![]() The intersection of data analytics and professional sports went mainstream in 2011 with Moneyball, the Oscar-nominated film starring Brad Pitt and Jonah Hill chronicling the creative tactics employed by Oakland A’s general manager Billy Beane in 2002 to field a competitive team despite having a budget of $39.7 million-less than a third of the Yankees’ $125.9 million payroll, and third-lowest in the league.Īn archetypal David vs. In recent decades, presumably after getting familiar with data’s equivalent of the Dewey Decimal system, baseball managers have been utilizing the numbers with increasing efficiency. But just because you have a library card and like to read doesn’t mean you’re checking out the best books. Pro baseball managers have long appreciated data and the fountain of useful knowledge it provides. But surprisingly, the three major American sports don’t appreciate this resource equally. Thankfully, this magical resource is real. Perhaps a better question: Would you ever stop worshipping at its altar? ![]() Now, imagine you learn of a magical, growing, rich, and plentiful resource that taught you lessons from history, statistics, probability theory, mathematics. A total nightmare.įurther imagine that nothing is expected to change in the coming year, and that the ownership group, in its boredom and desperation, has offered you enormous rewards if you can figure out how to win with relative consistency over the coming years. Playoff outcomes were determined by coin flips. Total parity: The year before, every team was. ![]() Imagine you’ve been thrust into a league with the exact same level of talent on every team. MLB, NBA, NFL-take your pick, the sport itself is irrelevant. Ironically, the evolution of the game they play has been painfully slow.ĭata: A Rich Resource Giving Sports the Option to Evolve.Īssume you’re the general manager of a major U.S. Roughly four dozen elite athletes whose physical bravado is the product of millions of years of evolution and natural selection. Two hundred million eyeballs-and that’s just in the U.S. The game, as far as the data is concerned, is being played the wrong way. But sadly, their talents are being misused. The NFL boasts some of the best athletes on the planet, putting on a show for the world to see. The kick returns, the tiptoeing around defenders, the swim move that leads to a sack, or the jumped route that leads to a game-changing interception. When the two best NFL teams face off in Mercedes-Benz Stadium in early February, we can rightly marvel at their athletic feats on the field. ![]() sports leagues-Major League Baseball (MLB), the National Basketball Association (NBA), and the National Football League (NFL)-the NFL has been the one most reluctant to adapt. At the top of the pyramid, senior to everything else, is data. It’s not squat reps or glasses of milk that separate the wheat from the chaff over a decade or more. But no team can expect that talent to be there for the long term. To be sure, athletes tend to get bigger, faster, and stronger over time, but as any longtime sports fan knows, even a team that’s skilled on paper is bound to disappoint more often than you might expect.Īll things being equal, it certainly helps to have skilled players on your squad. Routinely the most-watched television program of the year, over 100 million Americans will tune in to see some of the finest athletes in the world square off against each other in a battle of brawn, speed, wit, and-hopefully-analytics. On February 3, Super Bowl LIII will be played in Atlanta, Ga.
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