture: players as icons and brand ambassadors.
• Football in video games: the popularity of virtual football experiences.
• The importance of infrastructure in hosting major football events.
• Football tactics in different eras: from Catenaccio to Tiki-Taka.
• Football and broadcasting: the growth of televised matches and media rights.
• Football training drills for improving agility and speed.
• Physical activity and sports team participation .
• Strategies for effective team communication on the football field.
• The importance of proper warm-up exercises in preventing injuries in football.
• Tips for strengthening and conditioning specific muscle groups for football players.
• Defensive formations and tactics for shutting down opponents in football.
• Analyzing football game films to improve performance and strategy.
• Recovering from football injuries: rehabilitation exercises and protocols.
• Sports-related problems and conflicts .
• Sports psychology techniques for boosting confidence and mental resilience in football.
• Nutrition and hydration guidelines for optimal performance in football.
• The connection between globalization and football.
• The role of stretching routines in preventing muscle imbalances in football players.
• Practical strategies for successful penalty shootouts in football.
• Steroid usage in professional sports .
• Football scouting and player evaluation techniques for talent identification.
• The use of technology in football training and performance analysis.
• Football equipment maintenance and safety guidelines for players.
• Preparing and executing penalty kicks in pressure situations in football.
• Advanced passing techniques in football: long passes, through balls, and more.

Do you need to write a research paper about football but don’t know where to start? Consider our list of football research questions and topics:

• How have football tactics evolved over the past decade?
• The impact of technology on decision-making in football.
• Business industry: trend analysis for soccer .
• The psychology of team cohesion and its effects on football performance.
• What is the role of nutrition and diet in optimizing football players’ performance?
• What is the relationship between football and concussions?
• How do FIFA World Cup events affect host countries’ economies?
• What is the carbon footprint of major football events?
• The effects of climate conditions on football matches.
• Shortage of officials at the high school sports level .
• The influence of social media on football players’ image and brand.
• The role of VAR in the fairness of football matches.
• The impact of home-field advantage in professional football.
• How does the football stadium atmosphere affect player performance?
• The rise of women’s football and its impact on gender equality.
• The economic implications of football player transfers and fees.
• The correlation between a team’s wage bill and on-pitch success.
• Factors influencing fan loyalty in football.
• Research handbook of employment relations in sport .
• The role of leadership and coaching in a team’s success.
• The impact of sponsorship deals on football clubs’ financial stability.
• The relationship between player positioning and successful goal scoring.
• The effects of VAR on the emotions and behavior of fans during football matches.
• How does football influence youth development and participation in sport?
• How can big data analytics improve football performance and decision-making?
• The effects of football on cultural identity and national pride.
• How do sports affect disabled people psychologically ?
• The impact of football on the local community and economy.
• The influence of crowd noise on football referee decisions.
• The role of sports psychology in enhancing football performance.
• The impact of financial fair play regulations on football clubs.
• How does football betting affect match outcomes and integrity?
• The cultural significance of football chants and songs in fan culture.
• Steroid abuse in the world of sports .
• The influence of doping scandals on the reputation of football players and clubs.
• The role of football in promoting social inclusion and breaking down barriers.
• How do international football competitions affect tourism?
• The effects of player transfers on team dynamics and performance.
• The correlation between player height and success in football.
• The influence of different playing surfaces on football player performance and injury rates.
• How do referees maintain fairness and order in football matches?
• Achievement motivation theory in sports psychology .
• The impact of football on academic performance and school attendance.
• The role of football hooliganism in shaping public perceptions of the sport.
• The influence of football sponsorship on brand image and consumer behavior.
• The effects of football on social integration and community cohesion.
• How do rule changes affect football game dynamics?
• The influence of football on individual and societal gender norms.
• Sports analysis: steroids and HGH in sports .
• Investigating the impact of celebrity endorsement on football merchandise sales.
• The role of technology in improving football player performance and injury prevention.
• The correlation between alcohol consumption and football-related violence.
• The impact of fan protests and boycotts on football clubs and leagues.
• The effects of retirement on the mental well-being of former professional football players.
• The influence of football on urban development and infrastructure investment.
• How does football affect students’ academic motivation and educational attainment?
• The impact of football on destination marketing in tourism.

Structuring your essay on football is a piece of cake, and we’re going to prove it! Follow our mini guide with valuable tips and examples!

Football Essay Introduction

The first paragraph of an essay is crucial to creating a strong paper. A successful introduction often starts by addressing broad ideas related to the essay’s topic. Follow the steps below to write a compelling introduction:

1. Start with a hook.

Make a good first impression by using a captivating hook . In football essays, it can include a surprising fact, statistics, a question, or a relevant quote. Here’s an example:

What is the one thing that can unite a country and foster its pride? Yes, it is football!

2. Provide background information.

Give essential details on the essay’s main subject. This part can include the history of your topic, an explanation of key terms, and anything that can help your reader understand the context of your issue.

Football is a group of team sports that involve kicking a ball to score goals.

3. End with a thesis statement.

Put a concise thesis statement at the end to outline your motivation for the paper and present central arguments. Let’s talk about this element in detail.

Thesis Statement about Football

The thesis statement is a sentence expressing the primary idea of a piece of writing and guiding the thoughts within the work.

There are several steps that you should take to develop a thesis statement:

• Research information on your issue.
• Limit your topic to a specific area.
• Brainstorm to come up with interesting ideas.

Look at the example of a football thesis statement:

Football offers the chance to feel pride for the favorite team and positively impacts physical, social, and emotional development.

Essay about Football: Body Paragraphs

The main body of an essay is the most crucial part where you deliver your arguments. Here are some tips on writing a good body paragraph:

• Start with a topic sentence to capture the key points.
• Provide additional information to support your opinion.
• Use a transition sentence to get to the next paragraph smoothly.

Here’s an example of what your topic sentence and supporting evidence might look like:

Topic sentence : Football requires effective communication and listening skills since the game will not work without them. Supporting evidence : Communication helps athletes perform and focus better on the pitch and improves the decision-making process.

Conclusion for Football Essay

A conclusion brings your discussion to a close. The following outline may assist you in completing your essay:

• Restate your thesis.
• Explain why your topic is significant.
• Summarize the core points.
• Call for action or provide an overview of future research opportunities

Check out an example of a paraphrased thesis and the summary of the main points:

Rephrased thesis : Football is a fascinating sport with many societal benefits. Summary : To sum up, football can be considered a hobby, a sport, or an obsession. But still, its most important role is to unite people or even entire countries.

We hope you will find our football topics to write about and research beneficial! Want to receive some more ideas? Try our free online title generator ! Just click the button, and the result will not keep you waiting!

• Health and Wellness | The Football Players Health Study at Harvard University
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• NCAA and the Movement to Reform College Football | Library of Congress
• Medical Issues in Women’s Football | National Library of Medicine
• Football Injuries | University of Rochester Medical Center
• Head to Head: The National Football League & Brain Injury | NYU Langone Health

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Open Access

Peer-reviewed

Research Article

The Anatomy of American Football: Evidence from 7 Years of NFL Game Data

* E-mail: [email protected]

Affiliation School of Information Sciences, University of Pittsburgh, Pittsburgh, PA, United States of America

Affiliation Department of Computer Science and Engineering, University of California Riverside, Riverside, CA, United States of America

• Konstantinos Pelechrinis, 
• Evangelos Papalexakis

• Published: December 22, 2016
• https://doi.org/10.1371/journal.pone.0168716
• Reader Comments

How much does a fumble affect the probability of winning an American football game? How balanced should your offense be in order to increase the probability of winning by 10%? These are questions for which the coaching staff of National Football League teams have a clear qualitative answer. Turnovers are costly; turn the ball over several times and you will certainly lose. Nevertheless, what does “several” mean? How “certain” is certainly? In this study, we collected play-by-play data from the past 7 NFL seasons, i.e., 2009–2015, and we build a descriptive model for the probability of winning a game. Despite the fact that our model incorporates simple box score statistics, such as total offensive yards, number of turnovers etc., its overall cross-validation accuracy is 84%. Furthermore, we combine this descriptive model with a statistical bootstrap module to build FPM (short for Football Prediction Matchup) for predicting future match-ups. The contribution of FPM is pertinent to its simplicity and transparency, which however does not sacrifice the system’s performance. In particular, our evaluations indicate that our prediction engine performs on par with the current state-of-the-art systems (e.g., ESPN’s FPI and Microsoft’s Cortana). The latter are typically proprietary but based on their components described publicly they are significantly more complicated than FPM . Moreover, their proprietary nature does not allow for a head-to-head comparison in terms of the core elements of the systems but it should be evident that the features incorporated in FPM are able to capture a large percentage of the observed variance in NFL games.

Citation: Pelechrinis K, Papalexakis E (2016) The Anatomy of American Football: Evidence from 7 Years of NFL Game Data. PLoS ONE 11(12): e0168716. https://doi.org/10.1371/journal.pone.0168716

Editor: Kimmo Eriksson, Mälardalen University, SWEDEN

Received: July 23, 2016; Accepted: November 23, 2016; Published: December 22, 2016

Copyright: © 2016 Pelechrinis, Papalexakis. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are available within the manuscript and deposited in Github: https://github.com/kpelechrinis/footballonomics .

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1 Introduction

While American football is viewed mainly as a physical game—and it surely is—at the same time it is probably one of the most strategic sports games, a fact that makes it appealing even to an international crowd [ 1 ]. This has led to people analyzing the game with the use of data analytics methods and game theory. For instance, after the controversial last play call of Super Bowl XLIX the Economist [ 2 ] argued by utilizing appropriate data and game theory that this play was rational and not that bad after all.

The ability to analyze and collect large volumes of data has put forward a quantification-based approach in modeling and analyzing the success in various sports during the last few years. For example, pertinent to American football, Clark et al. [ 3 ] analyzed the factors that affect the success of a field goal kick and contrary to popular belief they did not identify any situational factor (e.g., regular vs post season, home vs away etc.) as being significant. In another direction Pfitzner et al. [ 4 ] and Warner [ 5 ] studied models and systems for determining a successful betting strategy for NFL games, while the authors in [ 6 ] show that the much-discussed off-field misconduct of NFL players does not affect a team’s performance. Furthermore, the spatial information collected from the RFID sensors on NFL players has been used to evaluate quarterbacks’ decision making ability [ 7 ], while efforts to assess the impact of individual offensive linemen on passing have been presented by Alamar and Weinstein-Gould [ 8 ]. Similarly, Correia et al. [ 9 ] analyzed the passing behavior of rugby players—the most similar sport to that of American football. They found that the time required to close the gap between the first attacker and the defense explained 64% of the variance found in pass duration and this can further yield information about future pass possibilities. Nevertheless, despite the availability of play data for American football and the proliferation of the sports analytics literature as well as the literature surrounding the NFL, there are only few—publicly open—studies that have focused on predicting a game’s outcome. Furthermore, some of the existing models make strong theoretical assumptions that are hard to verify (e.g., the team strength factors obeying to a first-order autoregressive process [ 10 ]). Close with our work, Cohea and Payton developed a logistic regression model to understand the factors affecting an NFL game outcome [ 11 ]. The benefit of our model as compared to the one presented by Cohea and Payton [ 11 ] is that the number of exploratory variables we are using is much smaller, making it easy for a fan to follow. Most importantly though we combine our model with statistical bootstrap in order to facilitate future game predictions (something that the model presented in [ 11 ] is not able to perform). Of course, predictive models for NFL games have been developed by major sports networks. For example ESPN has developed the Football Power Index, which is used to make probabilistic predictions for upcoming matchups [ 12 ]. Software companies have also developed their own models (e.g., Cortana from Microsoft [ 13 ]). Nevertheless, these models are proprietary and are not open to the public.

In this study we are first interested in providing a simple model that is able to quantify the impact of various factors on the probability of wining a game of American football. How much does a turnover affect a team’s probability of winning? Can you really win a game after having turned the ball over 5 times? While coaches and players know the qualitative answer to similar questions, the goal of our work is to provide a quantitative answer. For this purpose we use play-by-play data for the last seven seasons of the National Football League (i.e., between 2009 and 2015) and we extract specific team statistics for both the winning and losing teams. We then use the Bradley-Terry regression model [ 14 , 15 ] to quantify the effect and statistical significance of each of these factors on the probability of wining a game of American football. This model is a descriptive one, i.e., it quantifies the impact of several factors on the success of an NFL team. Similar descriptive models can be useful to the coaching staff since they provide an exact quantification of the importance of each aspect of the game. They can also be helpful for the fans—especially the novice ones—for better understanding of the game. Evaluating the obtained model through cross validation provides an accuracy of 84% in predicting the winning team of a matchup.

The above descriptive model is able to provide accurate predictions when the features are known, i.e., when the performance of the two competing teams of a matchup is known. This can be helpful in post analysis of games by comparing the actual outcome of the game with the expected probability of winning the game for each team given their performance. For instance, one can identify “unexpected” wins from teams that underperformed . However, even more challenging, and one of the most intriguing tasks for professional sports analysts, is predicting the winners of the upcoming NFL matchups, which is the second objective of our work. This task can not be completed simply by the regression model that quantifies the impact of various factors on the probability of winning a game. As we will elaborate on in following sections the majority of the features in the developed model includes performance statistics (e.g., total offensive yards, number of interceptions etc.). Hence, the winner prediction problem involves also predicting the features—i.e., the performance of each team—themselves.

Predicting the upcoming performance of a team can be based on its past performance. A factor that makes this task particularly hard for American football is the small number of games during a season, which translates to high uncertainty. Using a central tendency metric—e.g., mean—is not able to fully capture the variability of the performance. To tackle this problem we propose to use statistical bootstrap. In brief, resampling with replacement the features from the past games of a team will allow us to simulate the matchup between the teams several times and obtain a set of winning probabilities that will allow us to predict the final winner of the game. Our approach, FPM , is shown to exhibit an accuracy of approximately 64% over the past 7 seasons, which is comparable to that of the state-of-the-art systems such as Microsoft’s Cortana and ESPN’s FPI. However, given FPM ’s simplicity it should be treated as a baseline estimation. Simply put the output probability of our model can be thought of as an anchor value for the win probability. Further adjustments can be made using information about the specific matchup (i.e., roster, weather forecast etc.), hence, making it possible to significantly outperform existing proprietary systems. We further discuss this point in detail later in this work.

Our work complements the existing literature by contributing a descriptive and easily interpretable model for American football games. We further provide a prediction engine for upcoming matchups based on statistical bootstrap and the developed Bradley-Terry regression model. We would like to emphasize here that our regression model is rather simple and easy to implement. This, in fact, is one of our main contribution, since we demonstrate that such a simple and transparent approach is able to perform on par with state-of-the-art commercial tools for which due to their proprietary nature we have no telling of how complex they are. We view this as a first step towards exploring how we can maintain a simple and interpretable model that at the same time bears high predictive quality. In the rest of the study we present the data and methods that we used (see Section 2 ). We then present our regression model as well as FPM (see Section 3 ). We finally conclude and discuss the implications of our study (see Section 4 ).

2 Materials and Methods

In this section we will present the dataset we used to perform our analysis as well as the different methodological pieces of our analysis.

NFL Dataset: In order to perform our analysis we utilize a dataset collected from NFL’s Game Center for all the games (regular and post season) between the seasons 2009 and 2015. We access the data using the Python nflgame API [ 16 ]. The dataset includes detailed play-by-play information for every game that took place during these seasons. In total, we collected information for 1,792 regular season games and 77 play-off games. Given the small sample for the play-off games and in order to have an equal contribution in our dataset from all the teams we focus our analysis on the regular season games, even though play-off games are by themselves of interest in many perspectives.

Statistical Bootstrap: In order to perform a game outcome prediction, we first need to forecast the performance of each of the contesting teams. However, we only have a (small) set of historic performance data for each team. Furthermore given that the performance of a team is not stable , using a measure of central tendency (e.g., sample mean) does not accurately capture the variability in the data. To overcome this problem we will rely on statistical bootstrap [ 17 ]. Statistical bootstrap is a robust method for estimating the unknown distribution of a population’s statistic when a sample of the population is known. The basic idea of the bootstrapping method is that in the absence of any other information about the population, the observed sample contains all the available information about the underlying distribution. Hence resampling with replacement is the best guide to what can be expected from the population distribution had the latter been available. By generating a large number of such resamples allows us to get a very accurate estimate of the required distribution. Furthermore, for data with dependencies (temporal or otherwise), appropriate block resampling retains any dependencies between data points [ 18 ]. We will utilize bootstrap in the design of FPM .

3.1 Descriptive Model

In this part of our study we will present our descriptive generalized linear model. In particular, we build a Bradley-Terry model to understand the factors that impact the probability of a team winning an American football game. This model will be later used in our future matchup prediction engine, FPM , as we describe in Section 3.2.

Let us denote with W ij the binary random variable that represents the event of home team i winning the game against visiting team j . W ij = 1 if the home team wins the game and 0 otherwise. As aforementioned our model for W ij will provide us with the probability of the home team winning the game given the set of input features, i.e., y = Pr( W ij = 1| z ). The input of this model is vector z that includes features that can potentially impact the probability of a team winning.

The features we use as the input for our model include:

Total offensive yards differential: This feature captures the difference between the home and visiting teams’ total yards (rushing and passing) produced by their offense in the game.

Penalty yards differential: This features captures the differential between the home and visiting teams’ total penalty yards in the game.

Turnovers differential: This feature captures the differential between the total turnovers produced by the teams (i.e., how many times the quarterback was intercepted, fumbles recovered by the opposing team and turns on downs).

Possession time differential: This feature captures the differential of the ball possession time between the home and visiting team.

This ratio captures the offense’s balance between rushing and passing. A perfectly balanced offense will have r = 0.5. We would like to emphasize here that r refers to the actual yardage produced and not to the passing/rushing attempts. The feature included in the model represents the differential between r home and r visiting .

Power ranking differential: This is the current difference in rankings between the home and the visiting teams. A positive differential means that the home team is stronger , i.e., ranks higher, than its opponent. For the power ranking we utilize SportsNetRank [ 19 ], which uses a directed network that represents win-lose relationships between teams. SportsNetRank captures indirectly the schedule strength of a team and it has been shown to provide a better ranking for teams as compared to the simple win-loss percentage.

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https://doi.org/10.1371/journal.pone.0168716.t001

Based on the Kolmogorov-Smirnov test the features’ ECDFs for the winning and losing teams are statistically different (at the significance level α = 0.01). The probability mass function for the home team advantage is also presented.

https://doi.org/10.1371/journal.pone.0168716.g001

Our basic data analysis above indicates that the distribution of the statistics considered is significantly different for the winning and losing teams. However, we are interested in understanding which of them are good explanatory variables of the probability of winning a game. To further delve into the details, we use our data to train the Bradley-Terry regression model and we obtain the results presented in Table 2 . Note here that, as it might be evident from the aforementioned discussion, we do not explicitly incorporate a feature for distinguishing between the home and the visiting team. Nevertheless, the response variable is the probability of the home team winning, while the features capture the differential of the respective statistics between the home and road team (i.e., the difference is ordered). Therefore, the intercept essentially captures the home team advantage—or lack thereof depending on the sign and significance of the coefficient. In fact, setting all of the explanatory variables equal to zero provides us a response equal to Pr( W ij | 0 ) = 0.555, which is equal to the home team advantage as discussed above. Furthermore, all of the coefficients—except the one for the possession time differential—are statistically significant. However, the impact of the various factors as captured by the magnitude of the coefficients range from weak to strong. For example, the number of total yards produced by the offense seem to have the weakest correlation with the probability of winning a game (i.e., empty yards). On the contrary committing turnovers quickly deteriorates the probability of winning the game and the same is true for an unbalanced offense. Finally, in S1 Text we present a standardized version of our model.

