Understanding Sabermetrics: An Introduction to the Science of Baseball Statistics

by Gabriel B. Costa, Michael R. Huber, John T. Saccoman

Born in the 1970s as a radical challenge to traditional baseball statistics, sabermetrics has developed into a new way of understanding many aspects of the game. Its practitioners have created new statistical tools and revised our old ways of thinking about established measures such as the batting average, tactics such as the sacrifice bunt, and even who among the greats was truly great. This introduction to the basics of sabermetric analysis explains concepts including normalization, peak versus career performance, linear weights and runs created, as well as popular calculations like OPS (On-Base plus Slugging), WHIP (Walks and Hits per Inning Pitched), PF (Park Factor) and others increasingly used by baseball fans. Instructors considering this book for use in a course may .

Genres: Baseball, Sports, Nonfiction

190 pages, Paperback

First published December 1, 2007

Reviews

[Aaron · Rating 4 out of 5]

While other reviewers have described this as essentially a math textbook, I think readers with high school–level math skills can follow most, if not all, of the content. There are some frustrating errors—such as the incomplete R code on page 150, which will not run—and some glaring typos (e.g., page 83: “There does not appear to be a high correlation between linear weights offensive runs and wins above replacement.” Wrong!).

That said, there are definitely strong sections in the book, including a lengthy discussion on building a Wins Above Replacement model using publicly available data. I liked the book enough to purchase the next two sabermetrics volumes in the series, but I do wish it had a better editor and a bit more focus on key topics rather than, say, debating whether Gil Hodges belongs in the Hall of Fame. I may use a couple of chapters from this text for a university-level Sports Analytics course.

[Eric Parsons · Rating 2 out of 5]

After a while, I asked myself, "why am I reading this?" I love baseball. I agree that the traditional stats (BA, ERA, and the like) are not terribly useful overall. I agree that the SABR stats are more descriptive and predictive. My own favorite team, the Pittsburgh Pirates, were re-built on them for 2012-2016. (See Travis Sawchik's "Big Data Baseball.") However, even though I'm a math and baseball guy, this book was somewhat pointless. With the extra stats, there wasn't much discussion of the validity of them, so why bother?

[Daniel Archer · Rating 4 out of 5]

Interesting read, though quite literally a math textbook wrapped around sabermetric concepts. I’m quite satisfied to leave the detailed math to others and just consume the stats they create, as long as I understand what they’re doing and how they got there.

[Creed Anderson · Rating 4 out of 5]

I don’t think I really learned that much about sabermetrics besides finally understanding WAR. However, just hearing these guys write about it gives me so much more respect and love for the game. A surprisingly enjoyable read.

[Ivan Taylor · Rating 4 out of 5]

This is a small textbook for a short university math course. It is a good introduction to sabermetrics. Unfortunately, there are many typographical errors that make reading it difficult.