It’s been ten years since Brad Pitt’s portrayal of Oakland A’s manager, Billy Beane, in the Hollywood hit, Moneyball, launched sports analytics into the mainstream.
Beane pioneered the use of data analytics in sports by increasing wins without spending more money. In fact, without his data-driven strategy, he would have had to spend over a billion dollars buying top-rated players to create the same amount of wins for the A’s.
When sports teams embrace data, does it actually create more wins? Basketball legend Charles Barkley doesn’t think so. In staunch opposition to the Moneyball Movement, he insists,
“I’ve always believed analytics was crap”.
So are we all just suckers for a great underdog story, especially one starring Brad Pitt?
I ran an analysis of the sports data movement to find out the answer.
I looked at a piece that ESPN produced in 2015 where they rated pro sports teams in basketball, baseball, football, and hockey on how much they were using statistics. After grouping the teams into those who embrace and those who reject data analytics, I compared the performance of these groups by looking at their regular-season winning percentages over ten years
The teams who “rejected data,” shown here in blue, won less than half of their games and you can see a clear downward trend. These teams include the New York Knicks and the Brooklyn Nets who largely ignored analytics, such as the data-born revolution calling for more 3 pointers. Conversely, in orange, the Mavericks, Rockets, 76ers, and Spurs, all believers in data, continue to reap the benefits of following Beane’s lead.
Looking further, across sports, we find the results have consistency in different situations.