Significance codes: ***: p < .001, **: p < .01, *: p < .05.

https://doi.org/10.1371/journal.pone.0168716.t002

While the direction of the effects for these variables are potentially intuitive for the coaching staff of NFL teams, the benefit of our quantifying approach is that it assigns specific magnitude to the importance of each factor. Clearly the conclusions drawn from the regression cannot and should not be treated as causal. Nevertheless, they provide a good understanding on what is correlated with winning games. For example, if a team wins the turnover battle by 1 it can expect to obtain an approximately 20% gain in the winning probability (all else being constant), while a 10-yard differential in the penalty yardage is correlated with just a 5% difference in the winning probability. Hence, while almost all of the factors considered are statistically significant, some of them appear to be much more important as captured by the corresponding coefficients and potential parts of the game a team could work on. Again, this descriptive model does not provide a cause-effect relationship between the covariates considered and the probability of winning .

Before turning to the FPM predictive engine we would like to further emphasize and reflect on how one should interpret and use these results. For example, one could be tempted to focus on the feature with the coefficient that exhibits the maximum absolute magnitude, that is, the differential of ratio r , and conclude that calling only run plays will increase the probability of winning, since the negative differential with the opposing team will be maximized. However, this is clearly not true as every person with basic familiarity with American football knows. At the same time the regression model is not contradicting itself. What happens is that the model developed—similar to any data driven model—is valid only for the range of values that the input variables cover. Outside of this range, the generalized linear trend might still hold or not. For example, Fig 2 depicts the distribution of ratio r for the winning and losing teams. As we can see our data cover approximately the range r ∈ [0.3, 0.98] and the trend should only be considered valid within this range (and potentially within a small ϵ outside of this range). It is interesting also to observe that the mass of the distribution for the winning teams is concentrated around r ≈ 0.64, while it is larger for the losing teams ( r ≈ 0.8). We also present at the same figure a table with the range that our features cover for both winning and losing teams. Furthermore, to reiterate, the regression model captures merely correlations (rather than cause-effect relations). Given that some of the statistics involved in the features are also correlated themselves (see Fig 3 ) and/or are result of situational football, makes it even harder to identify real causes. For instance, there appears to be a small but statistically significant negative correlation between ratio r and possession time. Furthermore, a typical tactic followed by teams leading in a game towards the end of the fourth quarter is to run the clock out by calling running plays. This can lead to a problem of reverse causality; a reduced ratio r for the leading team as compared to the counterfactual r expected had the team continued its original game-plan, which can artificially deflate the actual contribution of r differential on the probability of winning. Similarly, teams that are trailing in the score towards the end of the game will typically call plays involving long passes in order to cover more yardage faster. However, these plays are also more risky and will lead to turnovers more often, therefore, inflating the turnover differential feature. Nevertheless, this is always a problem when a field experiment cannot be designed and only observational data are available. While we cannot claim causal links between the covariates and the output variable, in what follows we present evidence that can eliminate the presence of reverse causality for the scenarios described above.

Our model is trained within the range of input variable/statistics values on the left table. The figure on the right presents the probability density function for r for the winning and losing instances respectively.

https://doi.org/10.1371/journal.pone.0168716.g002

Correlations between the different variables considered for obtaining the features for FPM . Insignificant correlations are crossed out.

https://doi.org/10.1371/journal.pone.0168716.g003

Reverse Causality: In what follows we examine the potential for reverse causality. To fast forward to our results, we do not find strong evidence for it. To reiterate, one of the problems with any model based on observational data is the direction of the effects captured by the model. For example, in our case teams that are ahead in the score towards the end of the game follow a “conservative” play call, that is, running the football more in order to minimize the probability of a turnover and more importantly use up valuable time on the clock. Hence, this can lead to a decreasing ratio r . Therefore, the negative coefficient for the r differential in our regression model might be capturing reverse causality/causation. Winning teams artificially decrease r due to conservative play calling at the end of the game. Similarly, teams that are behind in score towards the end of the game follow a more “risky” game plan and hence, this might lead to more turnovers (as compared to the other way around).

One possible way to explore whether this is the case is to examine how the values of these two statistics change over the course of the game. We begin with ratio r . If the reverse causation hypothesis were true, then the ratio r for the winning team of a game would have to reduce over the course of the game. In order to examine this hypothesis, we compute the ratio r at the end of each quarter for both the winning and losing teams. Fig 4 presents the results. As we can see during the first quarter there is a large variability for the value of r as one might have expected mainly due to the small number of drives. However, after the first quarter it seems that the value of r is stabilized. There is a slight decrease (increase) for the winning (losing) team during the fourth quarter but this change is not statistically significant. Therefore, we can more confidently reject the existence of reverse causality for ratio r .

Ratio r is stable after the first quarter for both winning (left figure) and losing (right figure) teams, allowing us to reject the reverse causation hypothesis for r .

https://doi.org/10.1371/journal.pone.0168716.g004

We now focus our attention on the turnovers and the potential reverse causation with respect to this feature. In order to examine this hypothesis, we obtain from our data the time within the game (at the minute granularity) that turnovers were committed by the winning and losing teams. We then compare the paired difference for the turnover differential until the end of the third quarter for each game. Our results show that the winning teams commit fewer turnovers than their losing opponents by the end of the third quarter ( p -value < 0.01), further supporting that avoiding turnovers will ultimately lead to a win. Of course, as we can see from Fig 5 , there is a spike of turnovers towards the end of each half (and smaller spikes towards the end of each quarter). These spikes can be potentially explained from the urgency to score since either the drive will stop if the half ends or the game will be over respectively. However, regardless of the exact reasons for these spikes, the main point is that by committing turnovers, either early in the game (e.g., during the first three quarters) or late, the chances of winning the game are significantly reduced.

Turnovers spike towards the end of each quarter, with the highest density appearing during the two-minute warning.

https://doi.org/10.1371/journal.pone.0168716.g005

In conclusion, our model provides quantifiable and actionable insights but they need to be carefully interpreted when designing play actions based on it.

3.2 FPM Prediction Engine

We now turn our attention on how we can use the above model to predict the outcome of a future game. In a realistic setting, in order to be able to apply this regression model we will need to provide as an input the team statistics/features. This is by itself a separate prediction problem, namely, a team performance prediction problem. Hence, we begin by evaluating the prediction performance of the Bradley-Terry regression model itself using traditional machine learning evaluation methods. In particular, we evaluate the prediction accuracy of our model through cross validation. In this way we do not need to predict the value of the features but we explore the accuracy of the pure regression model. Using 10-fold cross validation we obtain an accuracy of 84.03% ± 0.35% . To reiterate this performance is conditional to the input features being known. From the inputs required for our model only two are known before the matchup, namely, the home team (which will allow us to formulate the response variable and the rest of the features appropriately) and the SportsNetRank differential. Thus, how can we predict the rest of the features, since in a realistic setting we will not know the performance of each team beforehand? Simply put, our FPM prediction engine will need to first estimate the two teams statistics/features (i.e., total yards, penalty yards, etc.) and then use the Bradley-Terry regression model to predict the winning team.

The proposed prediction engine consists of 3 modules; a bootstrap module, a regression module and a statistical test module.

https://doi.org/10.1371/journal.pone.0168716.g006

Delving more into the evaluation of our predictive engine we present the accuracy for each season in Table 3 . We also provide the accuracy of a baseline system, where the winner of a game is predicted to be the team with the better running win-loss percentage through the current week. If two teams have the same win-loss percentage the home team is chosen as the winner since there is a slight winning bias for the home team as we have seen earlier. Note here that the baseline is very similar to the way that the league ranks the teams and decides on who will qualify for the playoffs (excluding our tie-breaker process and the league’s rules with respect to the divisions). As we can see our predictive engine improves over the baseline by approximately 9%.

FPM outperforms the baseline prediction based on win-loss standings every season in our dataset. The overall accuracy of our system is 63.4%.

https://doi.org/10.1371/journal.pone.0168716.t003

One of the reasons we utilize bootstrap in our prediction system is to better capture the variability of the teams’ performances. As one might expect this variability is better revealed as the season progresses. During a stretch of few games it is highly probable to have a team over/under-perform [ 22 ]. Hence, the bootstrap module during the beginning of the season might not perform as accurately as during the end of the season. In order to examine this we calculate the accuracy of our prediction system focusing on games that took place during specific weeks in every season. Fig 7 presents our results, where we see that there is an increasing trend as the season progresses.

During the last part of the season the bootstrap engine can exploit the variability of a team’s performance better, hence, providing better prediction accuracy. The linear trend slope is 0.01 (p-value<0.05, R 2 = 0.41).

https://doi.org/10.1371/journal.pone.0168716.g007

Finally, we examine the accuracy of FPM ’s predicted probabilities. In order to evaluate this we would ideally want to have the game played several times. If the favorite team were given a 75% probability of winning, then if the game was played 100 times we would expect the favorite to win 75 of them. However, we cannot have the game play out more than once and hence in order to evaluate the accuracy of the probabilities we will use all the games in our dataset. In particular, if the predicted probabilities were accurate, when considering all the games where the favorite was predicted to win with a probability of x %, then the favorite should have won in x % of these games. Given the continuous nature of the probabilities we quantize them into groups that cover a 5% probability range (with only exception being the range (90%, 100%], since there are very few games in the corresponding sub-groups). Fig 8 presents on the y-axis the fraction of games where the predicted favorite team won, while the x-axis corresponds to the predicted probability of win for the favorite. As we can see the data points—when considering their 95% confidence intervals—fall on the y = x axis, which translates to an accurate probability inference. The corresponding linear regression provides a slope with a 95% confidence interval of [0.76, 1.16] ( R 2 = 0.94), which essentially means that we cannot reject the null hypothesis that our data fall on the line y = x where the slope is equal to 1.

The win probability provided by our model is in alignment with the fraction of the games won by the favorite for the corresponding win probability.

https://doi.org/10.1371/journal.pone.0168716.g008

4 Discussion and Conclusions

Finally, the models themselves can be helpful to many different involved entities associated with the sport. For example, it can facilitate better understanding of the game by novice fans. The impact and importance of ratio r will allow the newcoming fans to appreciate the running game. Similarly, agents and players can use knowledge obtained by similar models for negotiating purposes. It is well-known that running backs are among the least paid players in an NFL roster for a number of reasons (e.g., high risk of serious injuries etc.). Nevertheless, they are extremely important for the success of a team as our model indicates. Moreover, our descriptive regression model can be used by media personnel for a post-game analysis. For instance, “surprising” wins can be identified, while critical parts of the game that led to the final results can also be pinpointed.

Supporting Information

S1 text. standardized fpm ..

https://doi.org/10.1371/journal.pone.0168716.s001

Author Contributions

• Conceptualization: KP.
• Data curation: KP.
• Formal analysis: KP EP.
• Investigation: KP.
• Methodology: KP EP.
• Project administration: KP EP.
• Resources: KP EP.
• Software: KP.
• Supervision: KP.
• Validation: KP.
• Visualization: KP.
• Writing – original draft: KP EP.
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Innovation and Technology in Sports pp 245–257 Cite as

Football Analytics for Goal Prediction to Assess Player Performance

• Danish Javed 14 ,
• N. Z. Jhanjhi 14 &
• Navid Ali Khan 14  
• Conference paper
• First Online: 18 April 2023

322 Accesses

Part of the book series: Lecture Notes in Bioengineering ((LNBE))

Machine learning techniques are often used for sports analytics, such as player health prediction and avoidance, appraisal of prospective skill or market worth, and predicting team or player performance. This reshapes the sports performance and helps in coaching the teams and individuals. This research focuses on football analytics, which can help football managers and coaches for reshaping the performance of players to target the goal with higher accuracy and precision. The match results depend on the successful number of goals; any minor mistake may lead to failure. Other statistics, like shots on target and game possessions, have been gaining popularity in recent years. Several attributes are utilized to train an anticipated goal model formed by monitoring football data to evaluate the chance of a shot being a goal. Using historical data and advanced analytics, a credible prediction of a goal, as well as player and team performance, can be deduced. Furthermore, we address the identification and recording of personal talents and statistical categories that distinguish an exceptional goal scorer from the worst goal scorer through football analytics. Feature selection, data size, and parameters used may impact the results of the model. Our research proposes a Goal Prediction Model (GPM) with player analysis trained on data from 9,074 games, including 941,009 events from Europe's top 5 leagues containing the information of five seasons. Our model will explain the observations on expected goals through football analytics and monitor the performance of the players with respect to anticipated goals. This research could benefit football team managers and coaches by reshaping the performance of players.

• Goal prediction
• Football analytics
• Machine learning
• English Premier League
• Spanish La Liga
• Italian Serie A
• French League 1
• German Bundesliga

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Javed, D., Jhanjhi, N.Z., Khan, N.A. (2023). Football Analytics for Goal Prediction to Assess Player Performance. In: Syed Omar, S.F., Hassan, M.H.A., Casson, A., Godfrey, A., P. P. Abdul Majeed, A. (eds) Innovation and Technology in Sports. Lecture Notes in Bioengineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-0297-2_20

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218 Football Essay Topic Ideas & Examples

In your paper, you can talk about famous soccer players, or you could discuss the physics involved in a standard game. Our team came up with 130 football topics to write about in this article to help you find the right idea.

