
Analytic Methods in Sports
Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports
Thomas A. Severini(Author)
Chapman & Hall/CRC (Publisher)
3rd Edition
Will be published approx. on 30. January 2026
Book
Paperback/Softback
460 pages
978-1-032-83600-3 (ISBN)
Description
One of the greatest changes in sports analytics in the past 25 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, Third Edition, provides a concise, yet thorough, introduction to the analytic and statistical methods that are useful in studying sports.
Key Features:
New to the third edition is a chapter on applying mathematical and statistical methods to the analysis of daily fantasy sports
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
Discusses several more advanced methods, including logistic regression models, random forests, regression models with random effects, spline methods, principal components analysis, multidimensional scaling, quantile regression, and more
Illustrates the methods using real data drawn from a wide variety of sports
Offers many of the data sets on the author's website, enabling you to replicate the analyses or conduct related analyses
R code is included for all calculations
Exercises are given for each chapter, to enable use for courses and self-study
This popular textbook is primarily designed to be used to teach an introductory course on statistics to undergraduate students using sports examples. Its practical focus on application rather than theory ensures students develop immediately applicable skills for the rapidly expanding field of sports analytics. It is a perfect reference for readers comfortable with mathematics seeking to enter the growing field of sports analytics without prior statistical training. Its concise yet thorough approach makes it equally suitable for self-study by sports enthusiasts, coaches, and industry professionals looking to leverage the power of data-driven decision making in competitive environments.
Key Features:
New to the third edition is a chapter on applying mathematical and statistical methods to the analysis of daily fantasy sports
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
Discusses several more advanced methods, including logistic regression models, random forests, regression models with random effects, spline methods, principal components analysis, multidimensional scaling, quantile regression, and more
Illustrates the methods using real data drawn from a wide variety of sports
Offers many of the data sets on the author's website, enabling you to replicate the analyses or conduct related analyses
R code is included for all calculations
Exercises are given for each chapter, to enable use for courses and self-study
This popular textbook is primarily designed to be used to teach an introductory course on statistics to undergraduate students using sports examples. Its practical focus on application rather than theory ensures students develop immediately applicable skills for the rapidly expanding field of sports analytics. It is a perfect reference for readers comfortable with mathematics seeking to enter the growing field of sports analytics without prior statistical training. Its concise yet thorough approach makes it equally suitable for self-study by sports enthusiasts, coaches, and industry professionals looking to leverage the power of data-driven decision making in competitive environments.
More details
Edition
3rd edition
Language
English
Place of publication
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Academic, Postgraduate, Professional Reference, and Undergraduate Advanced
Illustrations
81 s/w Tabellen, 101 s/w Abbildungen, 101 s/w Zeichnungen
81 Tables, black and white; 101 Line drawings, black and white; 101 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 26 mm
Weight
726 gr
ISBN-13
978-1-032-83600-3 (9781032836003)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Thomas A. Severini
Analytic Methods in Sports
Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports
Book
approx. 01/2026
3rd Edition
Chapman & Hall/CRC
€254.50
Not yet published

Thomas A. Severini
Analytic Methods in Sports
Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports
E-Book
01/2026
3rd Edition
Chapman and Hall
€82.99
Available for download

Thomas A. Severini
Analytic Methods in Sports
Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports
E-Book
01/2026
3rd Edition
Chapman and Hall
€82.99
Available for download
Previous edition

Thomas A. Severini
Analytic Methods in Sports
Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports
Book
03/2020
2nd Edition
Chapman & Hall/CRC
€96.60
Available immediately
Person
Thomas A. Severini is a Professor of Statistics and Data Science at Northwestern University and a fellow of the American Statistical Association and the Institute of Mathematical Statistics. He earned his PhD in Statistics from the University of Chicago.
Content
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. Further Topics in Regression Analysis. 9. Some Advanced Methods. 10. Applying Analytic Methods to Daily Fantasy Sports.