Who are these “shot clock beaters”?

There is a post on Slate.com today that essentially argues that basketball box score and advanced statistics are of minimal value because there’s too much interaction in the sport between teammates to really differentiate results.  Of course, if “too much interaction” were the standard of reliability, football statistics should have been relinquished decades ago.  Besides, if this “unreliability” exists, why are so many of the box score basketball statistics so consistent from season to season (save for field goal percentage)?  I found an astonishing correlation between a player’s MWS from one season before and his MWS from the current season, and Dave Berri found the same thing with WS. 

(The author uses the worst possible logical fallacies to support his argument, including the dreaded anecdote — I’ll paraphrase:  “One season Jason Collins rebounded poorly because he spent the entire season boxing out the other team’s best rebounder in order that Jason Kidd could grab an inordinate amount of rebounds.”  Are you kidding me?  That’s not evidence… its not even plausible.  He spent the “entire” season doing this, and game in and game out it resulted in rebounds for Kidd?  That’s nonsense.  It sounds like one of those asinine anecdotes you would hear from a player from the 1950s — “You see, what happened was, Russell put flubber on his shoes and because of it he got that extra half inch he needed…”) 

But I don’t want to get into that tired argument.  I just want to zero in on one piece of mythology that the author says was raised by two economists to support the unsupportable idea that having a high usage player on your team allows the other players to be more “selective” with their shots. 

The author says the economists claim that “after all, if the shot clock is running down, they know they can just throw it to the high usage guy and he’ll use his playground moves to get off a shot”.  I’m paraphrasing, obviously.  The problem, though, is there is no evidence that this occurs.  If this was actually happening, we should see some of these high usage guys “shot clock” specific attempts tilted more heavily toward the last three seconds of the clock (21-24).  But I can’t find this result anywhere or with anyone. 

For instance, Carmelo Anthony, for whom the “Effect” is named, took only 14% of his shots with the three or less seconds on the shot clock (“the red zone”) when he played in Denver.  He’s taking only 8% of his shots in the red zone in New York.  Those shots must be going to Amare.  No, Stoudamire  takes only 9% of his shots in the red zone. 

LeBron does take 21% of his shots in the red zone, but this merely represents an even distribution for LBJ.  There’s no evidence that he’s called upon to take an inordinate number of red zone heaves.  In fact, teammate Mario Chalmers takes a higher percentage of his shots (24%) in the red zone than James does, and Chalmers is nobody’s idea of a “bail-out” guy.

How bout D Wade?  If anyone were to play the “chuck it to him” role on a team, it would be the hard penetrating Wade.  But Wade only takes 14% of his shots in the red zone.  How bout Durant — the NBA’s best scorer?  Do his teammates look to him with the clock ticking down?  Apparently not.  He only takes 12% of his shots in the red zone.

Dirk Nowitzki?  Only 16%.  Kevin Martin?  10%.   John Wall?  15%.  Kobe?  15%.   

I just can’t find any evidence that this type of strategy is being employed.  I don’t think it is.

In fact, here’s a rule of thumb.  When an argument is supported by unsubstantiated speculations, its probably not a sound argument.


4 Responses to “Who are these “shot clock beaters”?”

  1. DKH Says:

    Shouldn’t it be the percentage of team attempts in the red zone that are taken by a specific player that we are looking at? Compared to the percentage of overall team attempts taken by that player? I don’t agree with the linked article, but that seems like the more natural way to examine this, to me.

    Is the distribution of shot attempts in the last 4 seconds different than the distribution in the first 20?

  2. Mike Says:

    Can i ask where the stats came from?

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