BOSTON -- The MIT Sloan Sports Analytics Conference means different things to different people. For some this is an incredible opportunity to learn more about sports, the events and actions that our eyes miss, and those our brains misunderstand. For others it draws images of torturous high school calculus classes and of unwanted information, slowly leaching the fun from sports.
Shrinking the space between the analytics community and the "average fan" has been a thread through this entire event. Multiple panels and presentations have found themselves circling the idea of why that gap is closing, the rate at which it’s closing, how to speed up the process and whether it’s possible to close the gap completely.
TrueHoop at MIT Sloan Sports Analytics Conference
In the "Box Score Rebooted Panel," Bill James coalesced the mission of the analytics community as reducing a mountain of data to the simplest possible concepts. The exact degree of that simplicity varies with the concept, but it’s a beautiful idea. Simplicity of concept in statistical analysis would seem to create the most useful assessments and allow for the most effective communication of those results.
For the most part the themes with a basketball slant presented at Sloan -- "fit," "space," "physical performance," "pressure," "chemistry" -- are foundational enough for even the most casual fan to interact with. However, the vehicles for discussion used here at Sloan are largely inaccessible and decidedly unpalatable for large swaths of sports fans.
My day job is teaching first grade, and this year we’ve been working with an incredible math consultant, re-thinking everything about our instruction. One of the ideas that drives this effort is "language containers." The premise is that human language has evolved into a means of capturing ideas by providing containers in which to place a concept. To fully and completely master a concept you must understand all the language that defines and informs that idea.
For example, to be entirely fluent and comfortable with the concept of subtraction your language container must include: "take-away," "less than," "smaller than," "fewer," "deficit," "debit," etc.
To understand the concept of usage rate, you have to build a language container that includes the definition of a possession. The concept of a possession, in turn, requires its own container, built on the understanding of the ways a possession can be used. This endless stacking of knowledge upon knowledge can’t be fully completed until each previous layer is filled in entirely. Language containers have their place with every concept, and basketball analytics is no exception.
I work with statistics quite a bit in my basketball writing. To me, they help bring order to an otherwise chaotic jumble of action. For all my self-taught statistical knowledge, there has been plenty in the research presentations I’ve viewed this weekend that went over my head -- in some cases way, way above my head.
I’m comfortable with many of the conclusions, but not being comfortable with the language of Voronoi Tessellations or the Z-Plane means to some degree I’m simply taking the presenter at his word. This is the same experience someone who hasn’t finished building a language container for possessions has when reading an article that uses Offensive or Defensive Rating.
The past two days, every corner of the Hynes Convention Center has been filled with conversations on sports. Those conversations bridge the same concepts as conversations held in bars, living rooms and backyards -- How does my team get better? Which players should my team pursue in free agency? Why can’t Player X stay healthy? But the conversations here use different words, terms and visual representations; a lexicon that has evolved separately, distinctly and quickly.
I refuse to believe that any sports fan doesn’t want to know more about the games he or she loves. The challenge then in disseminating data and analytic methods, and in obtaining acceptance for the results, is not a conceptual challenge, but a problem of language.