- The Sabermetric Revolution: Assessing the Growth of Analytics in Baseball by Benjamin Baumer and Andrew Zimbalist
No sport is as obsessed by statistics and statistical analysis as baseball. Fans have used stats for more than a century to compare players from different eras, while mathematically inclined experts employ increasingly complex statistical models to analyze and predict player performance. “Sabermetrics,” a now ubiquitous term popularized by stats guru Bill James, is derived from the acronym SABR (Society for American Baseball Research), yet it is often misunderstood. Benjamin Baumer and Andrew Zimbalist’s The Sabermetric Revolution is a concise yet thorough study of baseball analytics that explores the current state of knowledge of sabermetric research and how that knowledge influences teams.
The book opens with an analysis of Michael Lewis’s 2003 bestselling book Moneyball and the film (2011), which played a pivotal role in popularizing sabermertric ideas. While [End Page 239] acknowledging the entertainment value of both, the authors contend that Moneyball “substantially misrepresents baseball reality” (1). Arguing that “the story of baseball statistics … is a good deal richer and more involved” (2) than the book and film suggest, the authors trace the development of multifaceted statistical analysis from the 1860s to the present to suggest baseball analytics are nothing new; rather, they have evolved especially since the 1950s and exploded in the 1970s and beyond.
Chapter two discusses the growth and proliferation of analytics in baseball. Baumer (a former statistical analyst for the New York Mets) and Zimbalist suggest that the number of sabermetricians working inside baseball has exploded since 2002 when just a handful was employed. They estimate that, by 2012, twenty-six of the thirty major-league teams had at least one person working full- or part-time in analytics. Given that teams are spending more money to improve their technological infrastructure and that more complex data are available to teams, the authors argue that the biggest challenge from front offices is to find analysts “who are capable of extracting meaningful information” (37).
In chapters three and four, the authors provide a succinct survey of the current state of sabermetric knowledge for offense (hitting and base running) and defense (pitching and fielding) and explain basic sabermetric theories. Baumer and Zimbalist deconstruct the math formulas used in analytics to demonstrate how sabermetric analysis works. After explaining Bill James’s formula to predict a team’s winning percentage and projected finish (often called the Pythagorean Expectation), the authors address various predictive analyses that estimate the number of runs a team will score. Sabermetrics debunk the importance of older, traditional statistics, such as batting average, in favor of more recent hitting statistics and metrics, such as OPS (on-base percentage + slugging percentage), runs created, and linear weights to quantify more accurately contributions in a given year and predict future performance. Accurate measurement of players’ defensive contributions has been a greater challenge for sabermetrics. Among other metrics, defense independent pitching theory (DIPS), batting average on balls in play (BABIP), fielding independent pitching (FIP) for pitchers, range factor (RF), defensive efficiency rating (DER), and ultimate zone rating (UZR) are explained and their benefits and limits clarified. The authors take a critical look at WAR (wins above replacement), an increasingly popular metric to determine how many wins each player contributes to a team. “The problems with WAR have to do not only with the opaqueness of the underlying data and methodology, but also with known elements of the method that are dubious,” suggest the authors (76).
Following chapters focusing on the increased use of sabermetrically informed analysis to assess performance and strategy in football and basketball and how statistical analysis has affected the business model of baseball and competitive balance, the study’s seventh and final chapter may be its most important: estimating the impact of sabermetrics. The authors note that sabermetrics is a rapidly evolving science and that many issues still divide the analytics community. They raise several interesting points in determining the saber intensity of a team, including the difficulties...