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March 1, 2012
Why We Use Stats
For Love of the Game

by Kevin Pelton


SOMEWHERE BETWEEN SEATTLE AND BOSTON - Every year at this time, as I travel to Boston for the MIT Sloan Sports Analytics Conference, I find myself reflecting on the statistical analysis community. I'd usually prefer to, y'know, talk about basketball, but sometimes this kind of big-picture thinking is instructive.

In the four years I've been traveling annually to Sloan, I've seen it grow from a sleepy get-together of industry insiders and academics to an event that is live streamed and broadcast worldwide thanks to ESPN. Besides the influence of Bill Simmons, I am at a loss to entirely explain that transformation, but I do have a good sense of why those of us who were interested in statistical analysis long before it became big business always highlight this weekend on our calendars.

Gathering in Boston is a chance to catch up with email friends we see in person only once or twice a year, certainly, but more than that it's an opportunity to feel at home among like-minded individuals. This is, I suppose, a natural human response, but in practice it's more about the opportunity to tell a joke about Antoine Walker's shot selection and have everyone instantly get it. There's a sense that, though we are scattered throughout the country and utilize statistical analysis in myriad different ways, we're all speaking the same language and looking through similar lenses.

There's a danger in that, of course. There's a thin line between defining ourselves as a group and defining others who don't belong. That's a natural human emotion, too, but one that's responsible for the vast majority of the tragedies of human society.

Recently, SBNation.com's Jason Concepcion (aka Netw3rk, if you're on Twitter) spotlighted this divide between NBA elitists and the league's casual fans. To the extent Concepcion overreached in his column, I thought it was with the notion that the only interactions between the two groups are public and hostile. We have friends; we have coworkers; we have families. The people I hang out with on a day-to-day basis may be more aware of the advanced stats movement because I force them to read my books, but if we're dividing up NBA fans they belong in the 99 percent. And yet we still manage to converse about the league. (It helps that we rarely seem to call each other names, except my brother and I, and that's been going on since long before I cared about stats.)

There's a way to discuss basketball that is informed by statistics but not necessarily driven by the statistics. I'd say this is the approach I have taken in my day jobs covering the WNBA's Seattle Storm and formerly the SuperSonics, writing for a broader audience than I'd expect here on Basketball Prospectus or even at ESPN Insider (where, at the least, using analytics is our niche).

Today on TrueHoop, Henry Abbott states a solid case that this task may be achieved more easily with the use of video, which conclusively relates the numbers back to the plays that generate them. As Abbott points out, really most of what we're doing is counting things that actually happened. In that sense, statistical analysts are really historians as much as mathematicians. We seek to use past results to try to determine what might happen in the future.

Put this way, I suspect it's a lot more difficult to hate statistical analysis, but it is still possible to root against it. On a recent BS Report podcast, Chuck Klosterman theorized that part of the reason the Tim Tebow and Jeremy Lin stories have become the kind of phenomena they have is because fans are attracted to the notion that the rise of the two players can't easily be explained by the numbers. In a sports world that now feels more black and white, Tebow and Lin offer a contrasting vibrant color.

In the case of Tebow, the battle lines were drawn more sharply. At least initially, NFL analysts were skeptical of whether the Denver Broncos could keep winning with Tebow passing so inaccurately. When the Broncos, and Tebow, triumphed again, it was clearly a case of the underdog overcoming the skeptics. (Eventually, I think the NFL's analytics community tended to be more open to Tebow making a difference as a runner than the media at large.)

The Lin story is stranger in that some statistical analysts have turned him into an example of what can happen when outside factors (including, but not limited to, his race) are weighted ahead of actual performance. I'm a bit more hesitant to make this claim. I had Lin rated as a draft pick--a first-round pick, even--but not far ahead of another accomplished four-year point guard in the 2010 Draft, Duke's Jon Scheyer. Scheyer has yet to make an NBA roster. Beyond that, what Lin has accomplished as a starter far exceeds what his numbers suggested; in a real sense, he is no longer the same player he was at Harvard.

More than anything, I think Lin taps into the excitement and sense of wonder that makes us all--statistical analysts and casual fans--love this game of basketball. The last thought-provoking piece I read recently was from past Prospectus contributor Kyle Whelliston, who tried to figure out whether he truly loved basketball, or the experience of writing about it. Ultimately, Whelliston found the latter the stronger draw.

I've never tried giving up hoops, but I already know the answer in my case. Not writing about the game would be painful because writers have a compulsive need to write, both to get our opinions across and to organize them in our own heads, but I don't have the same pull with anything else in my life. Something similar is true of my interest in statistical analysis. It starts with the love of the game, not the love of the numbers. Using statistics is, as Abbott explains, a tool to understand basketball better--and one of many.

In my opinion, that's where the dividing line is truly drawn: Not between those who use stats and those who don't, but between people who are interested in learning more about the game and those who are not. There's nothing wrong with being on the other side of the divide. Like Bill Simmons replied to Klosterman about hockey, I wouldn't take a pill that made me know everything about soccer even if I could. Sometimes it's nice to follow a sport casually instead of obsessively. At the same time, using statistics alone is not sufficient evidence that someone is really intellectually curious about basketball. Believing that the numbers are all that matter is just as closed-minded as finding them totally worthless.

So why do we come to Sloan? To chat, to catch up, to discuss but most of all to learn. (Oh, and also to see Linsanity in person on Sunday.)

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Kevin Pelton is an author of Basketball Prospectus. You can contact Kevin by clicking here or click here to see Kevin's other articles.

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