Stats 101: Why Statistics?

Happy New Year everyone! Hope everyone had a great January 1st. Missed the DEN and POR games; from what I gather, Tyson Chandler got in a fight, and David West was awesome. Business as usual. Oh, and thanks for holding down the game threads. Now... it's back to real business. Namely, statistics. Long time readers of the blog know of my propensity to use stats in my write-ups. This season, we've had a sizeable increase in readers (and lurkers). So I figure now's a perfect time to start a little series on stats.

This first one will just be a small intro, covering two items, starting with...

Why Use Statistics?

Let's start with the most simple explanation: there are too many games to watch. 30 teams, an 82 game season, 3 hour long games, 5-10 games a day... it's simply too much. I've already missed three Hornet games this season out of 30, and I'm supposed to be writing amateurishly professionally about them. There's simply too much going on in the course of a season for one person to reasonably follow at every instant.

Second, it is human nature to seek out patterns in everything we do. In terms of watching basketball, this works against us. We want to find some sense of order in what we see in front of us.  I might see Paul Pierce play twice in a month and watch him hit game winners in each game. Maybe I come to view him as "clutch." What I fail to see is all the shots he's missed when I wasn't watching, all the times he turned the ball over, all the times he got beat on defense. It's really easy to associate disparate and isolated instances with a player's "true" value. Once we come to see a player in a certain light, viewing that player in any other way becomes difficult. His mistakes come to be seen as aberrations, his positives serve to reinforce the original opinion.

That last point segues into the concept of "flashiness." The flashier a play is, the more attention it will get. The more consistently flashy a player plays, the more attention he will draw in general. It seems obvious, but it happens to all of us. A guy that toils night after night on the glass is going to get less air-time than a guy who can occasionally hit a long three and bust out something like this. In that last case, "occasionally" means 34% of the time, by no means a world-beating figure. But you wouldn't know it from that "gun" toting pose, would you?

Numbers don't care that a player poses and preens after a made three. Numbers take into account every minute of every quarter of every game of every season of every player. But Numbers is a vague term, which brings us to...

"Good" Stats and "Bad" Stats

You've no doubt heard the phrase "Statistics can be made to prove anything." Or "Lies, Damned Lies, and Statistics." Or some variation of the two. Both of those are true. I could probably invent a stat proving that Brian Skinner is the best player in the NBA. It'd have to involve the length and color of one's goatee... but it could be done. Point is, how can we determine the legitimacy of a statistic?

Easy enough when you remember why you're doing all this. In any game of basketball, there is only one objective- WIN. Not pile on stats, not score a lot of points, not anything, but win. The definition of a good statistic can thus be based on this concept. Which stat correlates most to winning? Which stat leads to winning more than any other? That is the fundamental question. On a simple level, this can be answered by summing a specific statistic for each of a team's players and seeing how well that sum statistic predicts team wins. It's a little more involved than that in reality, but in essence that's what must be done.

Let's end with this. It stands to reason that a "good" stat must take into account more than a single box score stat (pts, asts, rbs, etc.), right? It always seemed really funny to me when commentators struggled to explain why Denver was so mediocre despite having a 29 point scorer (Iverson) and a 28 point scorer (Melo). They, like MVP voters and 99% of fans, make the automatic assumption that the points scored statistic is a good indicator of winning. It's not. Points scored is an awful indicator of success, as are quite a few other stats traditionally associated with winning. What are the good ones? Over the course of this series, there'll be much more on good stats, as well as how defense can factor into all this.

For now, we've established the meaning of a good statistic.

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