Moneyball

Michael Lewis’s Moneyball, published in 2003, chronicles how the Oakland Athletics, under general manager Billy Beane, exploited inefficiencies in baseball’s player market. With one of the sport’s smallest payrolls, the A’s could not compete for stars against rich clubs like the New York Yankees. Beane, aided by assistant GM Paul DePodesta and a network of statistically minded analysts, turned to sabermetrics—the empirical study of baseball data—to find undervalued players. The book’s central argument is that baseball’s traditional scouting culture overrated misleading indicators: batting average, runs batted in, and stolen bases, along with physical appearance and gut instinct. Instead, Beane’s staff prized statistics that correlated with scoring runs and preventing them, especially on-base percentage and slugging percentage. The A’s famously targeted players dismissed by scouts as flawed—catchers with high walk rates, pitchers with odd deliveries, and aging or injured veterans—because the market priced them cheaply. Lewis contrasts this approach with the romantic scouting wisdom embodied by figures like the fictional composite scout in the opening pages, who judges players by their looks and swings. The narrative follows the 2002 season, when Oakland won a record 20 consecutive games and reached the playoffs despite losing key stars to free agency. It also profiles players such as Scott Hatteberg, a catcher converted to first base, and pitcher Chad Bradford, whose submarine style scouts disliked. The book became a landmark in sports economics, popularizing the idea that data can beat conventional wisdom.