#SSAC16 Day 1: Where I both wonder what I’m doing here, and remember why, in the same day

Good morning! DataGEEK here.

The MIT Sloan Sports Analytics Conference is in its tenth year, but it was my first time attending. So I had no idea what I was getting into before the event started. In the span of just a few hours, I went from feeling overwhelmed and out of my depth, to remembering exactly why I love this industry and why it interests me so much. I was able to gain some insights and come away with some conclusions, so that’s what I’m going to talk about this morning.

Conclusion 1: Who Knew That Company Did Sports Analytics?
As I write this, Day Two of the conference has begun, and right now, Noah Fischbach, of Gracenote, is participating in the #RiseofBigData panel. Obviously, Gracenote has been involved in big data for a long time with music. But Fischbach’s background includes the NFL and Fox Sports, so his position is not really part of the music side.

Similarly, Booz Allen Hamilton is taking what they’ve learned in supporting the Department of Defense, and applying it to sports. They seemed to be more in the “we want to be involved” phase rather than actually in sports, but I still didn’t expect to see a a defense consultant company here in Boston.

Conclusion 2: A “Sports Analytics” Conference Is Very Specific, But Also Very Broad
Daryl Morey, who you probably already know is the current GM of the Houston Rockets and co-founder of the MIT Sloan Sports Analytics Conference, mentioned in the opening remarks yesterday that the first conference was called “Sports Business” rather than “Analytics”, and that he thought the change was a very good decision. He’s probably right. But the scope of this conference is impressive.

Sports Analytics, based on what I’ve seen here, includes analyzing individual performance, including both from a skill perspective and sports science as well, and analyzing team performance. But sports businesses also analyze social media, fan interaction, and season ticket holder retention. All of that is represented here as well.

Conclusion 3: The NHL is Behind
Due to scheduling, I wasn’t able to attend the panel on NHL analytics. But I didn’t need to be there to come away with this conclusion. The playful title alone, “Out of the Ice Age”, was a pretty big clue. In addition, several other conference attendees mentioned, completely unprompted, that the NHL was noticeably behind other leagues and sports in terms of analytics.

Part of the problem, in my opinion as a complete outsider, is how unique the game of hockey is. Sports analytics is essentially derived from the work of Bill James in baseball. So most of the other sports have created analytics based on that sport’s similarities to baseball. And the most important piece is being able to recognize a positive or scoring play. Football teams are rewarded for moving the ball down the field and gaining first downs. Basketball teams have points per possession and tempo.

Hockey? It combines the low scoring of soccer (which I hear is similarly behind), with the possession time and tempo of basketball. So how can you tell when a team has improved their possession or position without scoring? I’m sure there are ways and that people are doing it, but I respect the challenge.

Conclusion 4: The Cleveland Browns are in Good Hands
Finally, and this is probably coming from a place of Ohio bias, I’m going to come away from this event more of a Browns fan than ever before. Paul DePodesta participated in two panels on Day One, the amazing #MoneyballReunion, and a later talk on Leadership. In both forums he was extremely impressive and gives me hope for the future of the Browns.

Since his hiring, my argument has been that the Browns finally have a vision and a plan. The entire front office is now analytical, and that shared vision is definitely a positive as a fan. But hearing him in person was even better than I imagined.

Later this weekend I’ll be posting more thoughts on Day Two of the conference. Until then, GEEK out!