Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports, 2nd Edition
- Length: 608 pages
- Edition: 2
- Language: English
- Publisher: Princeton University Press
- Publication Date: 2022-02-22
- ISBN-10: 0691177627
- ISBN-13: 9780691177625
- Sales Rank: #61026 (See Top 100 Books)
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.
Cover Contents Preface Acknowledgments Abbreviations PART I. BASEBALL 1. Baseball’s Pythagorean Theorem 2. Who Had a Better Year: Mike Trout or Kris Bryant? 3. Evaluating Hitters by Linear Weights 4. Evaluating Hitters by Monte Carlo Simulation 5. Evaluating Baseball Pitchers, Forecasting Future Pitcher Performance, and an Introduction to Statcast 6. Baseball Decision Making 7. Evaluating Fielders 8. Win Probability Added (WPA) 9. Wins Above Replacement (WAR) and Player Salaries 10. Park Factors 11. Streakiness in Sports 12. The Platoon Effect 13. Was Tony Perez a Great Clutch Hitter? 14. Pitch Count, Pitcher Effectiveness, and PITCHf/x Data 15. Would Ted Williams Hit .406 today? 16. Was Joe DiMaggio’s 56-Game Hitting Streak the Greatest Sports Record of All Time? 17. Projecting Major League Performance PART II. FOOTBALL 18. What Makes NFL Teams Win? 19. Who’s Better: Brady or Rodgers? 20. Football States and Values 21. Football Decision Making 101 22. If Passing Is Better than Running, Why Don’t Teams Always Pass? 23. Should We Go for a One-Point or a Two-Point Conversion? 24. To Give Up the Ball Is Better than to Receive: The Case of College Football Overtime 25. Has the NFL Finally Gotten the OT Rules Right? 26. How Valuable Are NFL Draft Picks? 27. Player Tracking Data in the NFL PART. III. BASKET BALL 28. Basketball Statistics 101: The Four Factor Model 29. Linear Weights for Evaluating NBA Players 30. Adjusted +/- Player Ratings 31. ESPN RPM and FiveThirtyEight RAPTOR Ratings 32. NBA Lineup Analysis 33. Analyzing Team and Individual Matchups 34. NBA Salaries and the Value of a Draft Pick 35. Are NBA Officials Prejudiced? 36. Pick-n-Rolling to Win, the Death of Post Ups and Isos 37. SportVU, Second Spectrum, and the Spatial Basketball Data Revolution 38. In-Game Basketball Decision Making PART IV. OTHER SPORTS 39. Soccer Analytics 40. Hockey Analytics 41. Volleyball Analytics 42. Golf Analytics 43. Analytics and Cyber Athletes: The Era of e-Sports PART V. SPORTS GAMBLING 44. Sports Gambling 101 45. Freakonomics Meets the Bookmaker 46. Rating Sports Teams 47. From Point Ratings to Probabilities 48. The NCAA Evaluation Tool (NET) 49. Optimal Money Management: The Kelley Growth Criterion 50. Calcuttas PART VI. METHODS AND MISCELLANEOUS 51. How to Work with Data Sources: Collecting and Visualizing Data 52. Assessing Players with Limited Data: The Bayesian Approach 53. Finding Latent Patterns through Matrix Factorization 54. Network Analysis in Sports 55. Elo Ratings 56. Comparing Players from Different Eras 57. Does Fatigue Make Cowards of Us All? The Case of NBA Back-to-Back Games and NFL Bye Weeks 58. The College Football Playoff 59. Quantifying Sports Collapses 60. Daily Fantasy Sports Bibliography Index
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