"Statistics are like bikinis. They're really nice to look at but they don't tell you the whole story" - Brent Barry, former NBA player
Alright, so enough about operations. Why am I really here?
I first read about the Sloan Sports Analytics Conference a couple years ago in a Bill Simmons column on ESPN.com. It's an event where a bunch of people in sports, media and academia get together to talk about all sorts of topics related to the business of sports. Specifically, one of the main goals of the conference is to have a forum to discuss the role that data analysis is increasingly playing in sports. And, as Brent Barry was getting at in his gem of a quote above (which might be stolen), the conference is also meant to help answer the important question of how to balance data analysis with the more "gut feel" type measures that make sports so appealing to follow.
The conference is only a few years old but already one of the premier events at Sloan. In addition to the Sports Guy, the 2011 conference (March 4-5) will include Malcolm Gladwell, Mark Cuban, Jeff Van Gundy and a lot of other big names. Last year Michael Lewis moderated the keynote panel, which also included Bill Polian and Jonathan Kraft.
Sloan students play a major role in putting together the conference. We work very closely with the two co-chairs, Daryl Morey (a Sloan alum and currently GM of the Houston Rockets) and Jessica Gelman (HBS grad; currently VP of Consumer Marketing & Strategy for the Kraft Sports Group). There are a lot of ways for us to get involved, from helping organize the logistics of the event to planning and coordinating the different panel discussions.
As part of the conference, people from the academic and business world also submit research papers on different sports analytics topics, which is the part I'm most directly involved with. We're currently going through this year's initial round of abstract submissions to determine which we think should submit final papers and perhaps present at the conference itself.
It's really cool to read about all of the new ways that sports-following nerds are trying to analyze sports data- everything from owner economics to selecting the best fantasy teams to better ways to analyze player performance. The analytical rigor of the papers also varies significantly, from relatively simple regression analysis to all sorts of complicated math that I don't understand. Last year, the paper that made the biggest splash was one that improved upon the adjusted +/- technique to analyze NBA players (check it out). I think in just a year a lot of NBA teams have adopted it or are looking to use it.
This year the number of submissions is up pretty substantially from last year. We definitely have a lot of cool ideas, which should make for some interesting and popular presentations at the conference. I think that order for a paper to have widespread appeal, it needs to be unique and analytically sound, though not so complicated that someone without a PhD in statistics can't understand the basic idea.
Stepping back a bit, it's obviously not easy to decide what activities you should get involved with and how much time to devote to them, because there is so much you can potentially do here. Should you spend time on activities that will help you find a job, things you're generally interested in, or both? I think it's worth exploring a lot of different options, but ultimately deciding on a very small number of things that you can actually devote time to. This conference is a no-brainer for me, just because it's such an interesting topic. I don't know if I'll ever pursue a career in sports, but I think it'll be an awesome experience regardless.