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• Which Is More Profitable, Baseball or Football? There are other sports which are more profitable than the two but the argument here boils to which sport between the two is more profitable. In regard to the ticket price, baseball becomes more profitable […]
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• The Offside Rule Concept in Football An offside position is a situation when a player of the attacking team is closer to the opponent’s goal than the ball and the opponent’s last player except for the goalkeeper during passing.
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• Fifa Football Organization: Marketing Strategy Prospective marketing partners are categorically divided as, FIFA partner, FIFA world cup sponsor and national supporter.
• Strategies of Football and Tennis Coaches in the UK To identify the coaching leadership styles used by football and tennis coaches To compare the motivations for using coaching leadership style in football and tennis To uncover the effect of the coaching leadership styles on […]
• Plyometric Training for Female Soccer Players Jump performance capabilities were confirmed to improve in all the studies except the one by Ramirez-Campillo et al, who found the implementation of plyometric training is not associated with the extra impacts on female soccer […]
• Geometry Web Quest for Soccer, Baseball, Basketball, Bowling, Golf, Volleyball and Pool Field for golf is the biggest and made of grass, sand and water and is the biggest and it has no fixed shape. Soccer field is made of grass or synthetic material and is the […]
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• Impediments to Football Development This could not be attributed to the standard of the game in the leagues but probably other factors within the administration and the players and fans. Of importance is the structure of the administration of […]
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• Legislations and Their Contributions to Football Safety This was largely as a result of a collision between two sets of people who were leaving and entering the stadium; these fans were reacting to the activities going on in the field and most […]
• The Lack of Soccer Popularity in the U.S. Lack of soccer popularity can be traced from historic events as well as the lifestyle of Americans.”American children grow up with the mentality that soccer is to be played for fun which is not an […]
• Manchester United – Football and Finance Football is a game that is played all across the globe; millions of fans watch the game each day and enjoy the experience of watching it.
• FIFA’s Public Image: Issues and Mitigate the Damage It is strongly recommended that the president does everything in their power to assist the FBI and any other authorities in reviewing the conduct of FIFA’s executives.
• Ernie Davis as a Football Role Model He was an exceptional player born ahead of his time, as he stood out on the football field as the first African American to win the Heisman trophy in 1961, and to be chosen for […]
• Soccer Articles About Kings of Diving Further, it is intriguing to realize that not only is it a commonplace practice, but it is utilized by some of the top players in the league.
• FIFA 10 Football Simulation Video Game A lack of consistency is evident in the various versions of this game as FIFA 10 played on a PC lacks the realism that is exhibited when the game is played on XBOX 360 and […]
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• Manning’s Leadership Within and Beyond Football Sport is a field where the competition is the core of the whole activity, and the quality of the teamwork defines the whole result.
• Soccer and National Identity The jubilation and merry that is evident during the topmost soccer challenge in the world commonly referred to as FIFA world cup is testimony to the immense love that fans have for this game as […]
• The Modernization of the Global Football Industry The popularity and development of the football industry is a result of multiple factors and events which had an impact on football fans and proliferation of facts.
• Marshall University’s Football Team After the 1970 Tragedy The tragedy that befell the Marshall University’s football team on 14th November 1970 and the appointment of the new football coach Jack Lengyel represents a scenario when managers can be faced with difficulties in their […]
• International Relations, Development and the Football Industry The paper is proposed to be divided into two parts: first will deal with football and its usage in political diplomacy will be discussed along with football as a means of creating national identity in […]
• Gold Coast United Football Club Marketing Situation They have made several efforts to ensure the success of this goal by hiring the winner of the golden boot, the goal of the year in 2008/9 Shane Smeltz and Jason Culina, the captain of […]
• European Soccer: The Final UEFA Cup Match On the whole with the rest of Shakhtar players the game spread out on the whole area of the field and change for rather long periods of time the halves of the field provoking alternate […]
• UEFA Cup Football Competition Winners and Histor With the merging of the UEFA Cup Winner’s Cup to the UEFA Cup in 1999, domestic cup competition winners could now enter the UEFA Cup competitions.
• Gaming Industry: FIFA 09 Analysis The advertisement which will be analyzed in this paper is of FIFA 09, the game is a sequel to the FIFA series which is released by EA sports each year.
• The History of Alabama Football: The Stadium, Team and Passion Before the home game began there was a video that was sent showing the famous play from Alabama history which had the voice of the founder of this team that is the bear Bryant and […]
• Football Industry in Africa: Socially Responsible Business? Football is a game that is played all across the globe; millions of fans watch the game each day and enjoy the experience of watching it.
• Relation Between Money and Football In the English league, clubs have been spending millions to sign up a player in the hope that the player will turn the fortunes of the company for the good.
• Soccer in America: Its History, Origin, Evolution, and Popularize This Sport Among Americans The coverage of the history of this game which is also popularly known as soccer is quite diverse and different ideas have been put across as to where the game originated and its evolution to […]
• Canadian Women’s Soccer Team’s Sport Marketing This paper identifies the best sponsor for the Canadian Women’s Soccer Team and how the two can collaborate to deliver positive results.
• Promoting Tumi Bags at the National Football League The audience will want to win Tumi products subconsciously, and in the future, fans will associate the goods of this manufacturer with excitement and victory.
• The First Aid Knowledge of Youth Soccer Coaches To establish the interrelationship between the years of work and success in the First Aid Assessment test, a Pearson Product Correlation was used.
• Soccer: Transmitting Real Information on the Game However, a significant degree of controversy in the ways soccer players are depicted in the media tend to create a negative image of the game of millions.
• Soccer Influence on Sociopolitical Aspects of WWI During this period, many footballers and athletes were tempted or encouraged to join the militaries of their respective countries and become part of the ongoing war.
• Soccer in the US and American Exceptionalism Soccer is one of the most popular sports in the world in terms of viewership and participation. The fact that America is not the best in terms of producing the best soccer talents explains why […]
• Senior Management: Soccer Tournament It is chosen as the central deliverable because the successful organization of the tournament is the most desirable outcome of the project.
• Pharmaceutical Firm as a Football Association Sponsor The image of the pharmaceutical industry is that of a bastion of health which is inconsistent with what most FIFA sponsors the project.
• Medical Marijuana Legalization by National Football League However, it must be realized that some of these players are usually in excruciating pain to the point that some may have lost consciousness.
• Sports Science Principles in Melbourne Football Club The intervention will involve a three-pronged approach designed to tackle most of the causes of poor on-field performance in Melbourne Football Club.
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• Federation International Football Association Management Specifically, in a later section, the paper will highlight issues such as poor governance, the flouting of various ethical principles, and mismanagement of the organization’s resources as key elements that triggered the need for leadership […]
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• Virtual Reality Technology in Soccer Training Therefore, it is imperative to invest in this area to protect the safety of our technology and ensure that we have a viable product.
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• Soccer in England, Its History and Popularity With this in mind, it is possible to say that is the most popular game nowadays, soccer can be taken as a unique phenomenon in the world of sport.
• Football, Its Objective, Players, and a Coach This game is very intense, and it is hard for one official to keep track of all the action, and assistant referees are needed.
• Arsenal Ladies Football Club’s History and Effects The main intention of the Arsenal Ladies Soccer group is to recognize the outstanding feminine players with football aptitudes and admitting them in the educational and technical programs.
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• Biosensors in Soccer Players’ Preparation The second step is associated with the formation of the movements and their absorption to specific imperatives in a situation where a few alterations will be required.
• National Football League’s Social Performance The success of NFL is also attributed to the ‘survivalist’ mentality of the organization. Community members are very significant and influential to the operations of NFL.
• Fantasy Football: Gambling Regulation and Outlawing Taking this into consideration, it can be stated that fantasy football and its other iterations on sites like Draft Kings is not a form of gambling.
• Planning for an Intramural Soccer Event The same goes for the organization of games, recruitment of referees, and raising the money required to hold the event. The operational plan was a significant determinant of the success of the event.
• The Australian Football League Expansion The Australian Football League is the most competitive professional competition in the sport of Australian Rules football. The final marks the end of the season and the winning team is crowned as ‘the ‘premiers.
• Total Quality Management in the EU and Football Association The European Commission and the council of the European Union are the chief institutions of the EU. In addition, the court of Justice of the European Union is a key legal institution of the EU.
• Football in Saudi Arabia: The Soccer Al Nasser Club The sport was introduced to the Kingdom following the relations between the Europeans and the Saudis in the 20th century. The club has many supporters in Riyadh and the rest of the country.
• The Developement of Soccer in the Past Century The side that will have put in the most goals at their opponents’ side by the ending of the game is the winner.
• Addicted 2 Football Business Plan Principally, the advertising of the filming will show the quality of the work I will be producing. The equipment to be purchased will show the quality of the professionals.
• Melbourne Football Club Marketing Analysis Members and supporters of the players want to see an overhaul of the operation and management of the Club. Rationale The Demons need to rebuild their brand by making changes to the club and marketing […]
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• History of England Football
• History of Womens Football in England
• How Do Leadership Styles and Motivational Theories Affect the Success and Failure of the Football Clubs?
• Does Pro Football Have a Positive or Negative Effect on Society?
• What Impact Has the Commercialization of English Football?
• How Does American Football Work?
• Are Football Referees Biased and Inconsistent?
• How Are Concussions Affecting Football in High School?
• Does Football Need More Statistics?
• What Will Football Look Like in the Future?
• How Are Women Portrayed in American Football Compared to Men?
• Did UEFA’s Financial Fair Play Harm Competition in European Football Leagues?
• How Does the Media Portray Football Hooliganism?
• Does Sports Performance Influence Revenues and Economic Results in Spanish Football?
• How Does the Stadium Atmosphere at a College Football Game Affect Behavioral Intentions Across Gender Lines?
• Are Football Wages Out of Control?
• How “Fair” Are Football’s Financial Fair Play Regulations?
• Does College Football Impact the Size of University Applicant Pools and the Quality of Entering Students?
• How Far Football Stadia Resemble the Roman Colosseum in Their Provisions for Spectators?
• Does the Australian Football League Draft Undervalue Indigenous Australian Footballers?
• How Has the NFL Changed Over the History of Football?
• Should College Football Players Be Paid?
• How Much Does the Air Pressure Within a Football Matter?
• Should Girls Have Equal Representation on Football Teams?
• How Does NCAA Division Make Money on College Football?
• Should High School Football Be Banned?
• Why Is Football Called Football?
• Should Parents Let Their Children Play Tackle Football?
• How Does Playing Football Develop Useful Skills?
• How Has Sports Marketing Changed College Football?
• What Does the Motivation of Coaches Effect Football Players?
• Chicago (A-D)
• Chicago (N-B)

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Bibliography

IvyPanda . "218 Football Essay Topic Ideas & Examples." February 24, 2024. https://ivypanda.com/essays/topic/football-essay-topics/.

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150 Football Essay Topics & Soccer Research Topics

Are you a soccer player? If yes, then you will enjoy writing a soccer-themed essay! To make the writing process even easier, we present to you our list of football essay topics and samples. Check them out below!

• 🔝 Top 10 Football Research Topics for 2024

🏆 Best Football Topics to Write About

✍️ football essay topics for college, 👍 good football research topics & essay examples, 🎓 most interesting soccer research topics, 💡 simple football essay ideas, ❓ research questions about football, 🔝 top 7 football research topics for 2024.

• The 2022 FIFA World Cup
• Soccer and Basketball Differences
• Football Watching as Entertaining Action
• Liverpool Football Club’s Strategic (PESTLE) Analysis
• The Physics Behind Football
• Environmental Impact of the Football Stadium Construction
• Advertisement in Soccer Overview
• American Football League v. National Football League Case The American Football league, abbreviated as AFL, filed a lawsuit against the national football league (NFL) on the grounds of the Anti-Trust Act breach.
• Spanish Football League Spain is one of the countries that have dominated the game of football over the last couple of years. The country has achieved success with its senior and junior national teams.
• Impact of Qatar Hosting FIFA World Cup 2022 This paper discusses the impact of Qatar hosting the FIFA World Cup in 2022, specifically on its brand image and business operations.
• Should Football Be Banned for Being Too Violent and Dangerous? The essay ponders whether the game of football is dangerous and violent, and it should be banned, or are there other ways to reduce the possibility of players’ injuries.
• Soccer in the US, Its Development and Popularity The main factor which impacted the development and popularity of soccer in the United States is the public’s area of interest.
• Event Management Analysis: Local Soccer Championship Even management requires careful and detailed analysis and planning in order to avoid a project failure and create an impressive and amazing setting for visitors.
• Soccer and Other Sports as a Communication Medium The paper discusses the ways sports communication potential is exploited by companies and organizations and how they use sports personalities charisma.
• FIFA and Corruption In other words, FIFA is a kind of a football image, and it has to be deprived of various unethical and immoral practices.
• “Fordson: Faith, Fasting, Football” Documentary “Fordson: Faith, Fasting, Football” is a film about a community of Muslim Americans, who are focused on their passion and support for the Fordson High School football team.
• Football in Ghana and Its Relationship with the Rest of the World (Player Transfers) Football is one of the most popular sports not only in Ghana but in the region of Africa and the global society.
• Reasons Why Kids Should Not Play Tackle Football The brain might repair itself, but the consequences of the injury usually last longer and include memory loss, headaches, and similar cognitive dysfunctions.
• The Qatar 2022 FIFA World Cup Bid The award of hosting the World Cup in 2022 for Qatar came as a surprise to Australia and the USA, which many people thought could win the rights.
• Goal Line Technology and Football Football matches are not only about the issue of teamwork but also about strict competition and the importance of the defining last-minute goal which can tip the scale between victory and defeat.
• Training Programs for a High School Quarterback Football Player The article addresses the specific exercises that the quarterback player should take and the duration, the number of sets, the reps, and the rest intervals.
• Real Madrid and Barcelona Football Clubs History Real Madrid and Barcelona are the top European Football Clubs, which are usually opposed to each other. During the long time they applied different strategies to achievements in sport.
• FIFA World Cup: History and Future The FIFA World cup is a soccer competition that is contested internationally by national soccer teams composed exclusively of male players.
• Planning Franz Beckenbauer Charity Football Match Today I will be presenting my event management plan for the upcoming Franz Beckenbauer Charity Football Match.
• Is Watching Football Morally Acceptable The public opinion on the morality of watching football, or other competitive sports, is divided, as there are clear dangers associated with participating in football matches.
• The National Football League Team Moving to the City of Omaha Moving the National Football League team to the city of Omaha, Nebraska, will have a positive financial influence on the citizens residing within its boundaries.
• The Negotiation Process in Football The main issue being negotiated is the extension of a playing contract for A. J. Washington, a quarterback participating in the Los Angeles Spartans of National Football League.
• Qatar Hosting FIFA World Cup 2022 FIFA World Cup is one of the largest soccer tournaments in the world. It is scheduled to occur in 2022, and the host country will be Qatar.
• American Sports: Football, Soccer, Basketball Some games have grown to be recognized as official sports with strict rules, governing institutions, and international events.
• Negotiations Between National Football League and NFL Players Association Approving the proposed 2020 NFL CBA faced a significant amount of backlash from the players due to some of the issues that were not addressed in the agreement.
• Organizational Theories in Australian Football League (AFL) This essay applies these two concepts to the operations of the Australian Football League. A brief background to the AFL will be presented before applying the individual theories.
• Nike’s Ad for Football Women’s World Cup 2019 Nike released its empowering advertisement ahead of the FIFA Women’s World Cup 2019 hosted in France. It claims that football is a game enjoyed by people of all races.
• How to Play Defense in Football In fact, a strong defense and a well-developed strategy can cause turnovers from the rival, and turnovers can significantly influence football game results.
• Soccer League and Grassroots Strategy Soccer is one of the most popular sports in the world, with over 240 million registered players at all levels, and at least 3.5 billion fans.
• FIFA, Zidane and Materazzi 2006 Debacle This paper examines FIFA, Zidane and Materazzi 2006 debacle. FIFA punishing both players was fair and helped them preserve their image.
• The Football Impact on the European Region The European region has been considered to be the world’s most prominent fan organization, with around three million football fans.
• Opposing American Football Ban Due to Health Reasons One of the opposing views regarding American football from the perspective of players’ health is the dubious nature of the claim that the described risks are universal.
• Rhetorical Strategies of FIFA Franchise The website central to this review provides its viewers with reasons for either pre-ordering or waiting on the newest instalment in the FIFA franchise, FIFA 22.
• Sport and Television: Football Support To retain its target audience and remain a popular activity, the sport needs the support of television as one of the main media tools.
• Racial Disparity in Professional Football: Rooney Rule An open conversation about equal rights and workplace diversity is reaching its peak in the form of viral social media campaigns and public demonstrations.
• Football Banned for Being Too Violent and Dangerous American football is a popular kind of sport in the United States, but scientific evidence demonstrates that this activity should be banned for being violent and dangerous.
• The National Football League Anti-trust Law The National Football League (NFL) during its long-lasting development is colored today, as the sphere where business interests seem to be more significant.
• American Football Is Too Dangerous and It Should Be Banned Regardless of American football being a major source of entertainment for many, it should be banned due to significant harm dealt with players’ brains, cognitive performance.
• The Review of Literature: American Football The articles included in the annotated bibliography research how violent and dangerous American football could be.
• American Football as a Popular Kind of Sport in the US American football is a popular kind of sport in the United States. A severe issue refers to the fact that professional players are often subject to health problems.
• Speed Drill: Agility Training in Young Elite Soccer Players The purpose of this paper is to describe and explain a speed drill for a specific athlete, using logical arguments and visual elements.
• Organizational Behavior Analysis: Japanese Soccer School Kurt Lewin’s theory of change is a framework most often used to describe and plan organizational change due to its relative simplicity, intuitive nature, and ease of use.
• Soccer: Effects of Sprint Training Training soccer players is an engaging and demanding activity, and it is crucial to make the most of this process to be a successful coach.
• Football and other Sports: Influence on Children’s Life Football is a very unique sport, as it helps a person establish a framework for life and attitude. It helps develop character and strengthen individuality.
• Training Football Athletes: Key Aspects Monotonous exercises should not bore them; trying activities appear to be more productive. Using many drills similar to deep ball drills in training practice is advantageous.
• 2010 FIFA Soccer World Cup Stadia Development in Cape Town: Resident Perceptions Bob & Swart’s Resident Perceptions of the 2010 FIFA Soccer World Cup Stadia Development in Cape Town assessed suggestions of the people on the venues of the FIFA.
• Soccer and Sport as a New Medium of Communication Execution of physical tasks calls for smooth, self-controlled, and concerted effort. Athletes need emotional control if they are to successfully engage in sporting events.
• Soccer and Sport: New Medium of Communication The concentration of wealth in certain clubs and leagues makes them more lucrative and more entertaining. This influences and entices more fanatics to join the clubs and leagues.
• Ranking Systems: FIFA and US College Football The purpose of this paper is to compare the FIFA ranking system for international soccer and the Matrix-based Methods system used in US College football.
• FIFA, Corruption, and Its Effects on Business The paper studies how unethical behavior affects FIFA and how business relates to FIFA will be affected by news and how it can deal with such a situation.
• Football Tactics and How They Evolve over Time
• Long-Term Effects of Concussion on Football Players
• Commercialization’s Impact on Football Club Performance
• Football Hooliganism and Fan Violence
• The Role of Video Assistant Referee in Football
• American Football: Technology and Regulation of Helmet Safety
• Race and Quarterback Survival in the National Football League
• National Football League and Player Compensation Issues
• Competitive Balance and Consumer Demand in the English Football League
• Quarterback Mobility and Its Impact on College Football
• Action Plan For Fundraising for the Penn Hills Football and Cheer Association
• American Football and Coin Toss
• Fitness Requirements for Football
• Broadcaster and Audience Demand for Premier League Football
• Assessing Methods for College Football Rankings
• Football Scholarships and Football Recruiters
• Being Special: The Rise of SuperClubs in European Football
• Ajax Football Club: Strategic Alternatives
• College Football Players Should Get Paid
• Beer Availability and College Football Attendance
• Exercise Program for Football Team
• American Football and Positive Latitude
• Concussions and American Football
• Football Helmets Are Insufficient to Stop Concussions
• American Football and Ice Hockey
• Strategic Behaviour and Risk-Taking in Football
• Professional Asian Football Leagues and the Global Market
• Concussions Are the Most Common Football Injury
• Justice, Professional Football, and Minority Coaches
• Market Size and Attendance in English Premier League Football
• Spanish Football: Competitive Balance and the Impact of the Uefa Champions League
• Cheshire Football Club and Management of a Soccer Team
• College Football and Its Social and Cultural Importance in the USA
• Motor and Cognitive Growth Following a Football Training Program
• High School Football Women Play
• The Growth and Challenges of Women’s Soccer
• Football Talent Identification and Training Programs
• The Impact of Football Events on Local Economies
• Analysis of Mental Strategies in Football
• How Digital Platforms Influence Soccer Fan Engagement
• America’s Football and the World’s Soccer
• Football Concussions and Head Injuries
• Football: The United Kingdom and English Public
• Joe Robbie Professional Football Stadium History
• American Football and High School
• Football Has Impacted Our Society in Many Ways
• Greatest Football Players Throughout History
• Domestic Violence and the National Football League
• British Culture, Economy and Society and the Role of Football
• High School and School Football Team
• Baseball, Football, and Basketball: Models for Business
• Football and Its Effect on Society
• International Women’s Football and Gender Inequality
• College Football Conferences and Competitive Balance
• Globalization and the Future of Indigenous Football Codes
• Football Hooliganism, Society, and Culture
• Acquiring and Performing the Football Passing Skill
• Football: History, Rules, and Influential Individuals
• Floating European Football Clubs in the Stock Market
• Gender-Specific Relative Age Effects in Politics and Football
• Health Risks Involved With Playing Football
• College Football Rivalry Between Ohio and Michigan
• Economics, Uncertainty, and European Football
• Deviations From Equity and Parity in the National Football League
• Professional Sports and Its Impact on the National Football
• Fantasy Football Provides Fans With Interactivity
• Concussions and Head Injuries in the National Football League
• Migrating Football Players, Transfer Fees, and Migration Controls
• Fantasy Sports and Its Effect on the National Football League
• Eliminating College Football Team
• What Are the Risk Factors for Injuries in Football?
• How Does the Players Behavior Off Field Affect the Game of Football?
• What Is the Role of Football in Everyday Life?
• How Did the Financial Crisis Influence European Football?
• What Is the Americanization of European Football?
• What Is Italian Football’s Status in an Age of Globalization?
• What AI Can Do for Football, and What Football Can Do for AI?
• What Are the Dynamics of Group Sports With Special Reference to Football?
• What Is the Data Collection on the Incidence of Injuries in Football?
• What Is the Network Theory Analysis of Football Strategies?
• What Is the Role of Corporate Social Responsibility in the Football Business?
• What Is the Impact of College Football Telecasts on College Football Attendance?
• Is There a Relationship Between Climatic Conditions and Injuries in Football?
• What Are the Determinants of Football Match Attendance?
• What Are the Biomechanical Properties of Concussions in High School Football?
• What Are the Fitness Determinants of Success in Men’s and Women’s Football?
• What Is Bayesian Hierarchical Model for the Prediction of Football Results?
• What Is the Effect of Altitude on Football Performance?
• What Are the Psychological and Sport-specific Characteristics of Football Players?
• What Is the Relationship Between Football Playing Ability and Performance Measures?
• What Is the Predictive Power of Ranking Systems in Association Football?
• What Are the Peculiar International Economics of Professional Football in Europe?
• What Are the Medical, Morphological and Functional Aspects of Football Referees?
• What Is the Epidemiology of Injuries in First Division Spanish Football?
• What Are the Common and Unique Network Dynamics in Football Games?

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• Chicago (N-B)
• Chicago (A-D)

StudyCorgi. (2022, March 1). 150 Football Essay Topics & Soccer Research Topics. https://studycorgi.com/ideas/football-essay-topics/

"150 Football Essay Topics & Soccer Research Topics." StudyCorgi , 1 Mar. 2022, studycorgi.com/ideas/football-essay-topics/.

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1. StudyCorgi . "150 Football Essay Topics & Soccer Research Topics." March 1, 2022. https://studycorgi.com/ideas/football-essay-topics/.

