Soccer Analytics
Chapman & Hall/CRC (Verlag)
978-1-032-35758-4 (ISBN)
Sports analytics is on the rise, with top soccer clubs, bookmakers, and broadcasters all employing statisticians and data scientists to gain an edge over their competitors.
Many popular books have been written exploring the mathematics of soccer. However, few supply details on how soccer data can be analysed in real-life. The book addresses this issue via a practical route one approach designed to show readers how to successfully tackle a range of soccer related problems using the easy-to-learn computer language R. Through a series of easy-to-follow examples, the book explains how R can be used to:
Download and edit soccer data
Produce graphics and statistics
Predict match outcomes and final league positions
Formulate betting strategies
Rank teams
Construct passing networks
Assess match play
Soccer Analytics: An Introduction Using R is a comprehensive introduction to soccer analytics aimed at all those interested in analysing soccer data, be they fans, gamblers, coaches, sports scientists, or data scientists and statisticians wishing to pursue a career in professional soccer. It aims to equip the reader with the knowledge and skills required to confidently analyse soccer data using R, all in a few easy lessons.
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.
1. Soccer analytics: the way ahead. 2. Getting started with R. 3. Using R to harvest and process soccer data. 4. Match data and league tables. 5. Predicting end-of-season league position. 6. Predicting soccer match outcomes. 7. Betting strategies. 8. Who are the key players? Using passing networks to analyse match play. 9. Which is the best team? Ranking systems in soccer. 10. Using linear regression to analyse match performance data. 11. Successful data analytics.
| Erscheinungsdatum | 05.04.2024 |
|---|---|
| Reihe/Serie | Chapman & Hall/CRC Data Science Series |
| Zusatzinfo | 21 Tables, black and white; 63 Line drawings, black and white; 63 Illustrations, black and white |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 453 g |
| Themenwelt | Sport ► Ballsport ► Fußball |
| Mathematik / Informatik ► Mathematik | |
| Medizin / Pharmazie ► Allgemeines / Lexika | |
| Medizinische Fachgebiete ► Chirurgie ► Unfallchirurgie / Orthopädie | |
| ISBN-10 | 1-032-35758-4 / 1032357584 |
| ISBN-13 | 978-1-032-35758-4 / 9781032357584 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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