Yeah, that is one of my questions too. Are they counting shots in transition in this study? If a team has a 2 on 1 in transition, they are obviously going to shoot a higher percentage than they are in a set offense.

Just take at the Warriors the last several years. They were a horrible defense and teams never had to use up the shot clock on them. Teams could get an easy lay up within the first 5-10 seconds of the clock. Bad defenses encourage teams to shoot early and good defenses make you work for it and force you to shoot later. It does seem to be somewhat backwards.

The real key to all this is getting good shots. Good shots, generally come from good passing/ball movement/playmaking. Be it an individual or a team.

Are nash’s suns (prime years) any more effective than Boston’s last 3 with rondo + big 3?

The idea that a certain pace is ‘better’ is short-sided. There’s more than one way to play effective bball. Typically your personnel dictates.

Now that I’ve read it – I do think it’s an interesting paper and a good thought experiment. Definitely a topic worth thinking about. That said, I don’t really buy into a theoretical model of optimal shot clock usage, at least not without a whole lot more supporting evidence that it does a good job reflecting reality. It wouldn’t surprise me if teams were somewhat off in their usage of the shot clock, but I’m very skeptical it’s close to the full 4.5 points per (was it game or 100 possessions). I suspect a lot of that difference comes from realities not taken into account in the model (I have a few in mind, but it could potentially be anything we can think of).

Actually it doesn’t do any sort of correlation like that. What the study does is construct a theoretical model for when the optimal time in the shot clock to take a shot is (average time that is, obviously not every observation will fit this average), based on observed shooting percentages. Basically, they look at the scoring efficiency of teams shooting earlier in the shot clock (but not so early as to be a transition bucket), and then later in the shot clock, and determine the gap is larger than their model says it should be – suggesting teams should shoot more often early in the clock.

My study shows winning teams have more black players than white ones. I studied over 50000 NBA games and found it true.

Therefor if we bench lee, biedrins and half of steph for Tyler, Barron and Nate we should win more

Hey, can you look the distribution for individual teams, rather than the NBA as a whole? I would think there’s a chance the bell shaped curve may just reflect the distribution of different teams styles, which isn’t relevant to any given teams decision of when to shoot….so I’m just curious what it would look like for different individual teams.