For many kids, the dream of playing professional sports drives athletic careers. Yet for most people the dream does not work out. Recently, however, a number of Harvard alumni have been blazing a trail for an alternative route to the big leagues: using statistics and skillful networking to place them in the front office of major sports organizations.
Two recent graduates, Jason Rosenfeld ’12 and Daniel Adler ’10 have started to implant themselves in the front offices of teams in two of the biggest sports leagues in the world: the NBA and the NFL. Rosenfeld is the Manager of Basketball Analytics for the Charlotte Bobcats, and Adler is the Assistant Director of Football Research for the Jacksonville Jaguars.
Both are living their dreams, continuing a passion they developed at Harvard while a part of the Harvard Sports Analysts Collective (HSAC), a popular sports analysis club on campus. Other members of HSAC have worked for the Phoenix Suns of the NBA and the Dallas Cowboys of the NFL, as well as other teams and sports-related companies and organizations.
The statistical movement in sports started with baseball. In 1977, Bill James, a janitor who spent his spare time analyzing baseball statistics, published his work and created what is now known as sabermetrics. While at first many people involved in the industry of sports were skeptical, claiming that conventional wisdom trumped the power of statistics, James’ method slowly gained traction throughout the baseball world.
Michael Lewis’ novel Moneyball—published in 2003—tracked the Oakland A’s, a small-market team that managed to make the playoffs through the brilliance of a statistically-inclined general manager and an artfully crafted low-budget team. The book was so influential that it was turned into a movie, starring Brad Pitt, in 2011.
But baseball, based around one-on-one matchups between a batter and a pitcher is much more constrained, and therefore lends itself to more extensive quantitative analysis. Even before James’ statistical revolution, stats like batting average, home runs, and runs batted in have been tracked for well over a century and been part of the sports parlance. But more free flowing sports like basketball and football don’t lend themselves as easily to recording meaningful in-game stats.
“It’s important to keep in mind how much more complicated basketball is than baseball,” Rosenfeld said. “You could create a formula to give you a number [that represents a player’s effectiveness] and that may be effective in baseball, but it might not be nearly as effective [in basketball].”
Take, for example, a touchdown in football. The running back or wide receiver-quarterback tandem gets credit for a TD, but the result is not completely dependent on their play. Offensive lines, other skill players, and play calling all have a role. Similarly in basketball, a basket is generally not scored by the sheer power of one player, but by a symphonic union of five who each influence the play on the floor.
“On any given play [in basketball], if you are trying to figure out what’s good or not, you have to divide credit, and that’s going to be hard. It’s a lot more complicated,” Rosenfeld said.
For this reason, the statistical movement has only recently entrenched itself in these sports. But recently teams across the league are beginning to realize the value added by these analytical thinkers. All the way up to the general manager position, teams are turning to guys who analyze numbers for advice.
“[In] basketball, it’s really the past five-to-ten years where [statistical analysis] has been really mainstream,” Rosenfeld said.
In 2007, Daryl Morey, a former computer science major out of Northwestern University and graduate of the MIT Sloan business school, became one of the first general managers who got to his position by fully embracing sports analytics. He is still the GM for the Houston Rockets and also co-runs the annual MIT Sloan Sports Conference.
While the nature of both Adler and Rosenfeld’s jobs are secretive, the general area that they influence their teams in is through draft analysis along with in-game scenario decision making.
“A lot of the stuff revolves around [game] decisions like if on fourth down, whether to punt or go for a field goal,” Adler said.
In 2005, political economy professor David Romer of UC Berkeley published an article entitled “Do Firms Maximize? Evidence from Professional Football,” which concluded that coaches often tend towards conservative choices that—at least from an analytical perspective—do not provide the best opportunity for winning.