Moneyball to the Next Level: How MLB Teams are Using Big Data

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by Jonathan Buckley

Simply mention the possibility of introducing a technological element into baseball, and most purists will shiver in trepidation. Baseball, after all, is America’s pastime, a sport that harkens back to a golden era where an afternoon at the ballpark was something everyone did. Major League Baseball has famously been reluctant to embrace high-tech changes to the sport, so when Moneyball became a phenomenon a decade ago, many were nervous about it. Moneyball is essentially the term (stemming from the book written by Michael Lewis) for using advanced statistics to determine how to build a team, what strategies to use, and more. The fact that Moneyball was such a success meant it was here to stay, but now many teams are taking it to the next level. This comes in the form of big data analytics. Just as it’s being used in other businesses, big data is utilized to make baseball teams better and organizations more profitable. Here are just a few examples.

Pittsburgh Pirates

The most obvious use for big data is to improve the on-the-field product. That’s what the Pittsburgh Pirates had in mind when the organization finally decided to embrace big data. After 20 straight years of losing seasons, it was probably a case of “what have we to lose?” As detailed in the book Big Data Baseball: Math, Miracles, and the End of a 20-Year Losing Streak, the Pirates took big data analytics and fully ran with it. That meant hiring the best big data analytics experts available and using their skills to integrate defensive shifts, pitch framing, and two-seam fastball usage. The result, as seen in the title, was a total turnaround after decades of failure. The Pirates managed to get to the playoffs this year (though they ended up losing in the NL Wild Card game).

Houston Astros

When the Houston Astros decided to adopt big data solutions, their goal was to improve in their evaluations of players. The Astros, much like the Pirates, were a bad team, and they decided to build up from scratch by following wherever the data led them. The result was the collection of a massive database of detailed player statistics. Though the Astros suffered many losses at the outset, their use of big data allowed them to draft well, spend money where it would be more useful, and craft a team ready to compete. The improvements were so great in such a short amount of time, that the Astros were able to make the playoffs this year, even knocking off the mighty New York Yankees in the AL Wild Card game.

Milwaukee Brewers

Improvements that come about through big data don’t just have to be seen on the baseball diamond. The Milwaukee Brewers are using big data tools like Apache Spark to get people in the seats. The goal was to look at people who attended sporadically and try to turn them into season ticket holders. Big data is used in marketing tickets to people, finding out what they like and appealing to their preferences. The Brewers also analyze every single email they get from fans so they can build a more accurate picture of who each fan is and what drives them to act. All these steps lead to different strategies for how to attract customers to the product, something the Brewers have been very good at doing in recent years.

Boston Red Sox

The Red Sox also look for ways to keep fans coming to Fenway Stadium. Not only do the Red Sox use the same kind of analytics strategy that the Brewers do, they also use big data to find ways to improve the fan experience while at the ballpark. The organization collects data on what fans purchase, which concession stands they visit, when they buy food, what kind of food they buy, and much more. The Red Sox have basically been able to create a concession “heat map” of sorts to track fan behavior. They hope to be able to use this information to keep fans better informed of where they can find their favorite treats.

While the baseball purists might be uneasy about how big data is influencing the game, it’s a trend that won’t be going away anytime soon. The evidence shows big data is helping teams succeed both on and off the field. Change can create uncertainty, but traditionalists shouldn’t be so quick to dismiss the good that the next level of Moneyball can do.

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