Last year, the ASA and CRC Press combined forces to produce the Statistical Reasoning in Science and Society series. The idea was to produce short and inexpensive books about a range of topics aimed at professionals across many fields, the general public, and high-school and college students. The second book in the series is Visualizing Baseball by Jim Albert, author or editor of 10 books, including Analyzing Baseball Data with R, Curve Ball, and the Handbook of Statistical Methods and Analyses in Sports. Here, Albert—a professor of statistics at Bowling Green State University—answers a few questions about his new book and what inspired him to
What do you want your audience to take away from the book?
There is an inherent randomness in baseball, both in the game results and the performances of its players. But there are clear patterns in performance, both from a historical and a player perspective, and statistical graphs are a great way to display these patterns. I would like the reader to understand new things about baseball and appreciate the power of graphical displays to communicate these truths.
What inspired you to write this book?
I am a great baseball fan and, as a statistician, I have been interested in the use of statistical thinking to better understand the game. I am particularly fascinated with the usefulness of graphs to communicate patterns in data, and I believe graphs are underutilized in sabermetrics (the scientific study of baseball). I thought a book focused on the application of graphical displays in baseball could appeal to a wide audience.
What audience did you have in mind while writing your book?
I was writing this book for the baseball fan who wishes to learn more about the statistical side of baseball without getting deep into the formulas or models used. Graphs, instead of formula or tables, are used to communicate. I was also writing this book for the person who wishes to learn more about statistical graphics. The interested reader can replicate many of the graphs in the book using the data and ggplot2 R code available on the book website.
What makes your book stand out from its competitors?
Although books are available that describe sabermetrics study, my book is unique in its focus on statistical graphs to communicate statistical thinking in baseball. I purposely limited the use of equations or formulas so the book potentially could appeal to a broad audience.
What did you enjoy about writing the book?
This book combined two of my passions: the game of baseball and the use of graphs to display statistical patterns in data. It can often take many iterations to produce a reasonable graph, but a good graph display has the potential to communicate interesting patterns in sports to many people.
Visualizing Baseball provides a visual exploration of the game of baseball. Graphical displays are used to see how measures of performance, at the team and individual levels, have changed over the history of baseball.
Special graphs are used to describe pitch data from the PitchFX system and batted ball data from the Statcast system. One can explore patterns of streaky performance and clutch play by the use of graphs, and special plots are used to predict final season batting averages based on data from the middle of the season.
Baseball fans should be interested in the topics of the chapters, especially those who are interested in learning more about the quantitative side of baseball. Many statistical ideas are illustrated, helping to promote statistical literacy at many levels. From a practitioner’s perspective, the chapters offer many illustrations of the use of a modern graphics system, and R scripts are available on an accompanying website to reproduce and potentially improve the graphs in the book