Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports, Second Edition

Review
"Sports fans will learn much from probability theory and statistical models as they abandon empty clichés (time to throw momentum out of the informed fan's lexicon) and confront institutionalized injustices (such as those built into the protocols for selecting a national champion in college football and for seeding the NCAA's basketball tournament). A rare fusion of sports enthusiasm and numerical acumen." ― Booklist
"Who is Wayne Winston? Maybe we should begin by telling you who he is not. He is not some barstool fan or uninformed sportswriter who fuels his opinions with information gleaned from SportsCenter highlights or newspaper box scores. He is a professor of decision sciences at Indiana University's Kelley School of Business, and until this year was the statistical guru for the Dallas Mavericks. He is author of the book Mathletics, which explains what statistics really tell us about sports."---Ken Berger, CBSSports.com
"[A] terrific read for anyone trying to model markets statistically and make trading decisions based on statistical data. . . . Reading Winston's book is a mind-opening experience."---Brenda Jubin, Reading the Markets blog
How to use math to improve performance and predict outcomes in professional sports
Mathletics reveals the mathematical methods top coaches and managers use to evaluate players and improve team performance, and gives math enthusiasts the practical skills they need to enhance their understanding and enjoyment of their favorite sports―and maybe even gain the outside edge to winning bets. This second edition features new data, new players and teams, and new chapters on soccer, e-sports, golf, volleyball, gambling Calcuttas, analysis of camera data, Bayesian inference, ridge regression, and other statistical techniques. After reading Mathletics, you will understand why baseball teams should almost never bunt; why football overtime systems are unfair; why points, rebounds, and assists aren’t enough to determine who’s the NBA’s best player; and more.