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Mathletics : how gamblers, managers, and fans use mathematics in sports / Wayne L. Winston, Scott Nestler, and Konstantinos Pelechrinis.

By: Winston, Wayne L, 1950- [author.]Contributor(s): Nestler, Scott, 1957- [author.] | Pelechrinis, Konstantinos, 1983- [author.]Material type: TextTextPublisher: Princeton : Princeton University Press, 2022Edition: 2nd EditionDescription: 1 online resource (xxi, 584 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9780691189291 electronic bk.; 0691189293 electronic bk.; 9780691177625; 0691177627Subject(s): Sports -- MathematicsDDC classification: 796.0151 Online access: Open e-book
Contents:
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.
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Includes bibliographical references (pages 569-578) and index.

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.

Electronic reproduction. [New York]: JSTOR, [2024]. Available as JPEG images or in PDF format. Description based on contents viewed 24 June 2024.

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