Bibliography

StudyCorgi . "150 Football Essay Topics & Soccer Research Topics." March 1, 2022. https://studycorgi.com/ideas/football-essay-topics/.

StudyCorgi . 2022. "150 Football Essay Topics & Soccer Research Topics." March 1, 2022. https://studycorgi.com/ideas/football-essay-topics/.

These essay examples and topics on Football were carefully selected by the StudyCorgi editorial team. They meet our highest standards in terms of grammar, punctuation, style, and fact accuracy. Please ensure you properly reference the materials if you’re using them to write your assignment.

This essay topic collection was updated on December 31, 2023 .

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Exploring football coaches’ views on coach education , role , and practice design : An Australian perspective

Erch selimi.

1 Institute for Health and Sport, Victoria University, Melbourne, Australia

Alexandra Lascu

2 Research Institute of Sport and Exercise, The University of Canberra, Canberra Australia

Fabio Serpiello

Carl t. woods.

3 Department of Sport and Exercise Science, James Cook University, Townsville, Australia

Associated Data

Data contains potentially sensitive information and cannot be shared publicly because of issues related to participant identification. For researchers who meet the criteria for access to confidential data, data is available from the Victoria University Human Research Ethics Committee (contact via ua.ude.uv@scihtehcraeser ).

Despite the importance placed on the design and delivery of formal coach education programs by Football Australia, there remains a lack of research relating to how formal coach education strategies support Australian football (i.e., soccer) coaches and their coaching practices. Through a series of semi-structured interviews, 20 highly qualified and experienced Australian senior football coaches shared their perspectives on: (i) coach education , (ii) their role as coach , and (iii) practice design . Findings revealed that formal coach education in Australia was largely ineffective in preparing senior coaches for the realities of senior football. Coaches attributed this to a number of factors, including the content’s quality, structure and delivery, which they viewed as rudimentary, outdated, repetitive and lacking in relevance and depth. Coaches also revealed there was an expectation of conformity to the content and practices endorsed by the National Football Curriculum, limiting the value and impact of formal coach education in supporting the development of coaches’ theoretical and practical dispositions. These findings point towards a number of broad and systemic issues relating to the conceptual, theoretical and practical foundations of the National Football Curriculum and subsequent courses. If Football Australia are to reach their goal in designing and delivering effective and meaningful coach education programs that support the highly complex and multifaceted role of senior coaching, formal coach education may need to adapt and evolve in a manner that better supports the multi-dimensional and context-specific needs of Australian senior football coaches.

Introduction

Sports coaching is a complex task [ 1 ]. Socio-cultural constraints operating at relatively long timescales (i.e., sporting identity, club culture, path dependent behaviour within an organisation) are likely to implicate how a coach views their role when situated within a broader ecology of relations [ 2 , 3 ]. While at shorter timescales, the pressure to win and perform (especially in high-performance sport), coupled with consideration of other stakeholders (i.e., players and support staff), likely implicates how coaches go about taking up with the day-to-day nuances of their role [ 2 , 3 ]. Football (i.e., soccer) coaching is no different. Coaches are required to operate in complex socio-cultural environments, while attempting to implement effective performance preparation frameworks at daily, weekly, monthly, and even yearly scales. Such complexity, in part, has contributed to the recent growth of interest–both practically and academically–in the professional education and development of sport coaches [ 4 , 5 ].

In 2020, Football Australia (FA)–the national governing body overseeing the development of football in Australia–released the ‘ XI Principles for the future of Australian Football ’. This document outlines eleven fundamental principles for the future growth and development of football in Australia [ 6 ]. Of particular interest to this study is ‘principle six’ , titled: ‘Create world class environments for coach development’ . In an effort to raise the standard of coaching and coach development, a number of promising measures have been proposed by FA, including: the need to foster a strong culture of coach development by emphasising the role’s importance in player development, modernise the method of coach education delivery, and review the content of coach education courses and the Australian coaching methodology [ 6 ]. At present, the Australian football coach education system is underpinned by the National Football Curriculum (NFC). Released in 2009, and updated in 2013, the NFC aims to provide coaches with an understanding of the national ‘playing’ and ‘coaching’ philosophy, advocating for a i) player-centred approach to coaching; ii) game-based, constraints-led approach to practice design; and iii) an information-processing view of motor learning [ 7 ]. Described by FA as an ‘holistic’ approach to coaching, FA hoped to establish a coaching culture where the implementation of theoretically-informed and evidence-based practice was a central component of coaching [ 7 ]. Despite the importance placed on formal education and accreditation by FA, there remains a relative paucity of research addressing how FA’s formal coach education strategies and the NFC support coaches and their coaching practices.

Currently, the football coach education system in Australia offers two distinct development pathways: the Community and Advanced pathways. The Community Coaching pathway is tailored toward coaches of participation players, aged between 5 to 17 years. Courses are relatively short, running for 1 to 2 days, with the content primarily focused on providing coaches with practice design and delivery guidelines [ 7 ]. According to studies that have observed coaching practices in such settings, although practice sessions are largely structured in accordance with NFC recommendations, coaching practices and behaviours are generally not reflective of the player-centred, constraints-led approach promoted by FA [ 8 , 9 ]. While findings from these studies have been important, such insights have mostly been based on community coaches with limited experience and accreditation. As such, the findings may not offer a representative view of the quality of coach education and content within the NFC.

The Advanced Coaching pathway is primarily targeted toward those working in the performance phase of football. Courses are more intensive than the Community pathway, often requiring 10 to 14 contact days, with content designed to cover FA’s Coaching Expertise Model that outlines a list of themed competencies ( training , the match , and management ) that a coach must acquire [ 10 ]. There are four levels of senior accreditation offered: the ‘C’, ‘B’, and ‘A’ licence, and a ‘Pro Diploma’, with the central tenet of this process aimed at ensuring the NFC’s coaching principles are easily understood and brought to life [ 10 ]. As such, the ‘C’ and ‘B’ licence are designed in a manner that encourages coaches to adopt FA’s vision and philosophy. Only at the ‘A’ licence level are coaches encouraged to develop and establish their own vision and philosophy of the game, which upon completing, are expected to be able to clearly articulate [ 10 ]. In addition, coaches aiming to work at the National Premier League level or higher are required to hold at least a ‘C’ licence, further signifying the important role FA’s formal coach education system has on Australian coach’s development and accreditation journey [ 7 ].

Globally, formal coach accreditation processes are thought to be important for quality assurance, ensuring a baseline of knowledge and competency across a variety of coaching cohorts [ 11 – 14 ]. As such, numerous countries have developed national coaching curricula [ 15 ], aiming to assist coaches “hone in their craft and become effective and ethical at achieving desirable ideals” [4 p.2]. This increase in the provision of formal coach education is due, in part, to the professionalisation of modern-day coaching, where coaches are now tasked with greater responsibilities, both on and off the pitch [ 16 ]. For example, professional coaches are often overseeing, not just the on-field performance of players, but are likely having a significant input to their off-field development, manifest through well-being and player welfare. As such, there is a growing consensus within high-performance sport that coaches are not just individuals who (co)design game plans and devise training strategies, but are managers of people –both players and support staff [ 17 – 19 ]. These emerging requirements of professional coaches point toward one of the many reasons we have seen an increase in the level of interest in the development of coach education programs from a variety of stakeholders [ 20 ], leading to a more scrutinised and regulated industry [ 21 ].

Given this, formal coach education, for all intents and purposes, is considered an integral and necessary component of a coaches developmental journey [ 22 , 23 ]. Despite significant empirical reports, the transfer of theoretical knowledge from formal coach education to the pitch has been difficult to demonstrate [ 4 ]. This could be related to the lack of alignment coaches feel with the theoretical material being covered [ 11 ]. Further, a continued and over-balanced focus on technical and strategical aspects of the game could limit the development of pedagogical and interpersonal competencies coaches feel are required to ‘do’ their job effectively [ 13 , 24 – 27 ]. The complex nature of coaching not only makes formal coach education challenging to implement [ 28 ], but “seriously calls into question the legitimacy and value of an overly-instrumental approach to coach learning and its provision” [11 p.3]. Critiquing along similar lines, Nelson [ 29 ] referred to formal education settings as a process more aligned to ‘indoctrination’ rather than ‘education’, while Abraham [ 30 ] suggested that formal coach education is often caught attempting to convince coaches of a singular and appropriate way of coaching, preventing exploration. This risks a view of formal coach development and accreditation regressing into a ‘box ticking’ exercise, rather than a valuable and integral part of their development journey. Formal coach education– in its current state –may thus not be able to foster the development of all the key skills the multi-faceted role requires [ 24 , 31 – 33 ]. To this end, the aim of the current study was to explore: (i) how Australian football coaches take up with formal coach education, (ii) how Australian football coaches conceptualise their role with regards to performance preparation; and (iii) how/why Australian football coaches use various practice strategies to support player development.

Study design

This study used an interpretivist, qualitative research design. This interpretivist position allowed for coaches to articulate unique meanings of their experiences and practices within their coaching domain [ 34 ], appreciating that the understanding of individual perspectives can only occur through observation and interpretation [ 35 ]. Ethical considerations for the research project in line with the National Statement on Ethical Conduct in Human Research was undertaken [ 36 ]. Additionally, a detailed ethics proposal was submitted and approved by the Victoria University Human Research Ethics Committee (Reference number: HRE22-031).

Participants

A purposive, criterion-based sample of Australian football coaches (n = 20) were recruited to participate in this study. In order to provide a comprehensive and well-founded account of their experiences during FA’s coaching courses and subsequent coaching content, coaches were required to have, at a minimum: i) an FA ‘A’ licence, and ii) accumulated 3 years of senior coaching experience (see [ 19 ]) within Australia. Altogether, 16 coaches held an ‘A’ licence, and 4 held a ‘Pro Diploma’. The sample level of senior coaching experience at the time of the interviews (defined temporally in years), ranged from 4 to 30 years.

Participant recruitment involved utilising existing networks within the Australian football community, social media posts, messages, emails, or through face-to-face conversation. After initial contact, participants received information regarding the project, example topics of conversation, and were able to ask questions to clarify the interview or data analysis process prior to an interview being organised. Written consent was obtained from participants prior to the interview starting. Consent was provided on the understanding that interviews would be anonymised. Thus, participant identities were coded numerically throughout all analysis (defined from HC1–HC20).

Data collection

Data was collected via semi-structured interviews that focused on three pre-defined themes related to the studies aims: coach education , their role as coach , and practice design . The questions were pre-planned yet open-ended, which allowed the conversation to flow naturally in a direction guided by the key themes [ 37 ]. The open-ended nature of the questions also provided this study with a broader understanding of the topics discussed while enabling participants to provide richer and deeper insight relative to close-ended interviews [ 38 ]. The questions used to guide the flow of the semi-structured interview are detailed in Table 1 .

The first author reflected on the interview process after each interview in order to evaluate the structure and appropriateness of questions. This resulted in only very minor modifications to basic wording, with no other changes made following reflection. All interviews were conducted by the first author online or in person between May and September, 2022. The duration of the interviews ranged from 73 to 145 minutes and were recorded for subsequent transcription and analysis.

Data analysis

Interviews were transcribed verbatim in Trint (Trint Ltd) by the first author. A pragmatic, two-staged thematic analysis was then used to analyse the data [ 39 ]. The first coding stage included an inductive approach, which entailed data immersion by re-reading transcripts and re-listening to interview recordings, as well as highlighting any interesting quotes or passages. Highlighted content was exported to Excel, where each excerpt was assigned a key code or description that encapsulated the ’essence’ of the material. The second author then analysed and examined the emerging codes and their relationships for consistency and relevance. This process of researcher-triangulation enabled the first author’s original codes and interpretations to be challenged and probed, ensuring that (i) codes could be appropriately organised into themes and (ii) the personal experiences and biases from the primary author did not lead to potential misinterpretations and distortions of the data [ 40 ]. Given that the primary author had previously participated in FA’s Advanced Coaching pathway and was a practicing coach, this reflexivity was essential for establishing and reinforcing the data’s trustworthiness and authenticity [ 41 ]. Next, a deductive analysis was conducted to compare the literature on (i) formal coach education ; (ii) coaches’ roles ; (iii) practice design , as well as the emergent themes discussed by the participants. All categories and emergent themes are presented in the results and discussion section, accompanied by selected quotes from the interviews. Thus, for brevity, both the results and discussion are presented concurrently.

Results and discussion

Given the magnitude of data collected, only excerpts that the authors felt best captured and reflected the sentiments expressed by the participants were included. The presentation of results and discussion section are guided by the three pre-determined themes: (i) perspectives on formal coach education, (ii) coaches’ role, and (iii) practice design. Each theme is composed of sub-themes that are either: (i) representative of the specific pre-determined topics discussed or, (ii) a collection of recurring themes that emerged from the openness of the interviews.

Theme 1: Perspectives on coach education

The first theme to be explored relates to coaches’ perspectives on formal coach education in Australian football. According to FA, there are three major areas of competency that senior coaches must develop: training , the match , and management [ 10 ]. As such, the interview questions were developed around these three sub-themes of coach education, while concurrently affording opportunities for participants to elaborate on their general coach education experiences as they felt necessary.

Sub-theme 1.1: Preparing coaches for senior football

National sporting organisations, such as FA, oft-attempt to support the development of coaches by providing well-designed and applicable coach education programmes [ 1 ]. Hence, there was a particular interest in the role formal coach education played in preparing coaches for the realities of senior football. A common sentiment shared among participants was the influence of the courses, particularly the ‘C’ and ‘B’ licences, in providing them with a framework to help plan and structure training sessions effectively. This is exemplified by an excerpt from HC18, who stated:

“I was pretty green and raw going into the whole coach education process . I felt like I really needed something that I could hang my hat on and use as a starting point to then progress forward from. I had some ideas based on my coaching, but I wasn’t sure how to translate those necessarily across onto a football field..…it just provided me with the structure that I needed, it gave me a framework and a tool kit that I could lean on.”

This sentiment is in keeping with the literature (see [ 8 ]), and should come as little surprise, given that FA’s earliest Advanced Coaching Courses are largely guided by ’The Football Coaching Process’ , which is a document designed to support coaches in planning, structuring, and delivering practice sessions [ 10 ]. Given there is suggestion that coaches practice their craft with little reference to a coaching process [ 42 ], FA seem to have good reason to focus on delivering a framework that helps coaches’ plan and structure training sessions. Though, despite participants expressing positive sentiments about the formalities of coach education on their basic practices, particularly in planning and structuring their training sessions, the changes in their coaching makeup seemed to be more methodological than theoretical . This was emphasised by HC14:

“When you’re starting out , it gives you all the tools that you need to make sure that the perception is that you know what you’re doing, you’re organised, and it seems like you’re doing a good job.”

In other words, the positive sentiments expressed by the participants seemed to point towards basic procedural developments in their practices. This was demonstrated in the fact that participants often remarked on the ineffectiveness their formal education had on preparing them for the role of senior coaching. This reinforces the notion that the senior coaches role extends beyond the development, design, and implementation of game plans and training sessions [ 43 ]. It also requires strong inter- and intra-personal competencies in order to cater for the diverse social contexts they find themselves in [ 18 ]. A sentiment also shared by HC13:

“ I don’t think the A licence prepared you [for senior coaching] to be honest. It was meant to be preparation for a professional coaching career, the qualification required to coach in the A-League as an assistant . But I don’t think it prepares you for that. If you’ve never been in that environment, there’s still a lot of learning to do when you get in there. So, I think it does leave you underprepared from a management perspective and what to expect around that environment. But it does give you preparation in terms of the daily process of training and giving you clarity in terms of a football process and identifying what you want to work on.”

These views are in keeping with reports that formal education has typically left coaches feeling unprepared for the rigours of senior coaching (see [ 44 , 45 ]). This is expected, though, given that coaching courses have traditionally been criticised for delivering abstract content far removed from current practice [ 11 ]. If the objective of formal coach education is to develop coaching knowledge, behaviours, and practices, then it seems important for FA to find a balance between the ‘development of coaches’ and the ‘accreditation of coaches’. As noted in the excerpts presented, these two things are not the same.

Guiding the development of coaches is FA’s Coaching Expertise Model, found within the NFC, which outlines a list of competencies ( training , the match , and management ) and football knowledge ( principles of play , strategy , and tactics ) that are considered essential to become an ‘expert coach’ [ 7 ]. Though, despite the importance placed by FA on the attainment of football knowledge within this model, participants felt the courses did not adequately address this area and were somewhat dissatisfied with its delivery:

“They [Coach Educators] always assumed that you had the football knowledge when you first come in. That was sort of the prerequisite . They thought you should just know. So, I think there could be a lot more work done in terms of developing football knowledge.” [HC11] “I think that [the lack of football knowledge] is probably the biggest weakness in terms of content across all of the courses.” [HC15]

When asked about why the development and attainment of football knowledge was an important feature of senior coaching, most participants were of the view that a deep knowledge about the game (see [ 46 ]) was essential for supporting the growth of a player’s knowledge of the game [ 46 ]. As HC12 explained:

“The reason [knowledge about football is important] is they’ll [players] call your bluff in two seconds. So, if I was to have no football knowledge , in the difficult times when you’re down at half time, when the players need something from you that gives them credible evidence, a tangible thing to take away that can improve their own and their team’s performance, and if you don’t provide it, you’ll get called out in two seconds. I think it’s [knowledge about football] absolutely key to the coaching toolkit. Football people are football people and if you’re not a football person, unless you’re Ted Lasso, it’s not happening for you.”

The importance placed on the acquisition of football knowledge is supported in the literature [ 18 ]. Moreover, the appreciation of football knowledge is conveyed by FA, who suggest “without in-depth football knowledge, the quality of what the coach does will be adversely affected” [10 p.13]. Despite this, ‘football knowledge’ is not considered as one of the three pillars of competency. Instead, FA encourage that ‘football knowledge’ be acquired through a variety of unmediated and informal ways such as: ‘ playing’ , ‘coaching’ , ‘analysing ’, and ‘talking’ about football [ 10 ]. However, although, coaches express a strong appreciation between football knowledge and coaching expertise (see [ 19 ]), research suggests that the attainment of football knowledge alone is inadequate to become an effective coach [ 17 , 47 ]. Rather, the development of football knowledge coupled with interpersonal and intrapersonal skills are regarded as an essential requirement for an effective coach [ 18 ]. Referred to as ‘ management skills ’ by many of the participants interviewed, this was another area participants believed the courses did not adequately address. For example, HC8 and HC14 stated respectively:

“The courses have helped with the coaching process, but the coaching process is only one aspect. How you deal with people , how you respond to setbacks and challenges is another thing and that’s a big part of coaching. And that’s not catered to enough in the courses.” “I almost feel like it’s back to front in the management area and learning how to relate and be in a group of people . Those types of [management] skills….I feel like there’s a whole piece missing there or it’s too late in its introduction.”

