It feels strangely appropriate that the biggest lesson I learned from attending the MIT Sloan Analytics Conference was something that works more as a reformulation rather than a genuinely new lightning bolt of knowledge or experience. The title of the event uses the word analytics which just so happens to be one of those concepts without a truly clear definition. While on the Basketball Analytics panel, Stan Van Gundy periodically derided those who treated sports like a “video game” and ignore some of the human elements of the sport. Of course, he usually followed those up with a profoundly analytical statement that showed this gulf of understand.

The best way I can articulate the concept of sports analytics is as follows: the willingness to consider or use any above board concept, strategy, or function with the goal of success, however success is defined in that context. Championships stand as the pinnacle on the personnel side of course, yet there were excellent presentations on fields like sports business, ticketing, and sports gambling which do not have that type of goal.

In this current world of sports, every entity has multiple objectives that can either run together or in conflict over the short and long terms. One particularly interesting example of this was the presentation by the season ticket guru for the Orlando Magic who discussed the negative impact the J.J. Redick trade had on renewals for the 2013-14 season. Management made the correct decision to move the player, but it had real consequences on their bottom line.

In fact, some of my absolute favorite concepts and exchanges had little or nothing to do with the scarlet S for stats the group gets labeled with sometimes.

On the very first panel of the conference, Mark Cuban and Daryl Morey engaged in a discussion on team psychologists (with plenty of thinly veiled references to Rockets draftee Royce White) that got both heated and entertaining. Numerous panelists opined on the challenges of player development and the methods teams can utilize to get the absolute most out of the individuals they have on roster.

Mike Zarren, Assistant GM for the Celtics, talked about how each player needed to get information like video and stats in their own way, whether that be the media itself (paper stats books, video) or even the format the player would look at it (DVD’s, paper, or iPhone/iPad). His comments echoed the “whatever works best” ethos that typified the convention. However, it must be noted that everyone from ownership to management to the players themselves can and should continue to improve themselves and the organization with an eye towards what’s next.

One of my absolute favorite comments came from Stan Kasten, the new President and CEO of the Dodgers. He acknowledged the difference in experience between attending a baseball game and watching one on TV while noting that the team is working on using smartphones to enhance the live experience in ways home viewing cannot duplicate. In sports like baseball and basketball, the large amount of home games necessitates movement in this direction, especially as league-affiliated programs like MLB.tv and NBA League Pass make it easier to be a fan without attending games live.

Keeping all of that in mind, plenty of the other lessons from the Sloan Conference came from the stats and tech. While only 15 teams have the cameras (and not all of them share the data), we are already starting to see the amazing data generated by the SportsVU technology. As someone both incredibly into defense in basketball and incredibly frustrated by how poorly we can use numbers to quantify and explain it, the early stage research has already yielded some fun returns.

The Dwight Effect, written by Kirk Goldsberry and Eric Weiss centered on how big men affect the game defensively in terms of both shots taken and their likelihood of going in the basket. While analysis of defense in the NBA requires plenty of context, the data and analysis here does paint a picture of value and usefulness we have had trouble with previously and can continue to refine and explain. Another presentation on acceleration by Philip Maymin (available at the same link) provides a potential spark for some real innovative understanding of how the league functions and stands as another example of where we can go with SportsVU with more time and even more data points.

As someone interested in all of the major sports, one of the most fun parts of Sloan was seeing how each sport stands at a different place in terms of both what data is captured and how it can be used. Baseball’s foundation of a pitcher/batter sequence allows for a different level of insight through numbers and we still have plenty to learn there. Basketball seems next on the list, though that may be only because of how daunting football can be in terms of in-depth analysis. Hockey’s challenges appear even harder though something akin to SportsVU could go a long way towards separating out the pieces that can be quantified.

Regardless of all these limitations, the big lesson from Sloan is that we need to be both broad in our vision of what to consider and skeptical of every piece of insight that comes our way regardless of the source. As long as sports continues to be both big business and a major source of interest and discussion for people around the globe, there will be conferences like Sloan with brilliant people engaging in high-level discourse, and I for one am overjoyed to see where this all goes.