Everyone has that friend who takes fantasy football or fantasy baseball a little too seriously, poring over reams of data to select the perfect lineup for achieving vicarious glory. This is probably the same friend who spent summer vacations indoors as a kid, rifling through baseball cards and sifting through statistics rather than getting outside and experiencing the sport firsthand.
Now the jocks are stealing your math, too!
Everyone has that friend who takes fantasy football or fantasy baseball a little too seriously, poring over reams of data to select the perfect lineup for achieving vicarious glory. This is probably the same friend who spent summer vacations indoors as a kid, rifling through baseball cards and sifting through statistics rather than getting outside and experiencing the sport firsthand. When you go out on the town, a constant chime emanates from his smartphone as updates ping in at a rapid rate. Every few minutes he retrieves the device, fingertips clicking frantically as his eyeballs race through the information. Emotions fluctuate based on whatever numbers the screen spits out, a smile breaking or a grimace growing with each incoming update.
Numbers have always been a big part of sports. What has changed, though, is the way these numbers are being manipulated and used by people whose lives are enriched by the games they follow. Instead of merely showing us what happened in contests already concluded, the analytics of today are designed to offer predictive potential to the statistician who understands the wealth of knowledge to be gleaned from them. Both individuals and teams are working with an increasingly complex range of data to provide a more nuanced understanding of what is happening and what that might indicate about future results.
The explosion in statistical analysis began in 1977, when a factory security guard and aspiring writer named Bill James self-published his first Baseball Abstract and irrevocably changed the way numbers are perceived and processed in sports. By writing not about the action within the contests but rather pinpointing specific actions and analyzing their overall effect, James shifted the mentality of franchises, writers and fans toward a focus on the possible outcomes of a game well before the first pitch is thrown.
This predictive use of statistics—identifying those underappreciated facets of a game that can have a quantifiable effect on the win-loss column—has since become an obsession for franchises. After the 2003 publication of Michael Lewis’ Moneyball, which detailed general manager Billy Beane’s success employing nontraditional statistics to keep the small-market Oakland A’s competitive on a shoestring budget, other MLB clubs acquired their own eggheads to emulate Oakland.
Teams in other sports started to adapt this methodology to their own lineups, taking advantage of a new generation of high-definition cameras and data-collection technology to rethink roster construction and game strategy. It was the career path of one among this new wave of forward-thinking executives that led to the creation of the MIT Sloan Sports Analytics Conference—the preeminent symposium in the ever-expanding world of sports analytics and the vanguard for the push to expand
our statistical understanding of athletic success.
For years, Daryl Morey worked in the front office of the Boston Celtics and lectured at the Massachusetts Institute of Technology Sloan School of Management. But when the Houston Rockets tapped him to become the team’s new general manager in 2006, his relocation to Texas meant that he would no longer have the opportunity to lecture at MIT Sloan. So Morey worked with the school to create a two-day conference that would bring together sports executives, management students and number-crunchers for presentations and panel discussions about the growing role of analytics in the field of athletics.
The conference, originally held in a collection of classrooms on the MIT campus for less than 200 participants, has become an essential pilgrimage for thousands of stat geeks each year. At the seventh annual conference, held March 1 and 2 in Boston, MIT Sloan welcomed 2,700 attendees to the Boston Convention and Exhibition Center, with ESPN serving as the primary sponsor of the event.
With ideas disseminating between franchises and across sports boundaries, the analytics only become more complex as amateur statisticians and professional staff seek out the next underexploited facet of the games they love. “It is not just about hearing the preeminent ideas of the day,” said Zach Slaton, a writer for Forbes.com who has attended the Sloan conference the past two years, “it’s really about networking and getting access to the people you meet and the opportunities that come out of the conference.”
Therein lies the essence of this geek movement in sports. Rather than perpetuating the introverted-statistician stereotype, analytics specialists congregate at the Sloan conference every spring in culmination of another year’s work conducted collaboratively all across the country. Think tanks and private analytics firms come together to share the highlights and lowlights of their efforts to understand the true value of every action on the field of play.
These collaborations expand our knowledge of what is really happening on the turf, the court and the ice, trickling down from the teams themselves and writers like James and Slaton to the masses following along on television screens and smartphones. Because of events like the MIT Sloan Sports Analytics Conference, teams have discovered new ways to maximize their rosters—and your stat-junkie friends now have a new alphabet soup of acronym-stamped information to help their fantasies run wild.