Game Theory, Machine Learning, And Production In Sports: The Fair-credit Baseball Statistics - Rilegato
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In this groundbreaking book, economist and game theorist Michael McBride presents an innovative answer to this question for the sport of baseball: 'How is individual performance fairly measured when success depends on teamwork?' The answer is ― the Fair-Credit Baseball statistics.Drawing on the Nobel Prize-winning Shapley Value from coalitional game theory, McBride creates two revolutionary measures of offensive performance: Shapley Run Credits (SRC) and Offensive Shapley Win Credits (OSWC). Unlike traditional baseball statistics, these new measures satisfy mathematical fairness axioms, making them the fairest measures of individual credit in the sport.McBride combines this theoretical foundation with cutting-edge machine learning to analyse over a century of Major League Baseball data, producing the most accurate measures of offensive performance in baseball history. The result is a sophisticated yet intuitive statistical framework that finally gives players the credit they truly deserve for actual results ― not projected or average performance.Written for academic researchers, sports analysts, and baseball enthusiasts alike, this book successfully bridges complex mathematical theory with practical application. It offers technical rigor for professionals while remaining engaging and accessible for anyone passionate about understanding what really happens on the baseball diamond.
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GAME THEORY MACHINE LEARNING AND PRODUCTION IN SPORTS
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Game Theory, Machine Learning, And Production In Sports: The Fair-credit Baseball Statistics
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World Scientific Publishing Co Pte Ltd, 2026
ISBN 10: 9819821843
ISBN 13: 9789819821846
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Game Theory, Machine Learning, And Production In Sports: The Fair-credit Baseball Statistics
Editore:
World Scientific Publishing Co Pte Ltd, 2026
ISBN 10: 9819821843
ISBN 13: 9789819821846
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GAME THEORY MACHINE LEARNING AND PRODUCTION IN SPORTS
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Game Theory, Machine Learning, And Production In Sports: The Fair-credit Baseball Statistics
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World Scientific Publishing Co Pte Ltd, SG, 2026
ISBN 10: 9819821843
ISBN 13: 9789819821846
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Hardback. Condizione: New. In this groundbreaking book, economist and game theorist Michael McBride presents an innovative answer to this question for the sport of baseball: "How is individual performance fairly measured when success depends on teamwork?" The answer is - the Fair-Credit Baseball statistics.Drawing on the Nobel Prize-winning Shapley Value from coalitional game theory, McBride creates two revolutionary measures of offensive performance: Shapley Run Credits (SRC) and Offensive Shapley Win Credits (OSWC). Unlike traditional baseball statistics, these new measures satisfy mathematical fairness axioms, making them the fairest measures of individual credit in the sport.McBride combines this theoretical foundation with cutting-edge machine learning to analyse over a century of Major League Baseball data, producing the most accurate measures of offensive performance in baseball history. The result is a sophisticated yet intuitive statistical framework that finally gives players the credit they truly deserve for actual results - not projected or average performance.Written for academic researchers, sports analysts, and baseball enthusiasts alike, this book successfully bridges complex mathematical theory with practical application. It offers technical rigor for professionals while remaining engaging and accessible for anyone passionate about understanding what really happens on the baseball diamond. Codice articolo LU-9789819821846
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Game Theory, Machine Learning, And Production In Sports: The Fair-credit Baseball Statistics
Editore:
World Scientific Publishing Co Pte Ltd, 2026
ISBN 10: 9819821843
ISBN 13: 9789819821846
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Hardcover. Condizione: Brand New. 250 pages. 9.00x2.00x6.00 inches. In Stock. Codice articolo x-9819821843
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GAME THEORY, MACHINE LEARNING, AND PRODUCTION IN SPORTS
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Buch. Condizione: Neu. GAME THEORY, MACHINE LEARNING, AND PRODUCTION IN SPORTS | Mcbride Michael | Buch | Englisch | 2026 | World Scientific | EAN 9789819821846 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Codice articolo 134649535
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Game Theory, Machine Learning, And Production In Sports: The Fair-credit Baseball Statistics
Editore:
World Scientific Publishing Co Pte Ltd, SG, 2026
ISBN 10: 9819821843
ISBN 13: 9789819821846
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Da: Rarewaves.com UK, London, Regno Unito
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Hardback. Condizione: New. In this groundbreaking book, economist and game theorist Michael McBride presents an innovative answer to this question for the sport of baseball: "How is individual performance fairly measured when success depends on teamwork?" The answer is - the Fair-Credit Baseball statistics.Drawing on the Nobel Prize-winning Shapley Value from coalitional game theory, McBride creates two revolutionary measures of offensive performance: Shapley Run Credits (SRC) and Offensive Shapley Win Credits (OSWC). Unlike traditional baseball statistics, these new measures satisfy mathematical fairness axioms, making them the fairest measures of individual credit in the sport.McBride combines this theoretical foundation with cutting-edge machine learning to analyse over a century of Major League Baseball data, producing the most accurate measures of offensive performance in baseball history. The result is a sophisticated yet intuitive statistical framework that finally gives players the credit they truly deserve for actual results - not projected or average performance.Written for academic researchers, sports analysts, and baseball enthusiasts alike, this book successfully bridges complex mathematical theory with practical application. It offers technical rigor for professionals while remaining engaging and accessible for anyone passionate about understanding what really happens on the baseball diamond. Codice articolo LU-9789819821846
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