Seminar

Soccer Analytics: Insights into prediction and performance evaluation

  • 18.00 - 19.30
  • 30 Apr 2024
  • Carnegie School of Sport Building, Lecture Theatre 1, Church Wood Avenue, Leeds, LS6 5LF
Soccer Analytics: Insights into prediction and performance evaluation
Book launch: "Soccer Analytics: An Introduction Using R" by Emeritus Professor Clive Beggs.

Data analytics is increasingly playing an important role in professional football, with top clubs like Liverpool and Manchester City hiring PhD physicists and data scientists to analyse performance data and assist clubs in informed decision making.

To celebrate publication of his new book, "Soccer Analytics: An Introduction Using R", Professor Clive Beggs is giving a presentation on how data science can help in making predictions and analysing complex data in football. This lecture is open to all those with an interest in data analysis in sport, and highlights some of the work that Clive has done with colleagues in the Carnegie School of Sport.

Clive Beggs

Clive Beggs is Emeritus Professor of Applied Physiology in the Carnegie School of Sport at Leeds Beckett University. He is a PhD bio-engineer and a physiologist, 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 on infection control, neurological disease, vascular physiology, and sport analytics.

With a background in mathematical modelling of clinical and biological systems, Clive regularly uses his expertise in data analytics and machine learning in his sport related work. Clive’s life-long interest in sport, exercise and mathematics prompted him to write Soccer Analytics: An Introduction Using R, which was recently published by Chapman & Hall (CRC Press). This book is a comprehensive introduction to soccer analytics, aimed at all those interested learning how to analyse soccer data.

About the book

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

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