• Analytic Methods In Sports

Analytic Methods In Sports

Analytic Methods In Sports

( from 245 reviews )
  • Author
    Thomas A Severini
  • Publisher
    Crc Press
  • Publication date
    14 April 2020

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Book Detail

  • Book Title

    Analytic Methods In Sports

  • Author

    Thomas A Severini

  • Date Published

    14 April 2020

  • Publisher

    Crc Press

  • Pages

    356 pages

  • ISBN

    9781000050905

Book Description

One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, Second Edition provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports.

The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from standard statistical analyses. The book integrates a large number of motivating sports examples throughout and offers guidance on computation and suggestions for further reading in each chapter.

Features

  • Covers numerous statistical procedures for analyzing data based on sports results
  • Presents fundamental methods for describing and summarizing data
  • Describes aspects of probability theory and basic statistical concepts that are necessary to understand and deal with the randomness inherent in sports data
  • Explains the statistical reasoning underlying the methods
  • Illustrates the methods using real data drawn from a wide variety of sports
  • Offers many of the datasets on the author’s website, enabling you to replicate the analyses or conduct related analyses

New to the Second Edition

  • R code included for all calculations
  • A new chapter discussing several more advanced methods, such as binary response models, random effects, multilevel models, spline methods, and principal components analysis, and more
  • Exercises added to the end of each chapter, to enable use for courses and self-study
  • Full solutions manual available to course instructors.

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