A few weeks ago my friend Nick sent me a link to this epic 12-part series on Dennis Rodman’s basketball prowess. While Rodman has been in the news for some interesting reasons lately, prior to that he was a basketball player unlike any we’ve ever seen and this series sets out to prove the point. I was especially part of part 2(a)(i) on “Player Valuation and Conventional Wisdom,” which has a nice explanation on the battle between the eye-test and math-test in sports:
Yet chances are he remains skeptical of the crazy-talk he hears from the so-called “statistical experts” — and there is truth to this skepticism: a typical “fan” model is extremely flexible, takes many more variables from much more diverse data into account, and ultimately employs a very powerful neural network to arrive at its conclusions. Conversely, the “advanced” models are generally rigid, naïve, over-reaching, hubristic, prove much less than their creators believe, and claim even more. Models are to academics like screenplays are to Hollywood waiters: everyone has one, everyone thinks theirs is the best, and most of them are garbage. The broad reliability of “common sense” over time has earned it the benefit of the doubt, despite its high susceptibility to bias and its abundance of easily-provable errors.
Felix Salmon gives his take on what really made Nate Silver such a phenomenom: First, he can explain complicated math simply and second, he gave people fodder for conversation. Felix explains:
The thing that Silver and the Obama campaign have in common, then, is that they used their databases to tell stories. Or, more to the point, their databases and models were used so that Americans could tell stories to each other. Silver’s site became a virtual watercooler, especially towards the end of the campaign — a place where people would gather to talk about what was possible and what was likely. Nate’s voice helped to guide the discussions, but the real reason that he got such astonishing traffic was not that people wanted to read what he was writing, so much as that people were using his model as a framework within which to hold their own idiosyncratic discussions.
Now I’m not sure that this is really unique. People consume, at least in part, to talk about what they read. This is especially true in the realm of politics as evidenced by the nonstop conversation over the last three months. But I still think Felix is very right and it’s interesting to think about the role of statistics here. Are statistics actually better conversational fodder than punditry because they still allow the reader to make observations and decisions? Not sure, but I like the thought.