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Analyzing Baseball Data with R 3rd Edition by Jim Albert, Benjamin S Baumer, Max Marchi ISBN 1032668091 9781032668093

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Analyzing Baseball Data With R third edition Jim Albert Digital Instant Download

Author(s): Jim Albert, Benjamin S. Baumer, Max Marchi
ISBN(s): 9781032668093, 1032668091
Edition: 3
File Details: PDF, 43.15 MB
Year: 2024
Language: english
SKU: EB-57481238 Category: Tags: , ,

Analyzing Baseball Data with R 3rd Edition by Jim Albert, Benjamin S Baumer, Max Marchi – Ebook PDF Instant Download/Delivery: 1032668091, 9781032668093
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Product details:

ISBN 10: 1032668091 
ISBN 13: 9781032668093
Author: Jim Albert, Benjamin S Baumer, Max Marchi

“Our community has continued to grow exponentially, thanks to those who inspire the next generation. And inspiring the next generation is what the authors of Analyzing Baseball Data with R are doing. They are setting the career path for still thousands more. We all need some sort of kickstart to take that first or second step. You may be a beginner R coder, but you need access to baseball data. How do you access this data, how do you manipulate it, how do you analyze it? This is what this book does for you. But it does more, by doing what sabermetrics does best: it asks baseball questions. Throughout the book, baseball questions are asked, some straightforward, and others more thought-provoking.” From the Foreword by Tom Tango Analyzing Baseball Data with R Third Edition introduces R to sabermetricians, baseball enthusiasts, and students interested in exploring the richness of baseball data. It equips you with the necessary skills and software tools to perform all the analysis steps, from importing the data to transforming them into an appropriate 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 ggplot2 graphics functions and employ a tidyverse-friendly workflow throughout. Much of the book illustrates the use of R through popular sabermetrics topics, including the Pythagorean formula, runs expectancy, catcher framing, career trajectories, simulation of games and seasons, patterns of streaky behavior of players, and launch angles and exit velocities. All the datasets and R code used in the text are available for download online. New to the third edition is the revised R code to make use of new functions made available through the tidyverse. The third edition introduces three chapters of new material, focusing on communicating results via presentations using the Quarto publishing system, web applications using the Shiny package, and working with large data files. An online version of this book is hosted at https://beanumber.github.io/abdwr3e/.

Analyzing Baseball Data with R 3rd Table of contents:

  1. Chapter 1: Baseball Datasets
    Introduces major baseball databases (Lahman, Retrosheet, Statcast), explaining their structure and how to obtain and use them for analysis of players, teams, games, and plays.

  2. Chapter 2: Introduction to R
    Covers basics of R programming with tidyverse, including data frames, vectors, functions, and reading/writing data—fundamental for data manipulation in baseball analytics.

  3. Chapter 3: Graphics
    How to create visualizations (bar graphs, scatterplots, boxplots) to explore baseball data, with specific examples like comparing historic sluggers and home run races.

  4. Chapters 4–8: Statistical Analysis in Baseball

    • Runs vs. Wins models

    • Run expectancy and value of plays

    • Effects of balls and strikes counts

    • Catcher framing analysis

    • Player career trajectories and aging patterns

  5. Chapter 9: Simulation
    Explains simulating innings, seasons, and playoffs using Markov chains and probabilistic models.

  6. Chapter 10: Streaky Performances
    Investigates hitting streaks and performance variability over time.

  7. Chapters 11–12: Working with Large Databases
    Using MySQL with R, constructing databases, computing park factors, and efficiently handling large Statcast datasets.

  8. Chapter 13: Home Run Hitting
    Detailed analysis of home run data including launch angles, ballpark effects, and changes over recent seasons.

  9. Chapter 14: Scientific Presentation
    Using Quarto for creating reproducible, professional presentations with embedded R output.

  10. Chapter 15: Shiny Apps for Baseball
    Building interactive web applications for baseball data analysis.

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Tags: Jim Albert, Benjamin S Baumer, Max Marchi, Analyzing Baseball