Analyzing Baseball Data with R 1st Edition by Max Marchi, Jim Albert ISBN 1466570237 9781466570238

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Product details:

ISBN 10: 1466570237 

ISBN 13: 9781466570238

Author: Max Marchi, Jim Albert 

With its flexible capabilities and open-source platform, R has become a major tool for analyzing detailed, high-quality baseball data. Analyzing Baseball Data with R provides an introduction to R for sabermetricians, baseball enthusiasts, and students interested in exploring the rich sources of baseball data. It equips readers with the necessary skills and software tools to perform all of the analysis steps, from gathering the datasets and entering them in a convenient format to visualizing the data via graphs to performing a statistical analysis.

The authors first present an overview of publicly available baseball datasets and a gentle introduction to the type of data structures and exploratory and data management capabilities of R. They also cover the traditional graphics functions in the base package and introduce more sophisticated graphical displays available through the lattice and ggplot2 packages. Much of the book illustrates the use of R through popular sabermetrics topics, including the Pythagorean formula, runs expectancy, career trajectories, simulation of games and seasons, patterns of streaky behavior of players, and fielding measures. Each chapter contains exercises that encourage readers to perform their own analyses using R. All of the datasets and R code used in the text are available online.

This book helps readers answer questions about baseball teams, players, and strategy using large, publically available datasets. It offers detailed instructions on downloading the datasets and putting them into formats that simplify data exploration and analysis. Through the book’s various examples, readers will learn about modern sabermetrics and be able to conduct their own baseball analyses.

Table of contents:

1. The Baseball Datasets

2. Introduction to R

3. Traditional Graphics

4. The Relation between Runs and Wins

5. Value of Plays Using Run Expectancy

6. Advanced Graphics

7. Balls and Strikes Effects

8. Career Trajectories

9. Simulation

10. Exploring Streaky Performances

11. Learning about Park Effects by Database Management Tools

12. Exploring Fielding Metrics with Contributed R Packages

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Tags: Max Marchi, Jim Albert, Analyzing Baseball Data, R