Book in Focus
Statistics Meets Sports"/>

09th May 2023

Book in Focus
Statistics Meets Sports

What We Can Learn from Sports Data

Edited by Yves Dominicy and Christophe Ley


This book is about sports analytics, which has lately become an increasingly popular domain. The world of sports has been revolutionized over the past few decades thanks to profound data analysis techniques. We provide the reader with an overview of the recent developments in the most popular sports.

The objective is to present the field of sports analytics to two very distinct target groups: on the one hand the academics (mainly statisticians) in order to raise their interest in these growing fields, and on the other hand sports fans who, even without advanced mathematical knowledge, will be able to understand and appreciate the data analysis part and gain new insights into their favourite sports.

The book thus offers a unique perspective on these hot topics, by combining sports analytics, data visualization and advanced statistical procedures to extract new findings from sports data such as improved rankings or prediction methods. The book is likely to have a deep impact on the two target groups and will contribute both to research and practice.

The reader has to keep in mind that the goal of this book is not to be an introduction to sports analytics, but rather a book where the sports enthusiastic gets a glimpse of the statistical part of their favourite sport and to raise interest among statisticians for this research avenue.


The world of sports is currently undergoing a fundamental change thanks to the upcoming trend of sports analytics. Recent advances in data collection techniques have enabled gathering large, sometimes even massive, amounts of data in all aspects of sports, such as for instance tactics, technique, health complaints and injuries, spatiotemporal whereabouts (e.g., tracking data from GPS), but also marketing and betting. Data is by now regularly collected in almost every sport, ranging from traditional Olympic disciplines to professional football, basketball, tennis, and handball, to name but a few. Moreover, massive data from individual recreational athletes such as runners or cyclists is available. It is by far not only professional and commercially successful sports clubs that aim to analyse data, even recreational athletes and amateur clubs make use of a variety of sensors to monitor their training and performances.

This global rush towards using advanced statistics and machine learning methods in sports is due in large parts to the success of the Oakland Athletics baseball team in the 2002 season. Prior to that season, they hired new players in an atypical way: namely, by not relying on scouts' experience but rather on sabermetrics, the technical term for empirical/statistical analysis of baseball. This particular story has been written up in the famous book Moneyball in 2003, which became a movie in 2011. The success of the Oakland Athletics team inspired other teams in baseball, and soon after in several other sports. Since then, sports analytics as a field has seen a phenomenal development, having led inter alia to the developments of new journals, such as the Journal of Sports Analytics whose first edition appeared in 2015.

The present book inscribes itself in this context and aims to further contribute to this stimulating research area thanks to its unique feature of targeting academics and sports fans.


This book is the follow-up of Science Meets Sports: When Statistics Are More Than Numbers and hence we consider here sports not described in our first book. It offers, in particular, a deep dive into sports like hockey, American football and swimming, plus it treats issues such as gender differences in sports, talent discovery, or tournament design, and tackles new aspects of football and tennis. Every sport aficionado should find their interest in this book.

The book starts with a chapter focussing on female athletes and the need for a differentiated analysis of both sexes (Chapter 1 by Zech and Hamacher), then continues with sports not treated in our first book such as hockey (Chapter 2 by David, Swartz, Schulte, Higuera and Javan), American football (Chapter 3 by Pelechrinis), and swimming (Chapter 4 by Leroy and Pla), before returning on other facets of tennis (Chapter 5 by Maričić and Jeremic, and Chapters 6 and 7 by Barnett and Ejov). Next the book considers topics of interest for many sports such as the role of tournament design in sporting success (Chapter 8 by Csato), talent identification via the plus-minus ratings (Chapter 9 by Hvattum, Kriegl and Čulík), uncertainty in competitive balance (Chapter 10 by Karlis, Ntzoufras and Manasis), risk profile identification and injury prediction (Chapter 11 by De Michelis Mendonça, Rezende Souza and Teixeira Fonseca), and finally rating systems and the predictability of World Team Championships (Chapter 12 by Stefani).

Yves Dominicy is a Data Scientist in the domain of credit risk in the banking sector in Luxembourg. He formerly worked as a Research Fellow of the Belgian National Fund for Scientific Research and Lecturer at the Solvay Brussels School of Economics and Management of the Université libre de Bruxelles, Belgium, where he received his PhD in Econometrics. He is Secretary of the Luxembourg Statistical Society, and the author of articles in journals such as Journal of Econometrics, International Statistical Review, and Journal of Experimental Social Psychology.

Christophe Ley is Associate Professor of Applied Statistics at the Department of Mathematics of the University of Luxembourg. He is also President of the European Association for Advanced Statistics Courses and of the Luxembourg Statistical Society, and initiator of the international network “Sports - Training and Research in Data Science Methods for Analytics and Injury Prevention Group”. He is a recipient of the Marie-Jeanne Laurent-Duhamel Prize of the Société Française de Statistique and associate editor for the journals Annals of the Institute of Statistical Mathematics, Econometrics and Statistics, and Statistique et Société.

Statistics Meets Sports: What We Can Learn from Sports Data is available now at a 25% discount. Enter code PROMO25 to redeem.

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