Want to work for the Cleveland Indians? All you have to do is be a whip-smart, forward-thinking inventor of analytical tools, and continue on, turning once-thought luxuries in to items team ultimately yearn to have. Seems easy enough, no? Such is the case with Max Marchi who will be leaving Baseball Prospectus to take a job with the Cleveland Indians.
Marchi, as some of you may know, is the author of a recently released 350-page book titled “Analyzing Baseball Data with R.”
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.
Got all that?
Readers of Marchi will know that he has recently done a lot of work on Pitch F/X and catcher framing, a hot topic back in 2013 when the Indians were dealing with the luxury of two lineup-friendly catchers in Yan Gomes and Carlos Santana—the former being much better at pitch-framing than the latter.
As Marchi writes in his farewell post, his first sabermetric studies were written on an Italian blog more than 10 years ago. Hard work gets noticed and the Indians, long-time users of advanced analytics, are no strangers to digging for gold. Marchi joins a growing list of individuals who have gone from writer/analyst to being hired by a Major League club, including Keith Woolner who left Baseball Prospectus to become the Manager of Baseball Research and Analysis for the Indians back in 2007.
As Woolner wrote in his farewell post, “Baseball Prospectus has, since its inception, been dedicated to the concept that that there are better ways for major league baseball teams to make decisions. Augmenting conventional, scouting-based reports with objective evidence gathered through analysis of the statistical record can help a team gain a competitive edge.”
Let’s hope that Marchi’s addition only serves to make the Indians that much smarter than their competition. Lord knows they can use every competitive edge they can get.