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• ## Re: Offensive efficiency as a function of offensive possessions per minute

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• ... Despite having taken several years of calc so far, Ive actually never taken stats, in highschool or college, so unfortunately all I have is what I can
Jul 10, 2004 1 of 4
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> A couple things...
>
> 1. The band getting narrower with more poss simply expresses that you
> have more variance with fewer attempts, which is what statistically
> should happen. Variance of efficiency is theoretically inversely
> proportional to how many possessions you take.
>
> 2. In Basketball on Paper, I generate functions that show how
> players' efficiencies vary with possession percentage (percentage of
> the team's possessions, with an average of 1 out of 5 or 20%). It's
> one of the most useful things I do. It suggests whether a player can
> use more possessions and still be efficient. It suggests how to
> optimize an offense. It says why Allen Iverson is valuable even if he
> is inefficient. You should take a look at that -- Chapter 19. (I
> know, the axes are backwards on my plots. It's a relic of how I had
> to originally generate them years ago.)
>
> 3. You are definitely right in your theory that efficiency should go
> down with poss used. Part of that theory should also incorporate how
> good teammates are. That's the tough one to work with...
>
> DeanO

Despite having taken several years of calc so far, Ive actually never
taken stats, in highschool or college, so unfortunately all I have is
what I can explain logically to myself, I can't compute the other
stuff. I feel like I have a pretty good grasp of most things
conceptually, but when it comes to things like variance etc, I dont
actually know how to find it. That said...

In response to 1, this is OP/M as opposed to OP. Unless I
misunderstand something, the narrowing of the band is not due to
variance in OP/M, as a low number of OP over an even lower number of
minutes can still produce a high OP/M number, and yet the variance is
only shown to the left of the graph, and not to the right.

2. Yes, there is a subtle difference between % of team OP and OP/M, as
you could probably argue that all of the players on a team like Dallas
are "unfairly" getting a boost to their OP/M, but on the other hand
using % of OP of total OP would "unfairly" reward players on slow
tempo/defensive type teams, like say Rip on Detroit. I dont remember
if I ever got to chapter 19, I put it down at some point and decided I
wanted to know more about computing statistics to be able to look over
the formulas myself before reading further. I might go back and look
it over now :)

3. Yes, but I believe the effects of playing with offensively good
teammates is overstated a bit. Part of that effect overlaps with the
OP/M effect. Good offensive teams have many offensive players, which
means any given player is more likely to have a lower OP/M than he
would on an average team, thereby indirectly raising his OE. The
converse is also true, where bad offensive teams usually have very few
good offensive players and a player's OP/M will likely be higher (See
• Also, here are the top 20 players in adjusted offensive efficiency from the formula used in the article: 1. Brent Barry 2. Peja Stojakovic 3. Brian Cardinal 4.
Jul 10, 2004 1 of 4
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Also, here are the top 20 players in adjusted offensive efficiency
from the formula used in the article:

1. Brent Barry
2. Peja Stojakovic
3. Brian Cardinal
4. James Posey
5. Corey Maggette
6. Shaquille Oneal
7. Yao Ming
8. Antawn Jamison
9. Steve Nash
10. Fred Hoiberg
11. Ray Allen
12. Mark Blount
13. Reggie Miller
14. Antonio Daniels
15. Kobe Bryant
16. Sam Cassell
17. Elton Brand
18. Jarron Collins
19. Dirk Nowitzki
20. Richard Jefferson
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