These findings are in keeping with the literature, which indicates that the support of inter-personal skill is disproportionately supported relative to sport-specific knowledge [ 48 ]. Although FA views ’management’ as a key pillar of coaching competency, and its delivery is heavily prioritised in the ‘Pro Diploma’, participants voiced feelings of dissatisfaction with the amount of attention and content devoted to management. Consequently, it may be beneficial for FA to reconsider the placement, delivery and the amount of time spent on developing management skills during the courses. Crucially, these findings point towards a potential disconnect between FA and the participants’ perceptions of the competencies required to be considered an effective senior coach and, perhaps more importantly, how coaching competency should be assessed . As HC7 discussed:

“Had a coach educator come to where I was working and spent a week with me, for example, in the planning process and in training sessions and team meetings on game day, you get a much better window into who the coach is . Are they an A licenced coach?, maybe or maybe not. But you can tell very quickly if that person is going to be a good coach or not. And that should be the basis of passing or failing or recommending further development. But at the moment, you’re in a group of 30 to 40 people, maybe you contribute once or twice in the classroom, you put on a session nervously, with a load of guys that don’t really want to be there. It either goes well, or if it doesn’t, you fail and then you’re suddenly not in A licence coach. Or, you have a personal relationship with the coach educator, or you’re an ex-socceroo and suddenly you’re an A licenced coach. Yeah, it’s pretty backwards.”

This sentiment highlights the challenge FA have in developing and assessing coach competency in its current format. Indeed, participants often felt like they were “ acting ” [HC19], eluding that the courses were merely a “ box ticking exercise ” [HC16] that had minimal influence on their coaching approach. Such findings are in agreement with the literature, in that coaches undertaking formal coach education are often seen engaging in ’studentship’ tactics to convey qualities desired to pass the course [ 44 ]. To address this issue, participants in our study remarked on how forms of mentorship within the coach education process “ could add another layer of value to the coach education process” [HC15], providing a more “learner-friendly environment that allows you to be a lot more expressive , leading to a more personalised assessment of competency ” [HC7]. Indeed, it has been suggested that coaching competency can be better understood and developed in a coaches respective coaching environment [ 49 ], implying that the assessment of coaching competency may also need to take place in such representative settings. Thus, in order for formal coach education to meet the needs of senior coaches, FA may need to re-conceptualise and re-structure the development and assessment of coaching competency, permitting learner-centred approaches (i.e., mentor- apprenticeship) to guide coach development.

Sub-theme 1.2: Coaches’ perceptions of the course content

According to the majority of participants, the quality of content presented on the courses was one of the key reasons why they felt formal coach education did not prepare them effectively for senior coaching. The content on the ‘C’, ‘B’, and ‘A’ licences was described as “ rudimentary ” [HC8, HC16], “ outdated ” [HC20], “ repetitive ” [HC3, HC4, HC5, HC13, HC18, HC19], and needing “ an absolute revamp ” [HC12]. This is further reiterated by HC7:

“I’m certainly not afraid to say that the biggest jump I made as a coach was doing the C licence, and from there I kind of thought, I’ll go into the B, A, and the Pro, and I’m going to make all these huge leaps . But the reality is the B was really an extension of the C, and the A an extension of the B…I was underwhelmed by the B and the A. I think the learning was very minimal, the content, structure and methodology of coach education was disappointing. But as we know, it’s a box that everybody has to tick. And it certainly felt like everybody was there just to see the time out and get their boxes ticked.”

The participants perspective that the course content lacked relevance was one of the most frequently cited reasons for their dissatisfaction. Participants revealed that they performed under vastly different contexts and conditions than those presented by the NFC, making the content challenging to connect and identify with. The following remarks capture this position:

“A coach looks at it [the NFC] and says, I’m under pressure, we’re in the bottom half of the table, we’re closer to relegation than we are to winning the competition, and people are telling me I should have this philosophy because that’s what the national curriculum says…? That’s nonsense, it erodes the confidence of people . These procedural documents that define what the game should be…it doesn’t match the reality. I think that disenfranchises people that are saying, well, in those circumstances it doesn’t apply to me, it’s irrelevant to me. I just need to survive.” [HC3]

These sentiments are consistent with the literature, in which the decontextualised manner of formal coach education means that the unique context that each coach operates in is usually ignored and disregarded, resulting in a lack of relevance and significance for coaches [ 31 , 50 ]. This points to one of the biggest challenges facing the make-up and delivery of content within formal coach education; if it is unable to meet the individual needs of coaches, it is likely that many will simply ignore the content delivered and continue to practice as they have in the past [ 51 ]. Thus, FA may need to reconceptualise the content within the NFC to better reflect the daily needs of senior coaching.

Beyond the participants dissatisfaction with the quality and relevance of the content delivered, there was an overwhelming sentiment that perhaps the most frustrating feature of the coach education process was the lack of freedom to explore. The expectation to conform was denoted amongst most participants, even into the later stages of the ‘A’ licence. It is, thus, worth quoting three participants at length here, given the richness of their responses related to feelings of constraint:

“If you take that freedom away from people when they’re going through the coach education process , the freedom to think differently, you’re kind of just indoctrinating in a certain way of thinking, and I’m not sure that’s what we should be trying to do.” [HC3] “I felt like it was very repetitious. It felt like everybody was trying to do the same thing on the courses . It was very homogeneous. It was almost expected that you had to toe the line and coach a certain way in order to pass the course. And again, I just don’t know if that’s conducive to robust learning and becoming a better coaching community if we’re going to do it that way . I just felt we could have had more different types of sessions or contrasted more with the national curriculum to sort of make you appreciate it or understand its weaknesses more in coaching that way.” [HC16] “I think that we have tried to take that [exploration] away from a lot of coaches and make them all cookie cutter coaches . And then you get robots and nasty, sterile coaches that, you know, if everybody’s learning to coach the same way, how are they going to adapt when they come up against something different? I think that’s one thing that was missing from the courses, right the way through.” [HC4]

These responses are unsurprising given that the ‘C’ and ‘B’ licences are explicitly designed to encourage coaches to adopt FA’s vision and philosophy. There is an expectation from FA that by the time coaches progress to the ‘A’ Licence or ‘Pro Diploma’, they should be able to develop and articulate their own philosophy [ 10 ]. Despite this stance, participants believed that the ’A’ and ’Pro’ licences were still heavily based on the NFC, limiting their ability to explore, develop, and expand their vision and philosophy of the game. These sentiments are prevalent in the literature, where coach education is frequently accused of indoctrination , merely employing a one-size-fits-all approach [ 50 ]. Accordingly, if FA are to realise their goal of developing ‘world-class’ environments for coach development [ 6 ], then formal coach education may have to move beyond a standardised football curricula based on transmission and application–giving coaches a ‘toolbox’ of professional knowledge–and aim toward a deeper, more meaningful change that encourages search and exploration.

Sub-theme 1.3: Coaches’ perceptions on the delivery of content

Recent literature has emphasised the important role coach developers have in the delivery of formal coach education content [ 52 – 54 ]. However, for the participants in this study, coach developers were seen as “ good guys and professional coaches , but not always great educators… you can tell the [coach developer] never taught anybody anything ” [HC12]. Coach developers were considered generally ineffective at communicating, presenting, and delivering content, as further discussed by HC7:

“The message between the curriculum and the application in the coach education space was really lacking . I saw coach educators who were so authoritative and rigid and structured and upon reflection, I thought, now this wasn’t meant to be applied like this. And somewhere the message has been lost.”

Although the above reflections are noteworthy, some assert that much of the criticism levelled at coach developers can be attributed to broader, systemic issues that reside beyond their control (i.e., situating ‘education’ in a model of transmission, not primary experience and careful exposure) [ 55 ]. While we are cautious about drawing too negative a conclusion about the (in)effectiveness of coach developers here, our findings do suggest that future work needs to examine ways in which coach developers working within FA’s coach education pathways can be better supported in developing, structuring, and presenting course content.

Theme 2: Conceptualisation of the coaching role

The next theme explored the conceptualisation of the coach’s role, which will concurrently encapsulate coaching approach, expertise, and knowledge needed for senior coaching. This component of the interview allowed participants to share their beliefs toward coaching and its function within a senior football environment.

Sub-theme 2.1: Coaching is multifaceted

A football coach’s roles and responsibilities are vast in both scale and scope [ 56 ]. Because of the multifaceted nature of coaching, coaches are frequently required to develop knowledge and expertise in a variety of fields, which can often be found outside their sport [ 33 ]. This was no different for the participants in this study, as noted by HC15:

“It’s a mixture of stuff. It’s a leader. It’s a motivator. It’s a CEO. It’s a mentor . It’s a father. It’s a brother. It’s not one thing. It’s a moving target. And you need to be robust in your makeup as a person, psychologically and emotionally and in every way. You need to be sensitive to the environment around you. You can’t be oblivious to it. It’s a whole lot of stuff. And then by the way, you need a little bit of football knowledge because, that at the end is the bit we’re doing.”

This response highlights the multi-dimensional nature of ‘coaching’ at the high-performance level. For the vast majority of participants, articulating the role of the senior coach was difficult, resulting in lengthy responses that further illustrated the role’s complexity. This could also be said of FA, whose description of the senior coach’s role–“to prepare successful teams” [10 p.58]–may considerably understate the role’s scope. Perhaps it is apt to question whether the title ‘coach’ is adequate in describing the wide range of duties and responsibilities that an individual may undertake and be accountable for, particularly in performance phase settings? Nash [ 43 ] supported this notion, arguing that due to the role’s uniqueness and idiosyncratic features, no definitive description can be established. Regardless, gaining deeper insight into the complexity of coaching, as well as the varying needs associated with different contexts is critical if FA are to design coach education programs reflective of the scenarios and contexts senior coaches find themselves in.

Sub-theme 2.2: Coaching approach

As stated earlier, FA advocate for a ‘player-centred approach’ to coaching [ 7 ]. Defined by “a style of coaching that promotes athlete learning through athlete ownership, responsibility, initiative and awareness, guided by the coach” [57 p.1], player-centric coaching practices actively encourage players to be involved in the decision-making and problem-solving process. While participants generally favoured player-centrism, the nature of high-performance football and subsequent pressure appeared to make it challenging for them to consistently take up with such an approach. Some participants were “ happy to have a little bit of dialogue with players , but when push comes to shove , and I say it’s going to be that way , it’s got to be that way” [HC11]. An excerpt from HC8 discusses this in depth:

“I try to be very inclusive and be a facilitator. I think on reflection, if I coach in a senior environment again, [I’ll need to be] more strict, more dominating, for lack of a better word . And when I say more, I only mean a little bit, I don’t mean I should go to the complete opposite end of the scale, but I feel like I was too nice or too flexible, allowing them to take the lead. Although there’s massive benefits to having that (player-centred) approach and engaging your playing group, you still have to be the ultimate authority. You have to have someone who can make a final call, who has the respect from people under them to make that call, and then they will follow that person’s decision.”

Although participants saw the advantages of supporting greater player ownership and accountability through a player-centred approach, the apparent socio-cultural constraints of high-performance football seemed to make this difficult to implement on a consistent basis. These sentiments are consistent with the literature, which suggest that coaches who work in high-pressure contexts are more likely to regress to controlling, directive, and prescriptive coaching [ 57 – 59 ]. If FA are to progress with a player-centric approach, then it is vital that they more clearly show how this can be achieved within the socio-cultural constraints of high-performance football.

Sub-theme 2.3: Management and interpersonal skills

Senior football coaches are required to interact frequently with a broad range of stakeholders. Accordingly, it has been suggested that a coaches’ effectiveness is largely dependent on their capacity to nurture meaningful and productive relationships [ 18 ]. This sentiment was also shared by participants here. Namely, despite the role requiring a diverse set of competencies, the ability to help develop people and build sustainable relationships appeared key to the senior role:

“Coaching is all about relationships. There are other facets to it, like the way that you communicate, deliver a message and the process you go through but I think without strong relationships you are doomed to fail because no matter how knowledgeable you are at your craft , if you can’t connect with someone, the chances of them hearing your message, let alone taking it on board and running with it, are very limited" [HC18] “ The role is to develop people. You have to be a better person after you’ve come through that environment. They have got to be a better footballer, a better personality, a better leader . And then under all of that is winning of course, you’ve got to win. Because, if you’re a senior football coach, you’re there to win games or you’re there to win relative to whatever your objectives are. So, that’s a non-negotiable part of being a senior coach.” [HC11]

This appears to align with the literature, which suggests that coaches who invest time in building strong relationships with players are likely to promote a connected and interactive environment that supports player development [ 1 , 13 , 60 ]. Moreover, considering all participants had coached teams that were focused heavily on performance outcomes (i.e., winning), they each seemed appreciative that team cohesion and performance outcome were not mutually exclusive. This is of note, although FA consider ‘management’ to be one of the key pillars a coach needs to be competent in, such skills are only briefly touched on in ‘ The Football Coaching Process ’ [ 10 ], and may not be sufficient in supporting coaches at the required level. Our results suggest that further emphasis and investment in supporting the development of management skills (i.e., interpersonal, and intrapersonal) could be of use within the coach accreditation process in Australian football.

Sub-theme 2.4: Delivering a vision, playing style, and getting results

Senior coaches in high-performance sport are largely evaluated on the results obtained. In other words, coaches are expected to “ win football matches , first and foremost ” [HC4]. Therefore, it should not be surprising that the need to produce results is a significant source of pressure and focal point for senior coaches [ 59 ]. Our findings showed that given this pressure, the importance of the curriculum diminishes overtime: “ senior coaches don’t care about the curriculum , they care about results ” [HC8]. This sentiment was also shared by HC2:

“You need to get the results first before looking to develop players . Unless you’ve come from a previous background where you’ve had some good results or you’ve been a high-profile player, I think you get a little bit more time then. But if you’re a young coach and no one knows you, you have to pretty much get results straight away.”

Despite the importance of getting results, there is a growing expectation within the football community that coaches also need to deliver a ‘club vision’ and ‘playing style’. This belief is echoed by FA, who have summarised Australia’s preferred playing style in the following statement: “A pro-active brand of football , based on effective possession , with the cutting edge provided by creative individuals . Defensively the key components are quick transition and intelligent collective pressing” [7 p.17]. Participants expressed an expectation and pressure “ to be competent enough to articulate your vision and your playing style ” [HC11] such that supporters, the club, and other stakeholders could identify with it. Thus, it appears important for senior coaches to not only get ‘results’, but to do so in a way that reflects a club vision. This further demonstrates the complexity of coaching at the high-performance level. Our findings suggest that the NFC and subsequent content delivered on the coaching courses needs to better represent the requirements, expectations and perhaps even echo the pressures associated with the senior coaching role.

Theme 3: Practice design

A fundamental priority for coaches in performance environments is the successful design and integration of performance preparation frameworks capable of supporting athletes in regulating behaviour in training and competition [ 61 ]. Accordingly, this final component of the interview presented an opportunity for participants to explore the practice strategies used, and why, in helping support the development of football skills.

Sub-theme 3.1: Approaches to practice design

When it came to identifying what type of practice strategies participants preferred, all favoured the need for ‘realistic’ or ‘representative’ environments. Here, we refer to such practice through the lens of ‘representative learning design’ [ 62 ]; defined as training activities that are representative of the informational constraints of competition [ 61 , 63 ]. It is thought that players who are exposed to representative learning designs will learn to ‘pick up’ key sources of information used to directly regulate their behaviour in competition environment [ 61 ]. This was a sentiment articulated by HC10 and HC7, respectively:

“I think representative design is crucial to be able to get the learnings across efficiently and effectively . If training is not representative of the actual scenario faced on the weekend or the problems faced on the weekend, I think you’re going to miss the mark, to be honest.” “Representative design is massive . Training has to look like the game. That doesn’t mean we play 11 v 11 in every session, but it means that generally the game is directional, there’s always opposition and more often than not, the attention is focused centrally towards a goal scoring point. 95% of our sessions will involve those principles. On a simplistic and fundamental level, training is designed so players are playing football competitively, that reflects the game.”

These responses are consistent with FA’s position on practice design, who state that for ‘proper’ learning to occur, training exercises require ‘game-specific resistances’ (i.e., opponents) that replicate the actual football situation in which the problem occurred [ 10 ]. Despite this stance, FA do state that in certain circumstances when coaches have exhausted all other options for developing a player, isolated and unopposed training may be used [ 10 ]. Such a sentiment seemed to be shared by participants, who despite advocating for representative learning design, accepted that a place for unopposed practice remained:

“Unopposed game patterns, which is something I use in the preseason working on what I call the ‘what if’ scenarios . I spend a lot of time in pre-season working on that, building a cohesion and I guess synergy . In the first instance, unopposed, maybe mannequins, but starting from different parts of the field and working through scenarios and options, just presenting them with alternatives. If this happens, there’s an alternative. And by repeating and repeating and repeating and repeating, firstly, without competition just patterns, they start building their own decision making based on the ‘what if’s’. Then, as you introduce a passive opponent and that passive opponent hypothetically leans right, then we go to option three, they go left, we play through the line beyond the press, and we do this.” [HC15]

This perhaps highlights a theoretical inconsistency. For example, research suggests that practice designs containing specifying information leads to effective and efficient skill transfer from training to competition, whereas practice designs containing non-specifying information may lead to a more general transfer [ 64 ]. The majority of participants shared the belief that isolated and unopposed training had merit and would likely transfer into competitive games, a belief likely found on the assumption that breaking up tasks into isolated components is beneficial to enhance performance [ 65 , 66 ]. Although despite this belief, it was of note that most participants were well aware of the limitations of unopposed practice with regards to the development of football skill. Moreover, some participants mentioned that unopposed practice was implemented to cater to areas such as introducing new tactical concepts, manage player physical load, and increase confidence of players prior to a competitive match. This was exemplified by HC7:

“I’m certainly not anti-unopposed practice, there’s just a place for them. If we play on a Sunday and we have one session between then and a Wednesday game, may be the best way to get a tactical idea out without compromising the loading [of players] is to do an 11 v 0 and an unopposed type of session. So, I will use them if that’s the best tool to get something out in a short period of time. But I think you neglect long term learning by doing anything unopposed . For me, a pre-set pattern is fragile. If I say, right, this is how we will build up to create a chance and this is the pattern that we work on repetitively unopposed at training. What happens when that doesn’t become available in the game? But if we train over and over again with the right level of opposition and problems to solve, we will create long term learning and problem solvers and collective problem solving cannot happen without putting them in problems to solve over and over and over again.”

Such sentiment indicates that additional factors, like training and playing schedule, are likely to influence practice design approaches for senior football coaches. Although participants favoured representative design, the nature and complexity of the high-performance environment meant ideal training methodologies were compromised. Indeed, there are other ways of reducing the complexity of practice while preserving its representativeness (see [ 67 ]), and given that most participants recognised the limitations of unopposed practice for sustained learning, FA could consider integrating such ideas into the NFC, like manipulating constraints in practice to preserve functionality in representative ways. Practice, in other words, could be reduced in complexity through simplification , rather than decomposition [ 67 ], thereby offering greater theoretical coherence in senior coaches undertaking their accreditation processes.

