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Sprache: Englisch
Verlag: Taylor and Francis Ltd, GB, 2025
ISBN 10: 1032030631 ISBN 13: 9781032030630
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In den WarenkorbPaperback. Zustand: New. Predictive Modelling for Football Analytics discusses the most well-known models and the main computational tools for the football analytics domain. It further introduces the footBayes R package that accompanies the reader through all the examples proposed in the book. It aims to be both a practical guide and a theoretical foundation for students, data scientists, sports analysts, and football professionals who wish to understand and apply predictive modelling in a football context.Key FeaturesDiscusses various modelling strategies and predictive tools related to football analyticsIntroduces algorithms and computational tools to check the models, make predictions, and visualize the final resultsShowcases some guided examples through the use of the footBayes R package available on CRANWalks the reader through the full pipeline: from data collection and preprocessing, through exploratory analysis and feature engineering, to advanced modelling techniques and evaluationBridges the gap between raw football data and actionable insightsThis text is primarily for senior undergraduates, graduate students, and academic researchers in the fields of mathematics, statistics, and computer science willing to learn about the football analytics domain. Although technical in nature, the book is designed to be accessible to readers with a background in statistics, programming, or a strong interest in sports analytics. It is well-suited for use in academic courses on sports analytics, data science projects, or professional development within football clubs, agencies, and media organizations.
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Sprache: Englisch
Verlag: Taylor and Francis Ltd, GB, 2025
ISBN 10: 1032030631 ISBN 13: 9781032030630
Anbieter: Rarewaves USA, OSWEGO, IL, USA
Paperback. Zustand: New. Predictive Modelling for Football Analytics discusses the most well-known models and the main computational tools for the football analytics domain. It further introduces the footBayes R package that accompanies the reader through all the examples proposed in the book. It aims to be both a practical guide and a theoretical foundation for students, data scientists, sports analysts, and football professionals who wish to understand and apply predictive modelling in a football context.Key FeaturesDiscusses various modelling strategies and predictive tools related to football analyticsIntroduces algorithms and computational tools to check the models, make predictions, and visualize the final resultsShowcases some guided examples through the use of the footBayes R package available on CRANWalks the reader through the full pipeline: from data collection and preprocessing, through exploratory analysis and feature engineering, to advanced modelling techniques and evaluationBridges the gap between raw football data and actionable insightsThis text is primarily for senior undergraduates, graduate students, and academic researchers in the fields of mathematics, statistics, and computer science willing to learn about the football analytics domain. Although technical in nature, the book is designed to be accessible to readers with a background in statistics, programming, or a strong interest in sports analytics. It is well-suited for use in academic courses on sports analytics, data science projects, or professional development within football clubs, agencies, and media organizations.
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In den WarenkorbPaperback. Zustand: Brand New. 272 pages. 9.18x6.12x9.21 inches. In Stock.
Sprache: Englisch
Verlag: Taylor and Francis Ltd, GB, 2025
ISBN 10: 1032030631 ISBN 13: 9781032030630
Anbieter: Rarewaves USA United, OSWEGO, IL, USA
Paperback. Zustand: New. Predictive Modelling for Football Analytics discusses the most well-known models and the main computational tools for the football analytics domain. It further introduces the footBayes R package that accompanies the reader through all the examples proposed in the book. It aims to be both a practical guide and a theoretical foundation for students, data scientists, sports analysts, and football professionals who wish to understand and apply predictive modelling in a football context.Key FeaturesDiscusses various modelling strategies and predictive tools related to football analyticsIntroduces algorithms and computational tools to check the models, make predictions, and visualize the final resultsShowcases some guided examples through the use of the footBayes R package available on CRANWalks the reader through the full pipeline: from data collection and preprocessing, through exploratory analysis and feature engineering, to advanced modelling techniques and evaluationBridges the gap between raw football data and actionable insightsThis text is primarily for senior undergraduates, graduate students, and academic researchers in the fields of mathematics, statistics, and computer science willing to learn about the football analytics domain. Although technical in nature, the book is designed to be accessible to readers with a background in statistics, programming, or a strong interest in sports analytics. It is well-suited for use in academic courses on sports analytics, data science projects, or professional development within football clubs, agencies, and media organizations.
Zustand: New. Ioannis Ntzoufras is a distinguished statistician and academic, widely recognized for his contributions to statistical modeling, Bayesian analysis, and sports analytics. He is a full professor in the Department of Statistics at the Athens Universi.
Zustand: New.
Sprache: Englisch
Verlag: Taylor and Francis Ltd, GB, 2025
ISBN 10: 1032030631 ISBN 13: 9781032030630
Anbieter: Rarewaves.com UK, London, Vereinigtes Königreich
EUR 68,09
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In den WarenkorbPaperback. Zustand: New. Predictive Modelling for Football Analytics discusses the most well-known models and the main computational tools for the football analytics domain. It further introduces the footBayes R package that accompanies the reader through all the examples proposed in the book. It aims to be both a practical guide and a theoretical foundation for students, data scientists, sports analysts, and football professionals who wish to understand and apply predictive modelling in a football context.Key FeaturesDiscusses various modelling strategies and predictive tools related to football analyticsIntroduces algorithms and computational tools to check the models, make predictions, and visualize the final resultsShowcases some guided examples through the use of the footBayes R package available on CRANWalks the reader through the full pipeline: from data collection and preprocessing, through exploratory analysis and feature engineering, to advanced modelling techniques and evaluationBridges the gap between raw football data and actionable insightsThis text is primarily for senior undergraduates, graduate students, and academic researchers in the fields of mathematics, statistics, and computer science willing to learn about the football analytics domain. Although technical in nature, the book is designed to be accessible to readers with a background in statistics, programming, or a strong interest in sports analytics. It is well-suited for use in academic courses on sports analytics, data science projects, or professional development within football clubs, agencies, and media organizations.
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