| ISBN13: | 9781032357584 |
| ISBN10: | 1032357584 |
| Binding: | Paperback |
| No. of pages: | 396 pages |
| Size: | 234x156 mm |
| Weight: | 453 g |
| Language: | English |
| Illustrations: | 63 Illustrations, black & white; 63 Line drawings, black & white; 21 Tables, black & white |
| 737 |
Probability and mathematical statistics
Medicine in general
Orthopedics, diseases of the limbs
Biomechanincs, Sports medicine
Ball games, racket games
Probability and mathematical statistics (charity campaign)
Medicine in general (charity campaign)
Orthopedics, diseases of the limbs (charity campaign)
Biomechanincs, Sports medicine (charity campaign)
Ball games, racket games (charity campaign)
Soccer Analytics
GBP 49.99
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Not in stock at Prospero.
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.
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.
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.
