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Data Analytics in Football provides students, researchers and coaches with a firm grounding in the principles of modern performance analysis. It offers an insight into the use of positional data, exploring how it can be collected, modelled, analysed and interpreted. Introducing cutting-edge methods, the book challenges long-held assumptions and encourages a new way of thinking about football analysis. Based on data collected from the German Bundesliga and the UEFA Champions League, the book seeks to define the role of positional data in football match analysis by exploring topics such as: What is positional data analysis and how did it emerge from conventional match analysis? How can positional data be collected and which technologies can be used? What are the benefits of a data-driven approach to decision making in football? What Key Performance Indicators based on positional data should be used? How can traditional match analysis be complemented by using positional data and advanced KPIs? How can these new methods evolve in the future? Accessibly written, packed full of examples from elite football and supplemented with expert interviews (Ralf Rangnick, Urs Siegenthaler and others), Data Analytics in Football is a thought-provoking, rigorously evidence-based guide to the use of data analytics in football performance analysis. As such, it is a vital resource for any student, researcher or coach interested in performance analysis and skill acquisition, or anyone interested in football more generally.
Daniel Link explores how data analytics can be used for studying performance in soccer. Based on spatiotemporal data from the German Bundesliga, the six individual studies in this book present innovative mathematical approaches for game analysis and player assessment. The findings can support coaches and analysts to improve performance of their athletes and inspire other researchers to advance the research field of sports analytics.
Well written and thoughtful. Takes us on a tour of some of Europe's most innovative football thinkers - Financial Times The future of football is now. Football's data revolution has only just begun. The arrival of advanced metrics and detailed analysis is already reshaping the modern game. We can now fully assess player performance, analyse the role of luck and measure what really leads to victory. There is no turning back. Now the race is on between football's wealthiest clubs and a group of outsiders, nerds and rule-breakers, who are turning the game on its head with their staggering innovations. Winning is no longer just about what happens out on the pitch, it's now a battle taking place in boardrooms and on screens across international borders with the world's brightest minds driving for an edge over their fiercest rivals. Christoph Biermann has moved in the midst of these disruptive upheavals, talking to scientists, coaches, managers, scouts and psychologists in the world's major clubs, traveling across Europe and the US and revealing the hidden - and often jaw-dropping - truths behind the beautiful game. 'A book full of exciting ideas and inside views on modern football. The most exciting book in an exciting time for football.' Thomas Hitzlsperger
'Football looked at in a very different way' Pat Nevin, former Chelsea and Everton star and football media analyst Football – the most mathematical of sports. From shot statistics and league tables to the geometry of passing and managerial strategy, the modern game is filled with numbers, patterns and shapes. How do we make sense of them? The answer lies in the mathematical models applied in biology, physics and economics. Soccermatics brings football and mathematics together in a mind-bending synthesis, using numbers to help reveal the inner workings of the beautiful game. This new and expanded edition analyses the current big-name players and teams using mathematics, and meets the professionals working inside football who use numbers and statistics to boost performance. Welcome to the world of mathematical modelling, expressed brilliantly by David Sumpter through the prism of football. No matter who you follow – from your local non-league side to the big boys of the Premiership, La Liga, the Bundesliga, Serie A or the MLS – you'll be amazed at what mathematics has to teach us about the world's favourite sport.
Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group. The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in: Ticket pricing Season ticket member retention Fan engagement Sponsorship valuation Customer relationship management Digital marketing Market research Data visualization. This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations. Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics.
One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, Second Edition provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports. The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from standard statistical analyses. The book integrates a large number of motivating sports examples throughout and offers guidance on computation and suggestions for further reading in each chapter. Features Covers numerous statistical procedures for analyzing data based on sports results Presents fundamental methods for describing and summarizing data Describes aspects of probability theory and basic statistical concepts that are necessary to understand and deal with the randomness inherent in sports data Explains the statistical reasoning underlying the methods Illustrates the methods using real data drawn from a wide variety of sports Offers many of the datasets on the author’s website, enabling you to replicate the analyses or conduct related analyses New to the Second Edition R code included for all calculations A new chapter discussing several more advanced methods, such as binary response models, random effects, multilevel models, spline methods, and principal components analysis, and more Exercises added to the end of each chapter, to enable use for courses and self-study
Moneyball meets Freakonomics in this myth-busting guide to understanding—and winning—the most popular sport on the planet. Innovation is coming to soccer, and at the center of it all are the numbers—a way of thinking about the game that ignores the obvious in favor of how things actually are. In The Numbers Game, Chris Anderson, a former professional goalkeeper turned soccer statistics guru, teams up with behavioral analyst David Sally to uncover the numbers that really matter when it comes to predicting a winner. Investigating basic but profound questions—How valuable are corners? Which goal matters most? Is possession really nine-tenths of the law? How should a player’s value be judged?—they deliver an incisive, revolutionary new way of watching and understanding soccer.
Data Analytics in Football provides students, researchers, and coaches with a firm grounding in the principles of modern performance analysis. It offers an insight into the use of positional data, exploring how they can be collected, modeled, analyzed, and interpreted. Introducing cutting-edge methods, the book challenges long-held assumptions and encourages a new way of thinking about football analysis. The book seeks to define the role of positional data in football match analysis by exploring topics such as the following: What is positional data analysis, and how did it emerge from conventional match analysis? How can positional data be collected, and which technologies can be used? What key performance indicators based on positional data should be used? How can traditional match analysis be complemented by using positional data and advanced KPIs? How can these new methods evolve in the future? Based on data collected from active leagues and fully revised for the new second edition, the text now also examines data collection in relation to other sports, how a data-driven approach in decision-making is achieved by professional teams, the potential of the new methods of data collection, and how they could evolve in the future. Accessibly written, packed full of examples from elite football, and supplemented with expert interviews, Data Analytics in Football is a thought-provoking, rigorously evidence-based guide to the use of data analytics in football performance analysis. As such, it is a vital resource for any student, researcher, or coach interested in performance analysis and skill acquisition, or anyone interested in football more generally.
Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more