Baseball is back, with spring training underway on professional fields and collegiate diamonds across the country. Yet the business of baseball remains a never-ending practice – and it is all about statistics. The numbers go way beyond earned-run averages, formulas for WAR better known as Wins Above Replacement, and all the computational twists that became the professional game’s norm via the “Moneyball” age around the turn of the 21st Century.
From ticket sales to schedules to promotions such as selecting a good night for a bobblehead, data and statistics are at the heart of Major League Baseball operations, and that’s why MLB and its teams rely on analytics experts such as Michael Trick and Jon Hay.
In December 2015 a crowd inside Mellon Auditorium welcomed Trick, Senior Associate Dean of Faculty and Research at the Tepper School of Business, and Hay, Manager of Ticketing Analytics for the Boston Red Sox and graduate of the University of Chicago’s Booth School of Business. They engaged the group in discussions about their experiences in applying their analytical backgrounds to the world of sports.
Ben Ganzfried, MBA ’16, organized the event to address a need to connect data-driven work to real-world situations and careers. In its third year as a Tepper School organization, the club saw a major upsurge in interest, with a 200-percent increase in membership over the past academic year. A popular question among this group: What kinds of analytics-related opportunities will be available to me during my career?
“Myself and the other members of the Data Analytics Club board thought that it would be educational and inspiring for our peers to hear from an MBA graduate and a faculty member who are doing interesting work related to analytics and optimization,” said Ganzfried.
So for one night, they were talking baseball.
Breaking down the data
Trick and his partners have been scheduling collegiate and professional sporting events for the past 10 years, while Hay is focused on the data behind ticket sales and promotions, serving in a position that did not even exist when he started business school.
“If you go back 10 or 15 years, people did not see the value in analytics,” Trick said. “But as data becomes more prominent and robust, the MLB is finding that analyzing that data and responding accordingly will help them be more successful.
“Even with the schedules, every team has a wish list, and we need to find a balance year after year in order to optimize the scheduling of games.” Not everybody can open or end a season at home, but analytics can help to secure optimal weekends or holidays to face archrivals or important series.
In addition to enhancing schedules, data impacts everything in the league from season-ticket sales to personnel decisions. Although Hay admitted that he has contributed to such baseball scouting and player discussions, neither he nor Trick work regularly in the “Moneyball” area of operations.
“One of the biggest changes is the use of big data and analytics in constructing a team,” Hay explained. “And even once players have made the team, they approach the analytics managers for data and statistics related to how they can improve their game.”
And while ticket sales, promotions, merchandise and concessions may not be the main driver behind Major League Baseball, Hay still considers conversations and data behind these profit centers to be imperative.
“Everything we do is to win – we are a professional sports team. Ticket sales and other profit margins are what fund our team and gives us the opportunity to win,” said Hay. In other words, analytics in hot dogs could help a team win the player WAR.
Keeping with tradition
In this age of Fangraphs and Baseball Prospectus as fan and media staples, Hay works for storied franchise that was the first to hire full-time the father of modern-day analytics used to dissect and diagnose the game on the field, Bill James. Yet it is all about the proper useage of statistics and computations in the business of baseball. In order to truly take advantage of the wide variety of data available to teams – from new analytics to historical data – they have to leverage how it’s applied in the MLB community and remain cognizant of their organization’s traditions and values.
The Red Sox don’t need a bobblehead promotion to attract fans to a Yankees game, and vice versa.
For any team to successfully leverage their findings, it is important to find a balance between using intelligent, data-based decisions, while still respecting the interpersonal dynamics of a situation or organization.
“I was particularly interested to learn about the mind-share between teams,” said Ganzfried, who hopes the next Data Analytics Club board continues to bring such valuable discussions to the Tepper School. “The MLB has a tight-knit community, and the teams seem to recognize that sometimes they can benefit from sharing models and helping each other.”