Typically, any mention of Moneyball brings to mind the 2011 film that covers the story of Billy Beane, manager for the Oakland Athletics MLB team in 2002. In the film, Beane, played by Brad Pitt, applies sabermetrics to recruit and analyze players—and his longshot efforts with data end up paying off.
But before the Columbia Pictures flick came out, author and journalist Michael Lewis penned the book Moneyball: The Art of Winning an Unfair Game. Lewis’ account closely followed Beane’s journey with the Athletics to apply sports data in a meaningful way. For the first time, sabermetrics had a tangible effect on a team’s success.
The book helped usher in a new era of modern sports, which favors identifying patterns from hard stats. But it’s not just the franchises and leagues themselves that have adopted a data-first policy. Through sportsbooks and fantasy leagues, fans are also dealing with hard analysis related to their favorite teams—and it helped create a multi-billion-dollar industry in the US alone.
Since the federal government repealed a ban on sports betting in 2018, dozens of states have opened up their retail and online markets. Those looking for moneylines and point spreads don’t need to head to Vegas anymore—parlays and free bets are available at the touch of a button.
Moneyball helped launch other industries, too—including wearable tech, VR for sports training, and even sports medicine. Barring Hollywood twists from the 2011 film, how exactly did Billy Beane accomplish this?
Conventional Wisdom Meets Capitalism
Beane’s journey started with a single mission: to help recruit the best Athletics roster possible while working with a minimal budget. Back in 2002, the Athletics had a $44 million budget compared to the MLB’s giant, the Yankees, who worked with $122 million.
To curb this disadvantage, Beane needed to throw conventional wisdom out the window. His approach was based on previous works regarding baseball, which explored the topic of sabermetrics. MLB staff, like Bill James of the Red Sox, had already explored the topic of empirical data analysis in baseball at length.
Using James’ foundational theories, Beane wanted to make concrete applications regarding the recruitment of players. He crunched hard data related to on-base and slugging percentages on prospects to identify and recruit undervalued players, who were determined to be ‘undervalued’ based on their predicted contributions to the team versus salary expenses.
In other words, Beane wasn’t just looking to perfect ideas put forth by James and other sabermetrics enthusiasts. He was looking to apply that information in a financial sense that would benefit the Athletics. The MLB is a business, after all, and all successful ventures benefit from efficiency.
The Billy Beane Legacy
Not everybody is a fan of Moneyball. Some baseball pundits think stats on stolen bases and bunting, which were tossed aside by Beane, matter just as much as other data points on on-base and slugging percentages. Others feel that Beane earned undue credit via Lewis’ book for the research conducted by James and others who helped evolve sabermetrics.
Some have instead criticized Lewis’ understanding of the sport and, therefore, his exploration of Beane’s story. Baseball pundits have posited that the league isn’t nearly as dependent on big money to create World Series-winning teams.
Regardless of whether Beane himself perfected the application of sabermetrics, or how Lewis described that journey in his 2002 book, there’s one clear conclusion: major league sports have adopted Beane’s primary thesis.
Today, each of the MLB’s 30 teams has its own data analytics department. But the trend has grown beyond baseball’s sabermetrics. The NBA has its own variation, known as ‘Moreyball’, after the president of operations with the 76ers, Daryl Morey. Across the pond in the EU, top football clubs from Arsenal to FC Barcelona also employ dozens of data specialists—and they’re not likely to go anywhere anytime soon.
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