The game of baseball changes very little from year to year. There are occasional, minor shifts, like the introduction of the automatic intentional walk this year, or tweaks like the Utley rule that refine how baserunners can slide into a base, but the game itself hardly changes, and that continuity and imperturbability is a part of its charm.
Baseball analysis, on the other hand, has undergone a massive realignment in the past two decades. New technology for measuring success on the field and new statistics for analyzing the old data and the new have turned baseball conversations on their ear and added a whole new vocabulary of WAR, wOBA, WPA, and FIP to the familiar measurements of batting average, RBI, wins, ERA, and saves.
If you’re a baseball fan who wants to expand your knowledge of the new stats but doesn’t know where to begin, Keith Law’s 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 is for you.
Out With the Old
For almost as long as men have played the game, they have measured their performance, and many of the stats we use today date back to the baseball’s early days. The venerable measurement of batting average, flashed across our television screens at the beginning of each at bat, was devised by sportswriter Henry Chadwick in the mid-19th century. Chadwick also invented the earned run average (ERA) to measure pitchers’ performance. There is nothing complex about these calculations, and they convey information to the reader about what happened in the games. As simple, accessible units of measurement, they served their purpose and still do.
Less useful, in Law’s eyes (and the eyes of most modern observers of the game) are the pitching statistics of wins and saves. The win (or “pitcher-win” as modern statisticians name it) sounds as simple as batting average or ERA: how many games did the team win while the pitcher was the pitcher of…