Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports, Second Edition
fev. de 2022 · Princeton University Press
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Sobre este e-book
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.
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.
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Sobre o autor
Wayne L. Winston is the John and Esther Reese Professor of Decision Sciences at Indiana University’s Kelley School of Business. Scott Nestler is associate teaching professor at the University of Notre Dame’s Mendoza College of Business. Konstantinos Pelechrinis is associate professor at the University of Pittsburgh’s School of Computing and Information.
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