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Basketball's new math

As in baseball, NBA starting to embrace stat science

Posted: Friday October 21, 2005 12:51PM; Updated: Friday October 21, 2005 12:51PM
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Dirty-work players like Golden State's Adonal Foyle, who doesn't rack up huge stats, benefit the most from basketball's sabermetrics.
Dirty-work players like Golden State's Adonal Foyle, who doesn't rack up huge stats, benefit the most from basketball's sabermetrics.
AP
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Regardless of your height, physical condition or jumping ability, there is one thing you could do in the NBA right now: rebound a missed free throw. Especially if the other team is already running back on defense.

Just stand there, watch the ball bounce off the rim and catch it. If you liked, you could slap it from one hand into the other to make the act look more emphatic, but this would be optional. Do this seven times a game and you would be considered a good NBA rebounder, at least statistically.

That's why conventional NBA stats are misleading. Houston head coach Jeff Van Gundy calls defensive rebounds off free throws "the biggest selfish glut of all time." He also points out, rightly, that on contested rebounds, "The guy who is blocking out and preventing a rebound is every bit as important as the guy who gets the rebound."

The same goes for offense. If Steve Nash passes the ball to a wide-open wing player, who hits a 15-foot jump shot, Nash gets an assist. But if he beats his man, draws a defender and drops it off to Shawn Marion, who is fouled before he can finish the layup, no assist. Less obviously, how does one credit the player who never touches the ball?

Warriors center Adonal Foyle brings up the following point: "If I'm on the weak side and one of my players is on the strong side and he's coming to the basket, I might just pull on the guys shorts -- and that's not going to show up in statistics -- but the player on my team knows that guy couldn't come over because I pulled him. How do you measure that?"

The answer, for now, is that you can't. But there are a lot of people who are trying to. In this week's Sports Illustrated, I wrote a piece on the statistical analysis movement in the NBA. The basic concept: to apply sophisticated mathematical and business tools to basketball for use in player valuation, scouting and coaching, not unlike what the Moneyballers have done in baseball.

It is the type of topic that is complex enough, and so nuanced, that one could write a book about it. (And people have: Check out Dean Oliver's Basketball on Paper, which examines, among other things, the "hot hand" shooter and, in a chapter entitled, "Should I Firebomb Billy Donovan's House," the impact of coaching).

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