MONEYBALL: DATA-DRIVEN BASEBALL on September 23, 2011, the film Moneyball opened in theaters the United States, starring Brad Pitt as Billy Beane, the iconoclastic manager of the described Athletics. The film was based general Lewis that baseball, how Beane led on the bestselling book by Michael in Major League to win 103 the underdog A's, with one of the tiniest budgets five times in the next eight games in 2002. Under Beane's watch, the As de the play seasons. At the opening of the 2002 baseball season, the wealthiest team was the New York Yankees, with a payroll of $126 million; the Oakland As and Tampa Bay Devil Rays, each with payrolls of $41 million, were the poorest. These disparities meant that only the wealthiest teams could afford the best players. A p team, such as the A's, could only afford what the "better" teams rejected and thus was almost certain to fail. That is until Billy Beane and Moneyball entered the picture How did Beane do it? He took a close look at the data. Conventional baseball wisdom main tained that big-name highly athletic hitters and skillful young pitchers were the main ingredients for winning. Beane and his assistant general manager Paul DePodesta used advanced statistical analysis of player and team data to prove that wrong. The prevailing metrics for predicting wins, losses, and player performance, such as batting averages, runs batted in, and stolen bases, were vestiges of the early years of baseball and the statistics that were available at that time. Baseball talent scouts used these metrics, as well as their gut intuition, to size up talent for their teams. Beane and DePodesta found that a different set of metrics, namely, the percentage of time