MONEYBALL: Statistics Makes Its Hollywood Premiere

UPDATE: MONEYBALL starring Brad Pitt almost wins the Oscar for Best Picture!

Imagine that you are a movie mogul looking for the next big hit. Two screenwriters come to you with a great idea for a baseball movie starring Brad Pitt. It combines America’s favorite pastime with one of Hollywood’s biggest names. It sounds like a sure hit. The next obvious question is, “What’s the storyline? “, to which the writers enthusiastically answer, “It’s about statistics!”

Though there is obviously more to the story, it is true that statistics plays a key role in the movie Moneyball . The film premiered this past fall and, though it has not become a major blockbuster, it has received some critical acclaim. Now, we aren’t movie reviewers. We’ll leave that to the experts. However, we are excited that a major motion picture shows the competitive advantage that can be had from statistical analysis (yes, we really ARE that nerdy).

Moneyball, adapted from a book by Michael Lewis, author of The Blind Side, is about General Manager Billy Beane and the Oakland Athletics. Beginning in 1997, Beane builds the club into one of the top American League Teams, despite the players being paid near the bottom of the pay scale. He does it by employing statistical analysis, or in this case, a type of analysis, called Sabermetrics. (For more information about Sabermetrics, see How Sabermetrics Works).

In a nutshell, Sabermetrics applies statistical analysis to objective data in order to calculate a team’s optimal performance. It’s the same principle that is used in determining the ROI of a marketing campaign (that’s why we are so giddy)…look at existing data, determine those elements that are most valuable and predictive, build the campaign and, “swing for the bleachers.”