Sports Analytics in Practice with R

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Ted Kwartler. Sports Analytics in Practice with R

Sports Analytics in Practice with R

Contents

List of Illustrations

List of Tables

Guide

Pages

Preface

Author Biography

Foreword

1 Introduction to R. Objectives

R Libraries

R Functions

The R Programming Language

Applying R Basics to Real Data

Positives and Negatives of R

Exercises

2 Data Visualization Best Practices. Objectives

R Libraries

R Functions

Sports Context

Plotting Best Practices and Static Images

Interactive Plots

Next Steps

Notes

3 Geospatial Data Understanding Changing Baseball Player Behavior. Objectives

R Libraries

R Functions

Sports Context

Code

Examining a Single Pitcher Analytically

Examining a Single Batter Analytically

Extending the Chapter Methods

Exercises

Notes

4 Evaluating Players for the Football Draft. Objectives

R Libraries

R Functions

Sports Context

Technical Context

KNN—Supervised Learning: Binary Classification

KNN—Supervised Learning: Multi-class Classification

Spherical K-means

Code—Binary Classification

Code—Multi-Class Classification

Code—Continuous Regression

Code—Unsupervised Learning (Clustering)

Extending the Approaches Employed

Exercises

Notes

5 Logistic Regression Explaining Basketball Wins and Losses with Coefficients. Objectives

R Libraries

R Functions

Sports Context

Technical Context

Code- Explaining Complexity with a Model’s Parameters

Extending the Method Demonstrated

Exercises

Notes

6 Gauging Fan Sentiment in Cricket. Objectives

R Libraries

R Functions

Sports Context

Technical Context

NLP-specific Terms

Code

Extending the Approaches Employed

Exercises

Notes

7 Gambling Optimization. Objectives

R Libraries

R Functions

Chapter Caveat

Sports Context

Technical Context

Complete Code—Linear Programming

Extend the Methods Employed

Exercises

Notes

8 Exploratory Data Analysis Searching Data for Opponent Insights. Objectives

R Libraries

R Functions

Sports Context

Technical Context

Code- Exploratory Data Analysis

Exercises

Notes

Index

WILEY END USER LICENSE AGREEMENT

Отрывок из книги

Ted Kwartler Harvard Extension School Adjunct, Faculty of Arts & Sciences Maynard, MA

This book has been a long journey in the making. Originally the book’s scope was centered on individualized chapters demonstrating analytical techniques within a sports context. The goal is that a reader inherits various tools that act as a foundation for analysis to build upon and add complexity with subsequent analyses as the reader’s technical acumen and sports interests grow. Each chapter is meant to be a standalone reference as the reader explores and learns. This also frees up the reader to focus on topics of interest. For example, a reader may not want to learn about natural language processing so could skip that chapter altogether to focus on another subject such as optimizing a fantasy football lineup. The book’s undertaking grew in complexity due to a personal commitment to demonstrate concepts on diverse data sets including Paralympic athletes, female soccer and basketball, and less US-centric popular sports including cricket in addition to the more typically demonstrated sports analyses of men’s football, baseball, and basketball. My goal is to make the subject accessible and relevant to many in the analytics field despite this effort slowing the book’s creation. Keep in mind a chapter’s concepts can be applied to many sports domains. For example, the text analysis applied to cricket fan forum posts can easily be applied to men’s basketball fan tweets or forum posts. Each chapter’s takeaway is meant to be a broadly useful tool, not a brittle or narrowly focused analysis. Additionally, the book was delayed due to the pandemic’s effect on the sports-world. Admittedly the shortened seasons, canceled games, and other changes that created outlier statistics pales in comparison to the pandemic’s hardship and humanistic impact outside of sports. Despite these challenges, the book’s end result was worth the delay. The final product covers many diverse concepts, and data, encouraging analytics professionals to enjoy the intersection of sports and analysis.

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