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

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  • Torch742
    ... 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
    Message 1 of 4 , Jul 10 7:30 AM
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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
      McGrady, Orlando).
    • Torch742
      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.
      Message 2 of 4 , Jul 10 7:46 AM
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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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