Sub-theme 3.2: Theoretical sentiments associated with practice design

In this part of the interview, participants were asked if they were guided by a particular theoretical framework of practice design and player development. According to FA’s coaching philosophy, which is underpinned by an information-processing view of motor learning, ‘perception’, ‘decision’, and ‘execution’ are considered as three distinguishable, yet interconnected processes a player undertakes before completing a football action [ 7 ]. This appears to have influenced some participants, as noted in responses by HC8 and HC12, respectively:

“ There is a literal chronological process of how decision making takes place in the brain, which is first you receive communication, so you perceive words and body language, it goes into your brain . Then your game insight, in other words, your knowledge, your experience as a player determines what solutions pop up in your brain and that you see as options. And then you obviously pick one and then you execute.” The ‘perception’, ‘decision’, ‘execution’ is the single biggest failure of us coaches over my period [in Australian football]….we have to allow the players to make decisions, I don’t care what decision you make, as long as you make one . Execution is purely about repetition, executing something is the output of the first two [perception and decision making].”

These responses suggest that at a superficial level, the information-processing view of motor learning presented by FA has influenced how some participants conceptualise player behaviour. By FA’s own account, the complexity of football requires players to rapidly select a particular response from a wide range of possible options and execute them under pressure [ 10 ]. Although this perspective on motor learning and skill acquisition still holds a strong position in player development models, ecological dynamics has emerged as a theoretical alternative in the explanation of learning and behaviour (for a detailed overview of its key tenets, see [ 68 ]). Despite the opposing theoretical stance of FA, it was of note that a handful of participants mentioned that an ecological dynamics rationale influenced their view of player development, practice design and their role in performance preparation. For example, when asked if they followed a particular theoretical framework, HC7 responded:

“An ecological dynamics approach. You went through the [education] process without really being exposed to the theory around ecological dynamics and the constraints-led approach . [The NFC] didn’t feel right, and that coaching in the manner we were asked to do, with a lot of unopposed stuff, a lot of over-structured coaching felt really unnatural to me.”

Despite miss-guided and uninformed criticisms, ecological dynamics offers a blended theoretical framework that brings together key ideas from ecological psychology and dynamic systems theory (see [ 68 , 69 ]). It is far from a ‘one-size fits all’ approach, offering sports practitioners with a theoretical positioning that explains behavioural emergence without relying on abstract mentalistic and mechanistic concepts. This helps guide the design of informationally rich and representative practice tasks (see [ 70 ]). Interestingly, these sentiments were noted by HC3:

“There’s never going to be a secret of how you score, because it’s an emerging concept that depends not just on what you do, but on the opposition. So, for me, all these ideas of trying to come up with some mechanistic approach… misses the point . I see the game as a complex, dynamic system with the scoring of the goal an emergent concept that really depends on the interactions of many parts. I don’t control an individual and I don’t control the individual process, I don’t control it in microscopic detail. But what I need to do is ensure that there are certain forms of interactions which happen within that system that generate certain emergent behaviours. If a player or playing group can come up with an idea that maybe I was missing right then, if they come up with it themselves, it will stick. If I say it, it may or may not stick, because the process of conceiving something I think ingrains it in the mind much more so than passively receiving that information.”

These findings, in conjunction with earlier sentiments regarding the rigidity of course content, demonstrate divergent theoretical perspectives on motor learning and control within the participants. Regardless of theoretical positioning, it is clear that FA need to consider supporting coaches in the exploration of theoretical concepts that resonate with them. This could take shape in the delivery of alternative theoretical frameworks and their implications for a coach’s role and practice design. Such diversity in the content of the NFC may thus foster ongoing exploration, not replication–a theme noted earlier as being diminished through the current delivery of rigid content.

The aim of this study was to explore Australian football coaches’ perspectives of formal coach education delivered by FA. Doing so allowed us to shed light on how coaches conceptualise their role, and what practice strategies they employ to support player development. With regards to formal coach education, the findings indicated that while courses supported a coaches’ basic methodological and procedural practice (i.e., structuring and planning training), the Advanced Coaching pathway was largely ineffective in preparing coaches for the rigours of senior football. This was primarily due to the nature, structure, and delivery of the content, which led to sentiments of indoctrination and conformity. When discussing their role in high-performance settings, participants emphasised its complexity, requiring competence across multiple domains. This appeared to be under-appreciated in the content delivered as part of the accreditation process. Finally, when discussing what practice strategies participants used, most expressed a strong preference for designing practices that are ‘representative’ of the competitive environment. Though, some did mention that utility of unopposed practice in high-performance settings, albeit for reasons other than skill development.

Our overarching aim was to gain a deeper understanding of the coach education landscape in Australian football, helping foster the voice of Australian senior football coaches in discussing the much-debated topic of coach development and education. The findings demonstrate that FA faces challenges far beyond simple cosmetic upgrades to the structuring and delivering of content on their courses. They rather point to broader, systemic issues relating to the conceptual, theoretical, and practical foundations of the NFC and subsequent courses. If the intention of FA is to develop ‘world class’ coach development environments capable of effectively developing the behaviours, knowledge, and practices of Australian football coaches, then greater emphasis on delivering coach education in a manner that meets the needs of the coaching community is required. We hope that these findings encourage FA and researchers to continue engaging with the Australian coaching community and collectively seek ways to develop future iterations of the NFC and coach education programs, thus better supporting and enhancing the theoretical, philosophical, and practical orientations of Australian football coaches.

Acknowledgments

The authors would like to thank all the participants for their involvement in this study.

Funding Statement

The author(s) received no specific funding for this work.

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REVIEW ARTICLE

How to be successful in football: a systematic review, article information.

Identifiers and Pagination:

Article history:, article metrics, crossref citations:, total statistics:, unique statistics:.

Background:

Despite the popularity of football, the analysis of success factors in football remains a challenge. While reviews on performance indicators in football are available, none focuses solely on the identification of success factors and addresses the large and growing body of recent research up until 2016.

To find out what determines success in football and to organize the body of literature, a systematic literature review analyzing existing studies with regard to success factors in football was undertaken.

The studies included in this review had to deal with performance indicators related to success in football. The studies were published in 2016 or before. The initial search revealed 19,161 articles. Finally, sixty-eight articles were included in this review. The studies were clustered with regard to comparative analyses, predictive analyses and analyses of home advantage.

In total, 76 different variables were investigated in the reviewed papers. It appeared that the most significant variables are efficiency (number of goals divided by the number of shots), shots on goal, ball possession, pass accuracy/successful passes as well as the quality of opponent and match location. Moreover, new statistical methods were used to reveal interactions among these variables such as discriminant analysis, factor analysis and regression analysis. The studies showed methodological deficits such as clear operational definitions of investigated variables and small sample sizes.

Conclusion:

The review allows a comprehensive identification of critical success factors in football and sheds light on utilized methodological approaches. Future research should consider precise operational definitions of the investigated variables, adequate sample sizes and the involvement of situational variables as well as their interaction.

1. INTRODUCTION

Football or soccer (in this paper the term ‘football’ is used) is the most popular sports in the world. According to the “Big Count” study of FIFA [ 1 ] there are 270 million people involved in the match (players and referees). Moreover, football attracts millions of spectators around the world. For example, the global TV audience that followed the 2015 UEFA Champion’s League final between FC Barcelona and Juventus Turin was estimated to be 180 million people from more than 200 territories [ 2 ]. Due to its high popularity, football stands out among sports and games. In contrast

to games such as basketball or handball, football is a low scoring game, and scoring a goal is usually a rare event. For this reason, the final match score does not provide a clear picture of the teams’ technical and physical performances. To understand success factors in football, various other performance indicators next to goals scored have to be considered. Football is also a sport which has elements of chance but nevertheless, this does not mean successful teams are just luckier than others [ 3 , 4 ].

To identify the factors which lead to success in football it is necessary to find performance indicators which significantly discriminate winners and losers. However, the identification of critical factors for successful performance poses a major challenge [ 5 ]. In 1912, Fullerton did the first work in this area of performance analysis for baseball [ 6 ]. In football, Reilly and Thomas [ 7 ] performed one of the first systematic notational analyses. They used hand notation and audio tapes to analyze in detail the movements of English First Division football players [ 8 ], and found out, inter alia, that a player is usually in touch with the ball for only two percent of the time. In another early performance analysis, Reep and Benjamin [ 9 ] developed a new approach to study 3,213 matches in England between 1953 and 1968 using frequency distributions. Their analysis revealed that about 80 percent of all goals are scored after three or fewer passes and about 10 shots are needed for one goal.

A milestone for science and football was the first World Congress of Science and Football which was held in Liverpool in 1987 [ 5 ]. Various themes were discussed such as team management, computer-aided performance analysis and decision-making by referees [ 10 ]. In the following years, the numbers of research papers concerning football and performance analysis increased steadily [ 11 - 15 ]. Hughes and Bartlett [ 16 ] reviewed and analyzed research on performance indicators in sports and defined a performance indicator as “… a selection, or combination of action variables that aims to define some or all aspects of a performance. Clearly, to be useful, performance indicators should relate to successful performance or outcome” (p. 739). Researchers also monitored match structures, summarized some performance indicators and utilized them ( e.g. , numbers of shots, passes, dribbles or ball possession) in various subsequent papers which provided more insight into possible success factors in football [ 6 , 17 ].

In the context of this paper, two review studies regarding performance analysis in football are noteworthy. Mackenzie and Cushion [ 18 ] critically reviewed 60 articles (articles published up to 2010) with a focus on methodological approaches and concluded that there is an overemphasis of research on predictive and performance controlling variables ( e.g. , location, shots). They suggested an alternative approach that focuses on research that investigates athlete and coach learning to enhance our understanding of football performance. However, these factors cannot readily be operationalized as success factors. Sarmento, Marcelino, Anguera, Campanico, Matos and Leitao [ 19 ] systematically reviewed 53 articles (articles published up to 2011) with a focus on major research topics and methodologies. They concluded that most studies used a comparative analysis to analyze differences between players or teams. Unlike Mackenzie and Cushion, they identified a lack of predictive studies. While it was not the main focus of their research, they also identified some success factors for a team such as the number of shots and shots on goal. They concluded that match location, quality of the opposition, match status and match half seem to have a greater importance for success due to a large number of studies that focused on these aspects.

1  The body of research on this topic has grown significantly in the last years. For example, in the three years between this review and the review of Sarmento et al. [19] the number of predictive studies, which are the most promising studies to deliver new insights to the of success in football, has grown by more than 40 percent (see also tables 6 to 8).

2 Actual results of the selected articles are found in the discussion section

2. MATERIALS AND METHODS

The systematic review of performance indicators in elite men’s football was done in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement [ 23 ]. The last search was conducted on June 24 th , 2017.

To search for relevant publications and ensure the quality of the articles, the following databases were utilized: Web of Science (the modules “Core” and “Medline”), Scopus and PubMed. Articles that were published in 2016 or before and in English were considered. The search strategy comprised search terms that combined one of two primary keywords (soccer OR football) with a second keyword ( e.g. , success, win, loss) using the Boolean operator and all utilized search terms are presented in Table 1 .

For inclusion, the articles had to meet the following criteria:

• The data had to deal with performance analysis in football.
• The variables of interest were linked to success (win/loss, goals, continuance in league/tournament, league ranking and points won).
• Adult elite football was investigated.
• The study was written in English.
• The study was published in an academic journal.
• The study design was comparative or predictive or focused on home advantage in football.

It should be noted that we included studies on home advantage in this review as a separate category besides comparative and predictive studies utilizing inferential statistics. Although most of the studies on home advantage used a descriptive approach to reveal the influence of home advantage, we considered these non-inferential studies because home advantage is one of the most investigated variables regarding success factors [ 18 ].

The initial search revealed 19,161 articles (Web of Science [Core and Medline]: 9,706; Scopus: 6,038; PubMed: 3,417). After excluding the duplicates 10,833 articles remained. The articles were screened based on an assessment of both the title and the abstract. All articles without a focus on the investigation and analysis of data on the conditions of competition results in elite adult football were excluded. In total, 185 articles were relevant for this review. These articles were read in detail and assessed for relevance and quality. Articles which did not meet the criteria were excluded. After this step, 53 articles remained. Subsequently, the literature references of these 53 articles were screened for more articles meeting the criteria. Fifteen additional articles were identified. Finally, 68 articles were included in the review (Fig. 1 ).

Then, the articles that met the inclusion criteria were indexed, and each article was summarized. The summaries comprised the study purpose and design, methods of data collection and analysis, and key findings. This enables an overview and comparison of the articles and allows an assessment of the current state of research on performance indicators in football.

The identified articles were published between 1986 and 2016, covering a time span of 31 years. More than half of the articles (exact 61.8%; 42 articles) were published within the last seven years (2010-2016) of the searched time period, indicating that this field of research has recently gained momentum.

To organize the identified analyses, the articles were categorized following a system used by Sarmento et al . [ 19 ] and Marcelino, Mesquita, and Sampaio [ 24 ]. In the first step, the articles were assigned to [ 25 , 26 ] comparative, [ 27 ] predictive or Home Advantage (HA) analyses [ 28 ]. In the second step, articles were assigned to one of the three types of analyses from above according to the different operationalization of success ( i.e ., win/loss, goals, continuance in league/tournament, league ranking and points won) (Table 2 ).

Of the articles, 30 were predictive analyses, 22 were comparative analyses, and 20 focused on the analysis of home advantage. One of the articles [ 15 ] covers both types of analyses (predictive and comparative). In total, 21 articles over all three types of analysis utilized “win/loss” as the success variable. “Goal difference” was used by seven articles, “goals” by eight, “league/tournament ranking” by 12, “points” by four and “continuance in league/tournament” by two.

4. DISCUSSION

In the following section, methods and major results of the identified articles will be presented within the three different categories of type of analysis. Finally, all findings will be summarized and the most frequent and significant variables regarding success factors in football will be discussed.

5. COMPARATIVE ANALYSES

In seven of the 21 comparative analyses, researchers compared wins and losses. In three of the seven papers draws were also included, and in one instance the percentage of wins was considered alongside wins and losses (Table 3 ). In the three papers that compared only wins and losses [ 29 - 31 ] the authors tried to find variables that explain differences between winners and losers. Broich et al . [ 29 ] identified goal efficiency (number of goals divided by the number of shots), shots, passes and ball contacts as the most important team parameter for winning. Efficiency was also analyzed by Szwarc [ 31 ]. He showed that players of winning teams are more efficient than their opponents. As a result of the small sample (seven matches) only shots on goal (p<0.05) and shots defended by a goalkeeper (p<0.01) differed significantly between winners and losers. Kapidizic et al . [ 30 ] did not analyze efficiency but they also found that the numbers of shots within 16 meters (p<0.05) and accurate passes (p<0.01) are significant indicators for winning teams at the European Championship in 2008. Winners also scored more goals than losing teams in the Championship. Three more papers investigated the differences between wins, losses and draws [ 27 , 32 , 33 ]. These studies reported various significant differences between winning, drawing and losing teams. Winners have more entries into the penalty area (p<0.01) [ 33 ], more successful attacks (p=0.003) and passes (p=0.015) as well as a higher ball possession rate (p=0.001) [ 32 ]. Armatas et al . [ 27 ] revealed that 71.4 percent of teams that scored the first goal subsequently won the match (p<0.05). In contrast to the other studies, one study focused on the total winning percentage [ 34 ]. Another difference is the use of group cohesion as the independent variable. The authors showed a statistically significant relationship between individual attraction to the group-task and performance with a very high effect size of 1.94 (p<0.05). The higher the positive feelings of each group member to the group-task, that is, to play football successfully, the higher were the likelihood of winning.

3  Oberstone [ 15 ] used comparative and predictive methods; Mechtel et al . [ 25 ] used win/loss and goal difference; Collet [ 21 ] used win/loss and points; Carmichael and Thomas [ 26 ] used predictive methods and home advantage; Armatas, Yiannakos, Papadopoulou and Skoufas [ 27 ] used comparative methods and home advantage; Lago-Penas, Gomez-Ruano, Megias-Navarro and Pollard [ 28 ] used predictive methods and home advantage.

In nine of the articles, the authors compared teams with different positions in the league/tournament ranking (Table 4 ). Luhtanen, Belinskij, Häyrinen and Vänttinen [ 35 ] investigated the influence of offensive and defensive variables on the final ranking of the European Championships in 1996 and 2000. In 1996, interceptions and the success rate of all defensive actions showed a significant correlation (p<0.05) with the final ranking. In 2000, significant correlations with the ranking were found for success rate in passes (p<0.05) and attempts (p<0.05) on goal. In the other papers, different football leagues were investigated and it was shown that better-ranked teams (top-teams) need less shots for a goal than worse ranked teams [ 15 , 36 , 37 ]. This parameter corresponds to Broich et al .’s [ 29 ] ‘goal efficiency’. It was also found that top teams have more successful attacks, complete their offensive attacks more frequently between zero and 11 meters in front of the goal [ 38 ], have more successful passes [ 15 , 38 , 39 ], score more goals [ 36 , 37 , 40 ], perform more crosses [ 15 , 40 ], have more ball possession [ 37 , 39 ], shoot more often on the goal [ 37 , 39 ], have more assists [ 36 , 37 , 39 ] and take more shots [ 15 , 37 , 39 , 40 ]. The best teams in the league also perform fewer fouls [ 15 ] and allow fewer shots and crosses [ 40 ]. The worst ranked teams have fewer counter attacks, have less possession with zero to four passes and have less possession longer than 12 seconds [ 41 ]. Worse teams also have more very high-intensity running, high-intensity running and total distance covered [ 39 ]. Better teams cover more total distance with the ball and very high-intensity running with the ball [ 39 ]. Furthermore, the top teams show a faster recovering (recapture is 1.3 to 1.7 seconds faster than mean times) of ball possession [ 42 ]. Obviously, top teams score more goals per match [ 15 , 36 , 37 , 40 ]. The cited studies showed that a lot of factors influence success (operationalized as league ranking) in football. Overall, it appears that goal efficiency, passes and shots are the most important factors in this research area.

