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.

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.

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. This up-to-the-minute reference will help you master all three facets of sports analytics — and use it to win! Sports Analytics and Data Science is the most accessible and practical guide to sports analytics for everyone who cares about winning and everyone who is interested in data science. You’ll discover how successful sports analytics blends business and sports savvy, modern information technology, and sophisticated modeling techniques. You’ll master the discipline through realistic sports vignettes and intuitive data visualizations–not complex math. Every chapter focuses on one key sports analytics application. Miller guides you through assessing players and teams, predicting scores and making game-day decisions, crafting brands and marketing messages, increasing revenue and profitability, and much more. Step by step, you’ll learn how analysts transform raw data and analytical models into wins: both on the field and in any sports business.

Match analysis in soccer has become more and more important in recent years. Nowadays, no professional soccer club plays a single match without having analyzed their own and their opponents’ matches to find the best possible match plan and maximize their success. In this book, Ian M. Franks and Mike Hughes explore soccer analyses and use the results to develop realistic, progressive practices to improve the performance of the individual players and the team. Research from human decision making and motor skill acquisition is directly applied to the coaching process and technical and tactical practices are designed to accommodate these findings. Not only is the players’ behavior during practice and matches analyzed but the coaches’ as well. This helps evaluate different coaching practices to find your ideal coaching style. Any coach reading this book will find help in developing and improving their coaching. Anyone who wishes to delve more into the science of soccer analysis will find ample material as well as a comprehensive bibliography to better understand the science of soccer!

Match analysis is a performance-diagnostic procedure, which can be used to carry out systematic gaming analysis during competition and training. The analysis of team and racket sports, whether in competition, for opponent preparation (match plan), follow-up, or training is nowadays indispensable in many sports games at different levels. This analysis nevertheless presents many open questions and problem areas: Which data should be used? Who manages the data? Who provides whom with which information? How is this information presented, digested, and applied? The more complex and anonymous the data management is, the more commercial, expensive, and uncontrollable information management and provision becomes. Match Analysis: How to Use Data in Professional Sport is the first book to examine this topic through three types of data sets; video, event, and position data and show how to interpret this data and apply the findings for better team and individual sport performance. This innovative new volume is key reading for researchers, students, and practitioners alike in the fields of Coaching, Performance Analysis, Sport Management, and related specific sport disciplines.

For many years, sports rights owners have had an ‘if you build it, they will come’ attitude, suggesting they take their fans for granted. Combined with advances in broadcasting quality, digital marketing, and social media, this has resulted in diminishing attendances and participation levels. The use of CRM (Customer Relationship Management), BI (Business Intelligence) and Data Analytics has therefore become integral to doing business in sports, emulating the approach used by brands such as Amazon, Netflix, and Spotify. Technology has made the world a smaller place; clubs and teams can now connect with their fans anywhere in the world, allowing them to grow their marketplace, but they operate in an ‘attention economy’ where there’s too much choice and engagement is key. This book sets out to share the processes and principles the sports industry uses to capitalise on the natural loyalty it creates. Case studies and commentary from around the world are used to demonstrate some of the practices implemented by the world’s leading sports brands including clubs Arsenal and the San Antonio Spurs. the governing bodies of UEFA and Special Olympics International, and the MLS and NHL. With a focus on our unique challenges coupled with the opportunities the use of data creates, this book is essential reading for professionals within the sports industry.

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

"Beautifully illustrated and sharply written, SprawlBall is both a celebration and a critique of the 3-point shot. If you want to understand how the modern NBA came to be, you'll need to read this book." --Nate Silver, editor of fivethirtyeight.com From the leading expert in the exploding field of basketball analytics, a stunning infographic decoding of the modern NBA: who shoots where, and how. The field of basketball analytics has leaped to overdrive thanks to Kirk Goldsberry, whose visual maps of players, teams, and positions have helped teams understand who really is the most valuable player at any position. SprawlBall combines stunning visuals, in-depth analysis, fun, behind-the-scenes stories and gee-whiz facts to chart a modern revolution. From the introduction of the 3-point line to today, the game has changed drastically . . . Now, players like Steph Curry and Draymond Green are leading the charge. In chapters like "The Geography of the NBA," "The Interior Minister (Lebron James)," "The Evolution of Steph Curry," and "The Investor (James Harden)," Goldsberry explains why today's on-court product--with its emphasis on shooting, passing, and spacing--has never been prettier or more democratic. And it's never been more popular. For fans of Bill Simmons and FreeDarko, SprawlBall is a bold new vision of the game, presenting an innovative, cutting-edge look at the sport based on the latest research, as well as a visual and infographic feast for fans.

This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018. The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individual sports cycling and martial arts. In addition, four challenge papers are included, reporting on how to predict pass receivers in soccer.

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