For the first time, I’d like to talk about a book I know solely because I follow its author online. Lee Panas blogs at Tiger Tales, a blog devoted, as the title implies, to the happenings of the Detroit Tigers. It is definitely one of the best single-team blogs around, as it includes good discussion of the current team with interesting work on the team historically. For our purposes, though, Panas has interests beyond the narrow confines of the Detroit Tigers. He has recently published a sabermetric primer called Beyond Batting Average: Statistics for the 21st Century. I picked up the electronic version recently to review here, so let me give the book its due.
The book does three things: It gives a history of the development of baseball statistics, lays out newer statistics in detail, and gives recommendations for the best statistics to use in player evaluation. Let us consider each in turn. The history of statistics that Panas gives is necessarily brief. It is not a primary focus of the book, and for that reason it is primarily confined to Chapter 1. However, each ensuing chapter gives some information on the history of stats dealing with the chapters topic. Given my own historical bent, I would have liked to see more of this. Given the book’s primary focus as a primer on newer statistics, it is unsurprising this area was not explored in more depth.
Next, Panas lays out newer statistics in detail. It is at this that the book truly excels. Want to know what OPS, WAR, UZR, qERA, FIP, or other statistics are? Panas’ gives some of the most succinct and clear explanations that I have seen. He is not bogged down in the exact mathematical derivations of each statistic, and instead he focuses on the originator, formula, and clarifying examples. Each example does a good job in illustrating the stats strengths and weaknesses. As someone already interested in statistics and particularly in using statistics to compare players, I found this portion of the book invaluable.
Finally, Panas gives recommendations for the best statistics to evaluate players. He emphasizes several things in these stats: repeatability, comprehensiveness, and sources. Repeatability refers to statistics that correlate highly from year to year. Why is on-base average better than batting average? For one reason, it is more predictive of a player’s performance next season. Comprehensiveness describes statistics that evaluate each area of a player’s full performance. Stats like WAR focus on players’ hitting and fielding contributions, instead of focusing narrowly on just one element of play. Sources focuses on where statistics derive their data. Panas considers fielding stats based on play-by-play data better than rivals with less specific sources. He gives more weight to stats that adjust for park, era, etc. than stats that don’t. I think Panas’ three grounds for recommendations make a great deal of sense. They have the advantage of forcing the analyst to look at what biases are built into each statistics and therefore add some humility into our evaluations.
Overall, Panas wrote a short and accessible introduction to sabermetric statistics. If you want to learn more about the most advanced statistics on the market right now, it is tough to find a better source.