Six more studies used a comparative approach to investigate success factors operationalized differently to the articles discussed previously (Table 5 ). Two papers focused on goal difference [ 43 , 44 ]. Bekris et al . [ 43 ] compared matches with one-goal differences (short range results) as well as matches with three-goal differences or more (wide range results). Their analysis showed that winners in wide range results have more ball possession, perform more passes, win more duels (overall and aerial), and have more shots, shots on target and a higher shot accuracy. In the short range results these differences were not found. A winner-winner comparison showed that wide range winners perform more passes, have a higher pass accuracy, more short distance shots and shots on-target. Yue et al . [ 44 ] used a similar approach. They analyzed matches with a difference of two or more goals and matches with a difference of three or more goals. Goal efficiency, shots, passes and ball contacts were found to be the most important factors for scoring a goal (in this order). Clemente [ 45 ] and Delgado-Bordonau, Domenech-Monforte, Guzmán & Mendez-Villanueva [ 46 ] operationalized success as a continuance in a tournament. They compared teams with a different number of matches respectively teams that got to the semifinal. Both analyzed matches of the World Cup 2010. Clemente [ 45 ] revealed that teams with more matches in a tournament (the successful ones) score more goals through open play, have more shots inside the penalty area and perform more passes. Delgado-Bordonau et al . [ 46 ] showed that successful teams perform more shots on-target, have a higher efficiency and concede fewer shots. They also revealed that the first goal in the match leads to a victory for 66.7 percent in the group stage and for 81.3 percent in the knockout stage. Hughes and Franks [ 17 ] used a new and different approach to analyze football. They normalized the data into “goals/shots per 1000 possessions” to analyze the relative importance of ball possession. The authors used this parameter to compare successful teams (getting to the quarterfinals) and unsuccessful teams (first round losers) in the 1990 World Cup. Accordingly, successful teams show a strong trend to be better in converting possession into shots on goal (no significant difference). For ball possessions with more than eight passes, there is a significantly higher chance for successful teams to create a shooting opportunity (p<0.05). In contrast, the necessary shots for a goal increase with more passes per possession [ 17 ]. Hoppe, Slomka, Baumgart, Weber & Freiwald [ 47 ] used the final points accumulated by each team during one season in the German Bundesliga. They analyzed the running performance with and without ball possession of the teams. Only total distance with ball possession was a significant predictor for final points (p<0.01). They concluded that not only running performance is important for success, but rather the relation to technical/tactical skill regarding ball possession [ 47 ].

6. PREDICTIVE ANALYSES

Fourteen of the predictive analyses focused on differences between wins, draws and losses (two of these papers considered two groups: winners and non-winners) (Table 6 ). Four of these papers used a discriminant analysis to reveal the most discriminating factors [ 48 - 51 ]. Shots on goal was a discriminant factor in all four studies. Crosses, match location and ball possession [ 48 , 49 ] as well as the quality of the opponent (similar to strength or team ability) [ 49 ] were other identified factors. Collet [ 21 ] and Harrop and Nevill [ 52 ] used a regression analysis/model and showed that higher pass accuracy is a good predictor for success. More shots, fewer passes, fewer dribbling and match location are further predictors [ 52 ]. Collet [ 21 ] investigated the influence of possession on success and showed that possession is not as relevant as assumed. If the strength of a team is controlled, the influence of possession on success will range from -5.7% (in German Bundesliga; significant (p<0.05)) to +1.8% (all national teams; not significant). The fact that possession has a potential negative link to success may be worth further examination. Efficiency measures seem to be better predictors for success [ 21 , 29 , 31 , 44 , 46 ]. Liu, Gomez, Lago-Penas and Sampaio [ 22 ], Liu, Hopkins and Gomez [ 53 ] and Mao, Peng, Liu and Gomez [ 54 ] used cumulative logistic-regression in a generalized linear model. They also divided the sample into close matches and unbalanced matches (a cluster analysis based on the goal difference was used) with a cluster analysis and cut-off values. In past research it appeared to be more likely in close matches that both teams play at their best [ 22 , 55 ]. They showed that shots on goal, shot accuracy, tackles and aerial advantage have positive effects on winning [ 22 , 54 ]. Liu et al . [ 53 ] also investigated the within-team effects (changes in team values between matches) and between-team effects (differences between average team values over all matches). Shots on target and total shots have positive within-team effects on winning. Game location showed a small positive within-team effect. Ball possession showed a small negative within-team effect but also a small positive between-team effect. Within-team effects varied depending on strength of team and opponent [ 53 ].

Gómez, Gómez-Lopez, Lago and Sampaio [ 56 ] used a factor analysis with several factors and the zone of the pitch. For the zone of the pitch they divided the field into five zones from goal to goal and into three to five subzones in each of these zones. They identified four factors. All factors are highest for winners. The best discrimination is given for ball recovery in zone two (2.1, 2.2 and 2.3) (penalty zone to center circle) and offensive actions with long passing sequences in zone 5.1 (six-yard box) and 5.2 (within penalty zone). Bar-Eli, Tenenbaum and Geister [ 57 ] and Mechtel et al . [ 25 ] investigated the impact of a player’s dismissal. Both found out that a sending-off decreases (sanctioned team) respectively increases (opponent) the chance of winning. Mechtel et al . [ 25 ] also identified strength (points earned in the last three seasons) and home advantage as success factors. Torgler [ 58 ] applied an economic win function to determine the influences on winning or not winning during the FIFA World Cup 2002. He showed that a higher number of shots on goal leads to a higher probability to win. He also revealed the negative effect of a player’s dismissal. Hosting the tournament was a strong advantage as well. It increases the chance of winning by 45 percentage points [ 58 ]. Hanau, Wicker and Soebbing [ 59 ] investigated the difference between the expected outcome of a football match and the actual outcome. They found out that the actual outcome is determined by the standing in the last season and home advantage.

The second most frequent kind of predictive analyses are studies that used goal scoring as the indicator of success (Table 7 ). Pollard and Reep [ 12 ] developed a quantitative variable, called the ‘yield’, defined as the probability of a goal being scored minus the probability of one being conceded. The yield for the penalty area as starting zone of ball possession and open play is 78.3 (per 1000 possessions you can expect 78.3 more goals scored than goals conceded). They also found that open play always has a higher yield than set play [ 12 ]. Carmichael and Thomas [ 26 ] established a match-based production function. They found that shots on goal, shots that hit woodwork, tackles, own goals and free kicks are significant predictive factors (p<0.05) for the home teams. Kapidžić, Bećirović and Imamović [ 60 ] also identified shots on goal as a significant predictor for goal scoring (p=0.027). Wright, Atkins, Polman, Jones and Sargeson [ 61 ] postulated position of attempt, goal keepers’ position and type of shot as the three predictors for goal scoring. Tenga, Holme, Ronglan and Bahr [ 62 ] and Tenga, Ronglan and Bahr [ 63 ] used the same data set with different methods for their analysis. Both papers showed that counter attacks are more effective than elaborated attacks in producing goals. Grund [ 20 ] used a network analysis to identify success factors. He revealed that networks with high intensity and low centralization have a better performance. An increased passing rate lead to a better performance in this study [ 20 ].

In the last group of predictive analyses three variables of interest were collected (Table 8 ). The most frequent variable is goal difference as utilized in five papers [ 13 , 25 , 64 , 65 ]. In all articles match location is positively linked to goal difference. Quality of the opponent was also identified as a significant predictor (p<0.05) [ 25 , 64 , 65 ]. Moreover, Carmichael et al . [ 13 ] showed that passes, tackles, interceptions, clearances, blocks, interceptions, free kicks and ball caught by goalkeeper are significant predictors for a positive goal difference(p<0.05). A red card was associated with a negative goal difference [ 13 , 25 , 64 ]. Garcia-Rubio et al . [ 65 ] showed that scoring first is the strongest predictor for a positive goal difference. Lago-Penas, Gomez-Ruano, Megias-Navarro and Pollard [ 28 ] used a tree analysis to determine the effects of scoring first on the outcome of a match. They showed that the first scoring team scored 1.88 goals more than their opponent on average. This is influenced by the quality of the teams and the match period in which the first goal was scored [ 28 ]. Oberstone [ 15 ], Hall, Szymanski and Zimbalist [ 66 ], and Kringstad and Olsen [ 67 ] investigated relevant factors for the league ranking in a predictive design. Hall et al . [ 66 ] focused on the relationship between payroll and performance. They found that there is a higher winning probability of 0.614 for 50% more spending in payroll. The top level is more sensitive to spending. Oberstone [ 15 ] developed a regression model to predict the league ranking. He revealed six variables which are sufficient for predicting the league ranking (in terms of points earned). These six variables are the percentage of goals to shot (goals divided by shots), the percentage of goals outside penalty area (goals from outside penalty area divided by goals within penalty area), ratio of short to long passes, total crosses, average goals conceded per match and yellow cards. Kringstad and Olsen [ 67 ] studied budgeted revenue and success. They showed that budgeted revenues are a significant factor (p<0.05) but only for the bottom-half of the teams and not for the top-half of the teams. The remaining three papers focused on points as the variable of interest. Lago [ 68 ] defined performance as shots performed minus shots conceded, and found that this is a predictor for more points. Furthermore, he showed that the higher the FIFA ranking is, the higher the chance to win. Collet [ 21 ] focused on ball possession. His result was that more time with the ball leads to more points and goals, but if it is controlled by team strength a negative effect for possession can be observed. Passes and shot accuracy turned out to be better predictors for points. Coates, Frick and Jewell [ 69 ] investigated the relationship between salary structure and success. They revealed that salary inequality has a negative effect on success but the wage bill of a team has a positive relationship with success by a similar amount. This results support the cohesion theory [ 69 ].

7. ANALYSES OF HOME ADVANTAGE

The review of predictive analyses already showed that match location (home advantage) is an important factor in explaining success in football [ 25 , 26 , 48 , 49 , 53 , 58 , 57 , 64 ]. Seventeen papers that focused mainly on match locations specifically home advantage were identified in this the review (see Table 9 ). In one of these papers [ 26 ] further factors related to success, besides home advantage, were also investigated. The first analysis of home advantage in football was done by Pollard [ 70 ]. He investigated different team sports including the first four football divisions in England from 1888 to 1984. There was very little variation between 85 seasons (between 1939 and 1945 there were no official seasons due to World War II). The points won by the home team differed between 62.5 percent and 67.9 percent. Clarke and Norman [ 11 ] provided an approach to quantify team ability and home advantage at a team level due to the influence of the quality of opponent (team ability or strength). This approach was also used by other authors to define home advantage for a team [ 25 , 49 , 64 ]. Clarke and Norman [ 11 ] stated that it is necessary to consider difference in ability to calculate home advantage. In their research the home advantage relating to goals differed from year to year and between teams. The average home advantage between 1981 and 1990 in England resulted in 0.528 goals per match. Another result is that team ability is more important than home advantage [ 11 ]. Overall, home advantage explains around 60 percent with some variations [ 71 - 86 ] (Table 9 ). Before the 1980s, the explaining percentage of home advantage was moderately higher [ 71 ]. Saavedra Garcia, Aguilar, Fernández Romero and Sa Marques [ 72 ] investigated home advantage in the first division in Spain between 1928 and 2011. Home teams won 70.8 percent of the points for the period when 2 points were awarded for a victory and 56.7 percent when three points were awarded for a victory. Lago-Pens et al . [ 28 ] showed a consistent home advantage for all five major leagues in Europe (France, Italy, Spain, England and Germany) for the season 2014/15. Home teams won between 56.47 percent (Italy) and 61.84 (Germany) of the awarded points for a victory.

Lago-Penas and Lago-Ballesteros [ 73 ] investigated the variables that discriminate best (discriminant value ≥|.30|) between home and away teams. Home teams score more goals, perform more crosses, more passes, have more ball possession and commit more fouls. Away teams show more losses of possession and gather more yellow cards. Armatas and Pollard [ 74 ] found shots, clearances, headed shots, corners and saves to have the highest effect size for match variables between home and away teams. Goumas [ 75 ] analyzed home advantage on a team level adjusted for team ability (operationalized by UEFA ranking points). Home advantage did not vary between teams despite a home advantage of 73% for Arsenal London and a home advantage of 58% for Inter Milan. Away disadvantage varied between teams ranging from 45% (F.C. Barcelona) to 68% (Olympiacos F.C.). There was also a tendency that teams with a higher home advantage had lower away disadvantage. Home advantage and away disadvantage differed significant between countries 70% English teams to 52% Turkish teams (p=0.01) [ 75 ]. The major causes for home advantage discussed are crowd support, travel fatigue, familiarity, territoriality, referee bias, special tactics, rule factors and psychological factors as well as the interaction of these [ 70 , 76 , 77 ].

8. INTEGRATIVE DISCUSSION

The aim of this study was to review performance analyses in adult male football in order to identify success factors and utilized methods. The review revealed that there is an extensive and growing body of performance analyses literature in football. In contrast to early studies that were often based on descriptive designs [ 9 ], analyses with predictive designs, explaining more and more success factors [ 21 , 22 , 49 ], have gained momentum in recent years. The most frequently studied variables were shots (27 times)/shots on goal (23 times) followed by passes (20 times). Overall 76 different variables were investigated in the reviewed papers. Based on the results in the papers, the most influential variables are efficiency [ 22 , 29 , 46 ], shots on goal [ 49 , 54 ], possession [ 39 ], pass accuracy/successful passes [ 32 , 35 ], quality of opponent [ 25 , 28 , 64 ], and match location [ 49 , 76 , 65 ]. 4

It became apparent that performance in football depends on a high number of variables. For example, Oberstone [ 15 ] investigated 24 different variables. Using a 6-variable regression (percentage of goals to shots, percentage of goals scored outside of box, ratio of short/long passes, total crosses, average goals conceded per match and yellow cards) he predicted the points earned by English football teams in the 2007/2008 season. The fit delivered an R 2 =0.990 (p<0.0000) indicating strong evidence for his model. Similarly, Kapidžić et al . [ 30 ] investigated 21 variables in the first division in Bosnia and Herzegovina 2008/2009 (12 matches) and in the 2008 European Championship (13 matches). While in the first division 13 variables ( e.g. , shots, passes, and offensive structure) significantly discriminate between winners and losers (p<0.05), in the European Championship only three variables were significant (shots on goal, number of goals scored within penalty area and number of goals scored outside penalty area) (p<0.05). Although both studies considered many variables, it were the obvious variables such as shots and goals that became significant,

explaining only little of the underlying mechanisms of success in football. Liu et al . [ 22 ] and Mao et al . [ 54 ] studied very similar variables in two different samples. Shot on target and tackle were the only two discriminating variables in both studies. Other variables had no clear effect or the effect depended on the context [ 22 , 54 ]. Based on these results, it seems that not many success factors in football are stable over different contexts and samples. It should be noted, however, that an exclusive focus on statistical data ( e.g. , shots, possession) will probably be not sufficient to explain these mechanisms. A more sophisticated approach is needed to reveal these mechanisms. This includes more variables and the use of more complex statistical approaches such as ordered logit regressions to determine the influence of these variables. Also, the inclusion of qualitative variables e.g. , self-perception and social perception or the evaluation of motivation can help to reveal the nature of performance. A third area of investigation should be more player centric such as questionnaires e.g. , about group cohesiveness or personality traits.

Moreover, the review revealed that to date many different types of matches and settings have come into the focus of researchers, providing a more holistic view on success factors in football. Regarding comparative and predictive analyses, 34 articles focused on league matches, 13 on cup matches for national teams and six on cup matches for clubs. Especially studies that integrate different types of matches and settings provide useful insights allowing for generalizable statements. For example, Collet [ 21 ] analyzed more than 6,000 matches including league matches from England, Italy, France and Germany, matches from the European Champions League and the Europe League as well as national matches from Europe, America, Africa and Asia. In this way, he found that in the leagues pass accuracy and shot accuracy are more important for success than ball possession, in contrast to the assumptions of many scholars and professionals (for Germany one percent more possession even leads to a winning probability that is reduced by 5.7 percent). Also Lago-Penas et al . [ 28 ] studied over 1,800 matches in the five top leagues across Europe. They could show that scoring first is a crucial part of winning a match. In total, 27 studies chose a design that comprised an international comparison, while among the studies that focused on one nation, England showed to be the most studied country in football (11 articles), followed by Germany (7 articles) and Spain (7 articles) (Table 10 ).

Methodologically, the review showed that in recent years new ways of statistical analyses were introduced. Lago et al . [ 48 ] were the first authors who used a discriminant analysis to identify differences between winners and losers. Moura et al . [ 51 ] combined this approach with a factor analysis. They investigated 14 variables and performed a factor analysis. Subsequently, a cluster analysis was used to classify the teams into two groups. Finally, they showed that 70.3 percent of the winning teams were classified into the same group (67.8 percent for drawing and losing teams). Shots, shots on goal, playing time with ball possession and percentage of ball possession were the most important variables to discriminate between winning teams and drawing or losing teams in this study. Liu et al . [ 22 ] used a cluster analysis to identify only close matches. This approach has the advantage that both teams give probably their best and do not lean

back because the match is already decided [ 22 , 55 ]. The concept of close and unbalanced matches also improved the analysis of success factors in football [ 22 , 29 ]. Close matches are defined by a small goal difference. In unbalanced matches one team dominates the other team in terms of goal difference very obviously [ 55 , 87 - 91 ]. This concept was first introduced in a discrimination study about rugby in 2010 [ 55 ] and is widely used since then [ 22 , 29 , 55 , 87 - 91 ].

However, most researchers (comparative and predictive design) used a form of regression analysis (22 studies). Discriminate analysis (six studies) and ANOVA (five studies) are the second and third most frequently used statistical methods. For example, Mechtel et al . [ 25 ] and Collet [ 21 ] used an ordered logit regression to identify the influence of a dismissal respective ball possession. An advantage of this method is that it controls for other variables and to investigate a goal-based and result-based approach. Liu et al . [ 22 ] and Mao et al . [ 54 ] used a generalized linear model. First they ran a cluster analysis to define cut-off values (see above). Then they applied a cumulative logistic regression to predict winning probabilities. Afterwards they employed non-clinical magnitude-based inferences to evaluate the true effect of the variable [ 22 , 54 ]. This approach allows a more realistic and intuitive interpretation of effects [ 92 ]. Since much of current research is still descriptive or comparative, these two approaches are promising with regard to providing new, valuable insights to performance in football.

Finally, a crucial point that was found is sample size. Many studies, such as Kapidžić et al . [ 30 ] who analyzed 25 matches, rely on small sample sizes. Of the reviewed papers, the sample sizes varied from seven matches [ 31 ] to 89,813 matches [ 76 ]. In total, only 28 papers analyzed all matches of a whole or several seasons. It appears that many studies lack sample sizes that are adequate to produce generalizable results.

9. PRACTICAL IMPLICATIONS

A critical question is how the results can support football coaches and their staff. Based on the findings of this review, coaches could be advised to instruct their teams to shoot extensively while at the same time considering shot accuracy. However, advice of this kind would not do justice to the complex nature of football and the demands of coaches. Bishop [ 93 ] emphasized that only results providing performance-enhancing knowledge will be applied in practice. Hence, research has to deliver results that make it more likely to win. This also includes findings with regard to training, match preparation and coaching. Nash and Collins [ 94 ] stated that coaching is a very complex and dynamic process. The actions of coaches are based on knowledge that has been acquired over years of experience and reflection, that is, tacit knowledge [ 94 , 95 ]. For coaches, the importance of shots for scoring goals is more than obvious. It is also hardly surprising that pass accuracy, the opponent’s quality and home advantage have a positive impact. A benefit for football coaches would be to reveal the partial influence of these variables including their interactions ( e.g. , by analyzing regression models).

However, there are less obvious findings that provide empirical evidence for beneficial tactical behaviors. First, possession is not as important as might be assumed [ 21 , 22 , 54 ]. Second, a focus on counter attacks can be very effective and can be utilized as a successful tactical strategy, especially for underdogs [ 41 ]. Ball recovery in the zone between a team’s own penalty area and center circle [ 56 ] and a quick ball recovery [ 42 ] can result in significantly more successful attacks respectively goals (p<0.001). Coaches can build on this evidence to improve tactical concepts. For example, coaches could put more emphasis on the practice of counter attacks, as a tactical element, to overwhelm the opponent’s defense and produce more good scoring opportunities. Also pressing, the attempt to recover the ball as close as possible to the opponent’s penalty area seems to be a promising tactic. It shortens not only the space between the attackers and the goal, it can also cause confusion within the opposing defense. This could lead to more goals since counterattacks are more effective against an imbalanced defense [ 62 ].

