书目详细信息
： Mathletics :
书目信息 机读格式(MARC)
| ISBN： | 9780691177625 |
|---|---|
| ISBN： | 0691177627 |
| ISBN： | 9780691189291 |
| ISBN： | 0691189293 |
| 编目源： | UKMGB UKMGB OCLCF OCLCO UKMGB PIT COD OCLCO BKL OVV |
| 个人名称： | Winston, Wayne L., |
| 题名： | Mathletics : how gamblers, managers, and fans use mathematics in sports. |
| 版本说明： | 2nd edition / |
| 索书号： | G80-32/W631E |
| 载体形态： | xxi, 584 pages : illustrations (black and white) ; 24 cm |
| 一般附注： | Previous edition: published as by Wayne Winston. 2009. |
| 书目附注： | Includes bibliographical references (pages 569-578) and index. |
| 格式化内容附注： | Preface -- Acknowledgments -- Abbreviations -- Part 1: 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 2: 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 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 3: Basketball -- 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 4: 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 5: 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 6: 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. |