Analytic Methods in Sports : Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports book cover
2nd Edition

Analytic Methods in Sports
Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports

ISBN 9780367469382
Published March 31, 2020 by Chapman and Hall/CRC
372 Pages 82 B/W Illustrations

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Book Description

One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, Second Edition provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports.

The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from standard statistical analyses. The book integrates a large number of motivating sports examples throughout and offers guidance on computation and suggestions for further reading in each chapter.


  • Covers numerous statistical procedures for analyzing data based on sports results
  • Presents fundamental methods for describing and summarizing data
  • Describes aspects of probability theory and basic statistical concepts that are necessary to understand and deal with the randomness inherent in sports data
  • Explains the statistical reasoning underlying the methods
  • Illustrates the methods using real data drawn from a wide variety of sports
  • Offers many of the datasets on the author’s website, enabling you to replicate the analyses or conduct related analyses

New to the Second Edition

  • R code included for all calculations
  • A new chapter discussing several more advanced methods, such as binary response models, random effects, multilevel models, spline methods, and principal components analysis, and more
  • Exercises added to the end of each chapter, to enable use for courses and self-study
  • Full solutions manual available to course instructors.

Table of Contents

1 Introduction
2 Describing and Summarizing Sports Data
3 Probability
4 Statistical Methods
5 Using Correlation to Detect Statistical Relationships
6 Modeling Relationships Using Linear Regression
7 Regression Models with Several Predictor Variables
8 Some Advanced Methods

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Thomas A. Severini is currently professor of statistics at Northwestern University. His research areas include likelihood inference, nonparametric and semiparametric methods, and applications to econometrics. He is also the author of Likelihood Methods in Statistics, Elements of Distribution Theory, and Introduction to Statistical Methods for Financial Models. He received his PhD in statistics from the University of Chicago. He is a fellow of the American Statistical Association.


Praise For First Edition

"Professor Severini’s stated aim for this book is ‘to provide a concise but thorough introduction to the analytic and statistical methods that are useful in studying sport’. Overall, the book scores many points in this regard. …
There is much to like throughout this book. It is not long (approximately 250 pages) and assumes almost no background in mathematics apart from some basics of algebra. However, it is dense with quality examples of the use of statistical methods. Those considering adopting this book as a text for an introductory statistics course will be encouraged by the fact that the selection and order of topics coincides with those from many introductory statistics texts. The book is also rich in data with over 40 different datasets the vast majority of which are multivariate and all of which are publicly available at the author’s website: Each chapter finishes with a set of example calculations and a list of further readings on the topics covered in that chapter. …
In summary, Severini’s book on statistical and analytic methods for sports is a winning addition to the literature on the analysis of sport data. It scores well on its goal of being an introduction to statistical methods for such data. The content will suit the intended audience and with some augmentation the book would be quite appropriate to use in teaching a first course on statistical methods that takes sport as focus or motivation."
Micheal E. Schuckers, St. Lawrence University, in the Australian & New Zealand Journal of Statistics, September 2017

"… this book is ideally suited to someone who has a keen interest in various sports and mathematics and would like to take their interest to a deeper, more quantitative level. I could also imagine using this book as a supplementary resource in an introductory statistics courses given its trove of interesting examples. … the book is extremely well written and includes a multitude of tools for someone interested in quantitative methods in sports. I would highly recommend the book for the audiences described above and, in particular, someone teaching introductory statistics who needs motivating examples for his/her course(s)."
The American Statistician, August 2015

"There is much to like here. The book provides an overview of statistical methods and gives applications of these methods for a wide variety of sports. … the book is a nice complement to other introductory statistics sports texts and could be used in teaching a lively introduction to statistics using sports."
Significance, April 2015

"Students and interested sports fans will find Analytic Methods in Sports very useful for learning the probability and statistics they need to begin analyzing sports data. The author provides the intuition behind the analytic methods discussed, avoiding overly technical explanations, and presents many interesting and thought-provoking examples that help to illuminate the material."
David Rosenthal, Associate Professor of Mathematics, St. John’s University, and co-author of A Readable Introduction to Real Mathematics

"A comprehensive and up-to-date look at the primary tools and techniques in sports analytics, covering every major sport, Analytic Methods in Sports condenses what took me five years to learn into 200 pages. It’s both easy to read and complete with mathematic rigor. If you’re serious about getting into analytics in any sport at any level, this needs to be on your bookshelf."
Brian Burke, Founder of Advanced Football Analytics and NFL Team Consultant

"Many people enter the rapidly growing sports analytics industry without the adequate tools to perform analysis. In his book, Severini details the fundamental statistical skill set needed to succeed with examples from every major sport. It will appeal to readers just introduced to the field of statistics as well as the more experienced looking to further develop their ability to manage and interpret data. A worthy addition to any analyst’s library."
Keith Goldner, Chief Analyst, numberFire

Praise for Second Edition

"This is a timely book. Anyone interested in analysing sport beyond platitudes should read it: what is information, what are the facts, and how do you present those in an accessible manner? These questions are central to this volume. Focus of the book is on ‘how do we get information from data’ as opposed to ‘how do I use sport as an example in statistics’. To that end, many examples are provided, and computational help is given both using Excel and R. Not only single variable analyses are presented, but also multivariate analyses. The material covered ensures that the reader is well prepared to dive deeper into data science. I like the last chapter on advanced methods a lot: it covers modern techniques as cross validation, random forests, and splines. This will definitely help us to understand sports phenomena better, but the techniques covered in this book have a much wider applicability as well. As a bonus, each chapter has a problem set. This book is an excellent resource for both researchers and students!"
- Ruud H. Koning, University of Groningen

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