A Macalester senior is at the forefront of a major shift in how a football game unfolds. In the past four years, Benny Goldman ’16 (Goldens Bridge, N.Y.) has met with several NFL teams to discuss his analytic models—a method, and a network, that all started as a first-year student in his dorm room.

Goldman, who was also one of Macalester’s quarterbacks, used to dream of a coaching career. In high school, he spent a summer learning the NFL’s play-calling system. Through that early work, he began to form his own opinions about how coaches could use data to inform their play calls—the data just had to be collected and analyzed. When Goldman arrived at Macalester, the football player inherited the team’s analytics program, started by offensive coordinator Marc Davies and Joe Dykema ’14. It was a basic, time-consuming program with data entered into Excel the day after each game.

While he searched for a niche academically, Goldman spent time writing a script that automated the whole program, and he also developed and copyrighted his own playcalling system using a unique set of metrics and data from 10,000 NFL games. He began reaching out to up to 20 NFL people every day via LinkedIn, and finally the wheels were set in motion when the Philadelphia Eagles’ head scout called him and then later asked him to show the NFL team’s coaching staff what Goldman was working on. When another contact got hired at a different NFL team, he reached out to Goldman. Last summer, Goldman spent his days working at the Federal Reserve Bank and then worked nights and weekends on projects for the team.

While Goldman keeps the specific details to himself, his analysis adds extra layers to evaluating each play’s value. For example, a two-yard run on its own isn’t particularly significant. But when that play reliably helps a team convert a third-and-short situation into a first down that moves the team closer to scoring points, then that layer of analysis has uncovered one key to success—and potentially more wins.

This kind of evaluation is similar to the analysis adopted by baseball’s Oakland Athletics, a story depicted in the book and film Moneyball—but it’s slower to catch on in football front offices. “What’s holding back analytics in football,” Goldman says, “is that each play is a much harder math problem than baseball scenarios. In baseball, the pitcher and batter are basically in a vacuum. In football, there are so many more variables” that could explain data and situations.

As Goldman put together his program, he also found his footing in Macalester’s economics department when he took microeconomics his sophomore year. It was a lightbulb moment for him—”this is always how I’ve thought about the world,” he says—and a natural fit, too. He went on to be drawn to econometrics and pursue a math major, too.

Both his academic foundation and time in the football program have strengthened his analytics work. “The collaboration has been huge,” he says. “I can walk into an econ professor’s office with a question about models I’m using for playcalling. I’ve gotten an extraordinary amount of help from professors, as well as the coaching staff. None of this would’ve been possible without the coaches here. Macalester harbors and encourages a lot of uniqueness and creativity. That’s been refreshing to me.”

In addition to his economics and math majors, Goldman watched game film all fall to prepare for a new opponent each week. This year, he balanced that preparation with graduate school applications, with plans to pursue a PhD in economics. He hopes to become a professor and consult with football teams on the side.

And, yes, he still watches football on Sundays—sometimes, when he has time.

February 1 2016

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