The aim of this work was to review research in performance analysis relating to success factors in elite men’s football. In total, 68 articles were identified and clustered based on their study design with regard to comparative, predictive or home advantage analyses. It was found that the most influential variables are efficiency, shots on goal, ball possession, pass accuracy/successful passes, as well as the quality of opponent and match location. New statistical approaches, such as discriminant analysis, factor analysis, regression analysis and magnitude-based inferences reveal interactions between these variables.

6  Bar-Eli et al . [ 57 ] focused also on a psychological factor. However, they focused on the factor that leads to a dismissal and not to a psychological factor that contributes directly to performance

Concerning study design, an increase of predictive studies was found. For future studies, we suggest considering more often one of the ‘Big 3’ leagues (Spain, England and Germany) or all of them to get more representative samples. Furthermore, the consideration of other influences on success such as psychological factors and/or weather conditions would be of interest. Additionally, new methodological ways of analyzing success factors in football could be beneficial. For example, Borrie, Johnson and Magnusson [ 96 ] presented a method to investigate time-based events in sports. Moreover, more advanced statistical methods should be applied to ensure a broader insight into the mechanisms of performance such as regressions and magnitude-based inferences [ 21 , 22 , 25 ].

Most of the studies did not consider the influence of contextual ( e.g. , home advantage, quality of opponent) and interactional variables ( e.g. , first goal scored by time of goal scoring). In some studies, the influence of variables is also computed without a clear definition of the investigated variables. This lack of operational definitions poses a problem and, inter alia, does not allow valid comparisons between the studies. In future research, variables should be clearly defined to enable comparable and reproducible results (see also Mackenzie & Cushion [ 18 ]; Sarmento et al . [ 19 ]). The consideration of interacting variables such as quality of opponent and match location should also be considered in future investigations to provide more insights. Future study designs should also make sure to take the differences between different competitions ( e.g. leagues, cup competitions) into account, especially the differences between a league match and a knockout match.

Moreover, we found very different approaches regarding the sample size required for generalization. Sample sizes of considered matches varied between very low numbers and thousands of matches. A small sample size is clearly a limitation in some of the reviewed papers, resulting in no generalizability. Studies investigating league matches should consider at least a sample size of one season. Hence, our review supports the finding of Mackenzie and Cushion [ 18 ] with regard to small sample sizes that remains a major deficit of performance analyses in football. Additionally, future studies should use effect sizes to interpret the results properly (see also Broich et al . [ 29 ]). A last important aspect to consider when designing a study is the context of the analyzed sample. For example, the tactic that is used ( e.g. , counterattacks vs. elaborate attacks) could vary regarding the opponent.

Based on the idea that performance is a consequence of prior learning, inherent skills, situational factors and influence of the opposition [ 97 ], the assumption holds that future performance is to a large extent a consequence of previous performance. Again, this underlines the aforementioned importance of considering the context of a sample as well as the operational definition of the investigated variables. Prior learning and inherent skills are two variables that were not considered in research about success factors in football as defined in this review. Both are exciting new possibilities for future research.

Finally, we would like to point to two methodological approaches that might lead to new insights in analyzing football performance. First, social network analysis provides new methods to analyze different aspects utilizing relational data, ( e.g. , the passing network of football teams), that have the potential to contribute substantially to a better understanding of success [ 20 , 98 , 99 ]. Second, psychological factors could be taken into account for future research ( e.g. , reversal theory, see Apter [ 100 ]). The investigation of psychological factors is, in fact, more difficult than the analysis of statistical data. The operationalization of cohesion found in this review [ 34 ] is a good example of the use of psychological concepts. 6

As this review has shown, generalizable knowledge about success factors in football can be a helpful resource for coaches to gain a better understanding of the match. While significant progress in the field of performance in football was made in the last years, the review identified various deficits that future research has to address to provide more valuable information about what determines success.

CONSENT FOR PUBLICATION

Not applicable.

CONFLICT OF INTEREST

The authors declare no conflict of interest, financial or otherwise.

ACKNOWLEDGEMENTS

We acknowledge support by Deutsche Forschungsgemeinschaft and Open Access Publishing Fund of Karlsruhe Institute of Technology.

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Published contents, about the editor, journal metrics, readership statistics:, total views/downloads: 857,000, unique views/downloads: 176,480, about the journal, table of contents.

• INTRODUCTION
• MATERIALS AND METHODS The data had to deal with performance analysis in football. The variables of interest were linked to success (win/loss, goals, continuance in league/tournament, league ranking and points won). Adult elite football was investigated. The study was written in English. The study was published in an academic journal. The study design was comparative or predictive or focused on home advantage in football.
• COMPARATIVE ANALYSES
• ANALYSES OF HOME ADVANTAGE
• INTEGRATIVE DISCUSSION
• PRACTICAL IMPLICATIONS

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• Essay on United States

Free Football Research Paper Sample

Type of paper: Research Paper

Topic: United States , American Football , Football , America , American Sports , Soccer , Organization , Sports

Published: 02/23/2020

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[Writer’s Name]

Football has been played in times since antiquity. Football, along with rugby and soccer, has derived from the Greek game of ‘harpaston.’ (Hornetfootball.org) American football began in 1879 when Walter Camp, a player and coach at Yale University constituted its rules. It was at the Massosoit convention that the first attempts at penning down the rules for this game were made. Camp edited every American Football rule book until he died in 1925. The National Football League was formed in 1920. (Inventors.about.com) In America, football is played both by amateurs as well as professionally depending upon the league, and is amongst the most popular sports in the country. In December 2005, 34% of Americans proclaimed football as their favorite sport. (Gallup.com) Football fans are mostly males between the age group 18-64. The distribution of fans is equal when it comes to white, black and non-white people. About 66% of the fans have studied in college and have lived in either urban or suburban areas of the country. When it comes to the players, I would mention the professional NFL ones and say that they are physically fit males between the ages 20-48. (Studymode.com) Football reflects the American value system like no other sport. Foreigners need to only watch a single game and they will get an insight into attitudes, concerns and beliefs of Americans. Football has the biggest impact on American society. Tough youngsters elbowing and jumping on each other, and their sheer physical built, everything affects the Americans. Many young Americans have football players as their role models. Football is the American culture’s greatest spectacle, be it the focus of homecoming or holiday celebrations – football is symbolic to all of them. Widely watched events like the Super Bowl and college football’s games on New Year’s Day provides a platform for Americans to celebrate on a regional, local, ethnic and collegiate levels. It is a violent, hierarchical and gendered sport, and is often said to be symbolic of American culture and society (and what is wrong with them) by many supporters and detractors. Football events are highly and extensively covered and cashed in by the media. The annual Super Bowl has become late-twentieth-century America's single-greatest televised sporting event. (Smc.edu) It has become highly commercialized and professionalized in today’s times. With the advent of television, scholarships to players and regulatory powers to the NCAA, many schools chose not to participate in it since it defeated the purpose of the game. Football is now watched by two classes of people in two different ways: one as a modern entertainment industry with its endorsements, advertisements and other monetary returns, while the others view it as a traditional sport wherein the monetary value of the sport is not as important as the passion to win. Football encapsulates gender roles as being a proving area for men to test and develop their manhood, and instilling values of teamwork and self-reliance. Females are part of the team through pep squads and cheerleading which denotes a complete reversal of roles. As a social institution, football has come a long way since its advent. It is enjoyed by players, spectators and even gamblers who put wagers on each game. Even with the advent of computers and high-end mobile devices with all their entertainment offerings, people still continue to watch the game with their loved ones before Thanksgiving dinner. It has become an important part of community life and even the nature of this institution has changed. In older times, we saw people playing the game for what it stood for: team spirit, taking direction and working well with others to achieve a common goal. But we now see the rampant commercialization of the sport, players resorting to cheating and even using steroids to enhance performance, etc. Despite all the negatives, one cannot dismiss the importance of this institution, for it is garnering all these desperate attempts at victory due to its very special place in people’s lives.

Works Cited

“A Brief History of the Game.” Hornetfootball.org. Accessed on December 01, 2013. <http://www.hornetfootball.org/documents/football-history.htm> Bellis, Mary. “History of Football.” About.com. Accessed on December 01, 2013. <http://inventors.about.com/od/fstartinventions/a/HistoryFootball.htm> Morris, Peter. “Football in the USA.” Santa Monica College. Accessed on December 01, 2013. <http://homepage.smc.edu/morris_pete/papersandpresentations/main/footballinusa.html> "Sociology of American Football" StudyMode.com. 09 2013. 2013. 09 2013 http://www.studymode.com/essays/Sociology-Of-American-Football-1914020.html Jones, Jeffrey. “Nearly Half of Americans are football fans.” Gallup. 04. 04.2013. <http://www.gallup.com/poll/22240/nearly-half-americans-baseball-fans.aspx>

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• Quantum Research

Landmark IBM error correction paper published on the cover of Nature

Ibm has created a quantum error-correcting code about 10 times more efficient than prior methods — a milestone in quantum computing research..

27 Mar 2024

Rafi Letzter

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Today, the paper detailing those results was published as the cover story of the scientific journal Nature. 1

Last year, we demonstrated that quantum computers had entered the era of utility , where they are now capable of running quantum circuits better than classical computers can. Over the next few years, we expect to find speedups over classical computing and extract business value from these systems. But there are also algorithms with mathematically proven speedups over leading classical methods that require tuning quantum circuits with hundreds of millions, to billions, of gates. Expanding our quantum computing toolkit to include those algorithms requires us to find a way to compute that corrects the errors inherent to quantum systems — what we call quantum error correction.

Read how a paper from IBM and UC Berkeley shows a path toward useful quantum computing

Quantum error correction requires that we encode quantum information into more qubits than we would otherwise need. However, achieving quantum error correction in a scalable and fault-tolerant way has, to this point, been out of reach without considering scales of one million or more physical qubits. Our new result published today greatly reduces that overhead, and shows that error correction is within reach.

While quantum error correction theory dates back three decades, theoretical error correction techniques capable of running valuable quantum circuits on real hardware have been too impractical to deploy on quantum system. In our new paper, we introduce a new code, which we call the gross code , that overcomes that limitation.

This code is part of our broader strategy to bring useful quantum computing to the world.

While error correction is not a solved problem, this new code makes clear the path toward running quantum circuits with a billion gates or more on our superconducting transmon qubit hardware.

What is error correction?

Quantum information is fragile and susceptible to noise — environmental noise, noise from the control electronics, hardware imperfections, state preparation and measurement errors, and more. In order to run quantum circuits with millions to billions of gates, quantum error correction will be required.

Error correction works by building redundancy into quantum circuits. Many qubits work together to protect a piece of quantum information that a single qubit might lose to errors and noise.

On classical computers, the concept of redundancy is pretty straightforward. Classical error correction involves storing the same piece of information across multiple bits. Instead of storing a 1 as a 1 or a 0 as a 0, the computer might record 11111 or 00000. That way, if an error flips a minority of bits, the computer can treat 11001 as 1, or 10001 as 0. It’s fairly easy to build in more redundancy as needed to introduce finer error correction.

Things are more complicated on quantum computers. Quantum information cannot be copied and pasted like classical information, and the information stored in quantum bits is more complicated than classical data. And of course, qubits can decohere quickly, forgetting their stored information.

Research has shown that quantum fault tolerance is possible, and there are many error correcting schemes on the books. The most popular one is called the “surface code,” where qubits are arranged on a two-dimensional lattice and units of information are encoded into sub-units of the lattice.

But these schemes have problems.

First, they only work if the hardware’s error rates are better than some threshold determined by the specific scheme and the properties of the noise itself — and beating those thresholds can be a challenge.

Second, many of those schemes scale inefficiently — as you build larger quantum computers, the number of extra qubits needed for error correction far outpaces the number of qubits the code can store.

At practical code sizes where many errors can be corrected, the surface code uses hundreds of physical qubits per encoded qubit worth of quantum information, or more. So, while the surface code is useful for benchmarking and learning about error correction, it’s probably not the end of the story for fault-tolerant quantum computers.

Exploring “good” codes

The field of error correction buzzed with excitement in 2022 when Pavel Panteleev and Gleb Kalachev at Moscow State University published a landmark paper proving that there exist asymptotically good codes — codes where the number of extra qubits needed levels off as the quality of the code increases.

This has spurred a lot of new work in error correction, especially in the same family of codes that the surface code hails from, called quantum low-density parity check, or qLDPC codes. These qLDPC codes are quantum error correcting codes where the operations responsible for checking whether or not an error has occurred only have to act on a few qubits, and each qubit only has to participate in a few checks.

But this work was highly theoretical, focused on proving the possibility of this kind of error correction. It didn’t take into account the real constraints of building quantum computers. Most importantly, some qLDPC codes would require many qubits in a system to be physically linked to high numbers of other qubits. In practice, that would require quantum processors folded in on themselves in psychedelic hyper-dimensional origami, or entombed in wildly complex rats’ nests of wires.

In our paper, we looked for fault-tolerant quantum memory with a low qubit overhead, high error threshold, and a large code distance.

Bravyi, S., Cross, A., Gambetta, J., et al. High-threshold and low-overhead fault-tolerant quantum memory. Nature (2024). https://doi.org/10.1038/s41586-024-07107-7

In our Nature paper, we specifically looked for fault-tolerant quantum memory with a low qubit overhead, high error threshold, and a large code distance.

Let’s break that down:

Fault-tolerant: The circuits used to detect errors won't spread those errors around too badly in the process, and they can be corrected faster than they occur

Quantum memory: In this paper, we are only encoding and storing quantum information. We are not yet doing calculations on the encoded quantum information.

High error threshold: The higher the threshold, the higher amount of hardware errors the code will allow while still being fault tolerant. We were looking for a code that allowed us to operate the memory reliably at physical error rates as high as 0.001, so we wanted a threshold close to 1 percent.

Large code distance: Distance is the measure of how robust the code is — how many errors it takes to completely flip the value from 0 to 1 and vice versa. In the case of 00000 and 11111, the distance is 5. We wanted one with a large code distance that corrects more than just a couple errors. Large-distance codes can suppress noise by orders of magnitude even if the hardware quality is only marginally better than the code threshold. In contrast, codes with a small distance become useful only if the hardware quality is significantly better than the code threshold.

Low qubit overhead: Overhead is the number of extra qubits required for correcting errors. We want the number of qubits required to do error correction to be far less than we need for a surface code of the same quality, or distance.

We’re excited to report that our team’s mathematical analysis found concrete examples of qLDPC codes that met all of these required conditions. These fall into a family of codes called “Bivariate Bicycle (BB)” codes. And they are going to shape not only our research going forward, but how we architect physical quantum systems.

The gross code

While many qLDPC code families show great promise for advancing error correction theory, most aren’t necessarily pragmatic for real-world application. Our new codes lend themselves better to practical implementation because each qubit needs only to connect to six others, and the connections can be routed on just two layers.

To get an idea of how the qubits are connected, imagine they are put onto a square grid, like a piece of graph paper. Curl up this piece of graph paper so that it forms a tube, and connect the ends of the tube to make a donut. On this donut, each qubit is connected to its four neighbors and two qubits that are farther away on the surface of the donut. No more connections needed.

The good news is we don’t actually have to embed our qubits onto a donut to make these codes work — we can accomplish this by folding the surface differently and adding a few other long-range connectors to satisfy mathematical requirements of the code. It’s an engineering challenge, but much more feasible than a hyper-dimensional shape.

We explored some codes that have this architecture and focused on a particular [[144,12,12]] code. We call this code the gross code because 144 is a gross (or a dozen dozen). It requires 144 qubits to store data — but in our specific implementation, it also uses another 144 qubits to check for errors, so this instance of the code uses 288 qubits. It stores 12 logical qubits well enough that fewer than 12 errors can be detected. Thus: [[144,12,12]].

Using the gross code, you can protect 12 logical qubits for roughly a million cycles of error checks using 288 qubits. Doing roughly the same task with the surface code would require nearly 3,000 qubits.

This is a milestone. We are still looking for qLDPC codes with even more efficient architectures, and our research on performing error-corrected calculations using these codes is ongoing. But with this publication, the future of error correction looks bright.

Fig. 1 | Tanner graphs of surface and BB codes.

Fig. 1 | Tanner graphs of surface and BB codes. a, Tanner graph of a surface code, for comparison. b, Tanner graph of a BB code with parameters [[144, 12, 12]] embedded into a torus. Any edge of the Tanner graph connects a data and a check vertex. Data qubits associated with the registers q(L) and q(R) are shown by blue and orange circles. Each vertex has six incident edges including four short-range edges (pointing north, south, east and west) and two long-range edges. We only show a few long-range edges to avoid clutter. Dashed and solid edges indicate two planar subgraphs spanning the Tanner graph, see the Methods. c, Sketch of a Tanner graph extension for measuring Z ˉ \={Z} and X ˉ \={X} following ref. 50, attaching to a surface code. The ancilla corresponding to the X ˉ \={X} measurement can be connected to a surface code, enabling load-store operations for all logical qubits by means of quantum teleportation and some logical unitaries. This extended Tanner graph also has an implementation in a thickness-2 architecture through the A and B edges (Methods).

Fig. 2 | Syndrome measurement circuit.

Fig. 2 | Syndrome measurement circuit. Full cycle of syndrome measurements relying on seven layers of CNOTs. We provide a local view of the circuit that only includes one data qubit from each register q(L) and q(R) . The circuit is symmetric under horizontal and vertical shifts of the Tanner graph. Each data qubit is coupled by CNOTs with three X-check and three Z-check qubits: see the Methods for more details.

Why error correction matters

Today, our users benefit from novel error mitigation techniques — methods for reducing or eliminating the effect of noise when calculating observables, alongside our work suppressing errors at the hardware level. This work brought us into the era of quantum utility. IBM researchers and partners all over the world are exploring practical applications of quantum computing today with existing quantum systems. Error mitigation lets users begin looking for quantum advantage on real quantum hardware.

But error mitigation comes with its own overhead, requiring running the same executions repeatedly so that classical computers can use statistical methods to extract an accurate result. This limits the scale of the programs you can run, and increasing that scale requires tools beyond error mitigation — like error correction.

Last year, we debuted a new roadmap laying out our plan to continuously improve quantum computers over the next decade. This new paper is an important example of how we plan to continuously increasing the complexity (number of gates) of the quantum circuits that can be run on our hardware. It will allow us to transition from running circuits with 15,000 gates to 100 million, or even 1 billion gates.

Bravyi, S., Cross, A.W., Gambetta, J.M. et al. High-threshold and low-overhead fault-tolerant quantum memory. Nature 627, 778–782 (2024). https://doi.org/10.1038/s41586-024-07107-7

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