THHB Interview with HOOPDATA

We have to admit that, despite our educational epicenter (University of Florida) and the fact that whenever we try to use statistics to make a point, it's like listening to Carl Lewis singing the national anthem, we love the way that basketball is beginning to embrace the discovery around advanced mathematical analysis and using it to understand what's going on in the game.

We have long been enamored with the work of Bill James in baseball, and love to read Football Outsiders and their breakdown of the gridiron. We even offered our services to John Hollinger when he was scribing Basketball Prospectus and wasn't the ESPN branded guru as yet.

So it seems obvious then that we would be in numerical intoxication with the advent of Hoopdata (after being brought to our attention by their use in the Hoopinion recaps), a palace for advanced statistical basketball analysis, highlighted with their day after box scores complete with Usage Rate, Rebounding Rate, and Points Created/Points Used and their sortable database which makes our usual shoddy research more credible. In fact, we were in so deep this morning diving into the stats and fuming about Al Horford's criminal underuse that we failed to note that Josh Smith was one steal shy of a 5 X 5 which, while being part of the old style of box score, is an impressive feat nonetheless.

From their About Us, Hoopdata was launched in October 2009 and is dedicated to making basketball statistics more accessible and understandable for the common fan. It was founded by Joe Treutlein, who has some extensive basketball background listed in his bio, and it was he who THHB tracked down and was gracious enough to allow us a few questions so we can get to know him, his partners, and their site.

What is the origin and purpose of Hoopdata?

Hoopdata was basically born out of me playing around in excel with a bunch of numbers and realizing that all of the advanced stats sites out there were missing a few crucial features (namely league averages and sort options). From there, I talked with Matt (Nolan, co-owner, programmer, and analyst) about getting the numbers online, and we then figured out with his programming skills, we could also parse play-by-play information to record stats that aren't available anywhere else. Everything else really grew from there.

Are there any mentors or inspirations behind your work?

Mentors, no, but there's no denying that all the work we do is heavily influenced by the likes of John Hollinger, Dean Oliver, David Berri, and all of the great members of the apbrmetrics community. Funnily enough, though, I don't really consider myself a stats guy. Phil Jackson and Dean Smith's books have probably had a greater impact on my perspective of basketball from an analytical standpoint, for example.

Is this a full time job, full time passion, or both?

For me, it's part of a full time passion, which is the analysis of basketball, something I intend to make my career, and have been working towards for the past five years through my work at DraftExpress and Synergy Sports Technology. As for full time job, it's a good deal of work, but not to the point I'd call it a full time job, and I don't think either of us ever plan to make this a primary source of income.

What’s the most important thing for readers to understand about Hoopdata?

We're just trying to give our readers as much information as possible to be used for analyzing the NBA, and present it in a format that is highly accessible and easy to understand. The important thing to remember, though, is that basketball is a highly contextual game, and stats only tell a small part of the story. I think using our site is a great way to supplement what you see on the court, but statistical analysis will always be just that.

Where do you see the future of statistics and basketball analysis?

The NBA is a copycat league, and as teams like Houston continue to have success with their 29 million dollar rotation that has no lottery picks, just one former lottery pick, and only two players making the league average salary, eventually teams will catch on and try to emulate their decision-making. That said, while plenty of teams are likely to devote more efforts to statistical analysis in the near future, there will certainly be those that stubbornly leave themselves behind, and probably just as many who will misuse statistics in their attempts to emulate, leading to failure.

THHB thanks the entire Hoopdata team for their work and Mr. Treutlein for his time in responding to our questions. We wish them all the best in their efforts and look forward to their future work and features.