Smart Baseball: The story behind the old stats that are ruining the game, the new ones that are running it, and the right way to think about baseball
by Keith Law, 2017

The sabermetric revolution in baseball has already happened. There are no longer any holdouts among MLB front offices; by the start of 2017, all thirty organizations had established analytics departments, employing multiple people, often with Ph.D.s in computer science specialties, charged with gathering data and using them to answer questions from the GM or the coaching staff, or to look for previously undiscovered value in the market for players. If your local writer is still talking about players in terms of pitcher wins, saves, or RBI, he’s discussing the role of the homunculus in human reproduction. The battle is over, whether the losers realize it or not.

If you are familiar with wRC, FIP, and fWAR/bWAR in baseball, you probably don’t need this book. It spends a long time explaining why old stats (RBI, ERA, pitcher wins) are not as useful as previously imagined and how new stats are better. The last few chapters include interesting discussions on why certain players should be in the hall-of-fame and on the role of scouts in a modern organization.