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Can I read Analyzing Baseball Data with R, Second Edition (Chapman & Hall/CRC The R Series) on EtoBox?

Analyzing Baseball Data with R, Second Edition (Chapman & Hall/CRC The R Series) by Max Marchi, Jim Albert, Max Marchi, Jim Albert, Benjamin S. Baumer is a nonfiction available to read on EtoBox.

What is Analyzing Baseball Data with R, Second Edition (Chapman & Hall/CRC The R Series) about?

Analyzing Baseball Data with R Second 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 online. New to the second edition are a systematic adoption of the tidyverse and incorporation of Statcast player tracking data (made available by Baseball Sava

Who reads Analyzing Baseball Data with R, Second Edition (Chapman & Hall/CRC The R Series)?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Max Marchi, Jim Albert, Max Marchi, Jim Albert, Benjamin S. Baumer
Publisher
CRC Press, Taylor & Francis Group
Published
2018
Language
EN
ISBN
9781351107075
Category
nonfiction
Subjects
Mathematics, Sports, Computer Science

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