Chapter 1 Soccer analytics: the way ahead
Chapter 2 Getting started with R
Chapter 3 Using R to harvest and process soccer data
Chapter 4 Match data and league tables
Chapter 5 Predicting end-of-season league position
Chapter 6 Predicting soccer match outcomes
Chapter 7 Betting strategies
Chapter 8 Who are the key players? Using passing networks to analyse match play
Chapter 9 Which is the best team? Ranking systems in soccer
Chapter 10 Using linear regression to analyse match performance data
Chapter 11 Successful data analytics
Biography
Clive Beggs is Emeritus Professor of Applied Physiology in the Carnegie School of Sport at Leeds Beckett University in the UK. He is both a physiologist and a bio-engineer, who has worked for many years with leading research teams around the world on a wide variety of medical and sport related projects – publishing many scientific papers in both fields. With a background in mathematical modelling of clinical and biological systems, he also has expertise in data analysis and machine learning, which he regularly uses in his sport performance work. Clive is both an amateur runner and soccer fan, and it is his life-long interest in sport and mathematics that has prompted him to write this book.
"As someone who shares with the author a lifelong interest in sports in general and soccer in particular I fully agree with the authors’ premise of writing this book. The organization of chapters around picking up specific skills is useful. The provision of R scripts and data (through a Github page associated with the book) is
welcome and will encourage readers to delve into their own analytics. I believe that this book overall successfully covers its targeted niche."
~Alexander Aue, Journal of the American Statistical Association
