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kevin's weighting system

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  • Joe
    ... the article describes a different approach (though i d actually wish there was more detail to explain why you feel (if you do) that the results of your
    Message 1 of 1 , Mar 10, 2004
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      --- In APBR_analysis@yahoogroups.com, "Kevin Pelton" <kpelton08@h...>
      wrote:
      > > Using linear weights generated from team statistics, I suspect
      > > that a player such as Iverson would get a relatively low rating,
      > > even though they may be quite valuable to their team.
      >
      > I've tried to account for problems like this by putting individual
      > players' statistics in a team context -- an imaginary team of them
      > and four average teammates. For this specific issue, I make an
      > artificial adjustment to teammates' efficiency based on percentage
      > of possessions used. That seems to work fairly well, though there
      > are still major problems with the system overall.
      >
      > http://www.sonicscentral.com/ratingsystem.html
      >
      > That link explains it in painful detail, if anyone has interest.


      the article describes a different approach (though i'd actually wish
      there was more detail to explain why you feel (if you do) that the
      results of your formulas more closely fit reality than linear weight
      systems. but certainly the new outcome measures are interesting and
      useful conceptual twists.

      i read the rebounding stuff in particular and understand what you are
      saying about roles and other teammates. but perhaps instead of
      adding 4 average teammates wouldn't be cleaner to just compare
      individual player performance to league average player at that
      position? isnt that the real intent?

      one of my reactions was that your approach seems to blur and
      somewhat minimize rebounding, i.e. the other 4 average players will
      do 70-90% of it. and the results of adding in the 4 average players
      will be the stat number yielded will be far more heavily composed by
      what they do rather than the player in question. it can also end up
      rewarding those that rebound beyond the norm of the position (say a
      guard who pulls done 5 or 6) more than those that might rebound
      higher but are in positions that are supposed to rebound higher (say
      a power forward that "only" pulls down 7 or 8) . but isnt a rebound a
      rebound?

      your position comparative approach appears to do what you do with
      rebounding for all stats which is consistent and appropriate and
      produces a useful if somewhat different analytical product. maybe it
      is a compliiment to, not a replacement of indivdual player data only
      ranking systems. with about 80% (give or take) of the data weight
      in that product not being from that player so it would seem to mute
      the range between top and bottom or at least require looking at top
      and bottom level stat outcomes differently. small differences
      (around 1/5th the size of differences in individual player data only
      rating systems?) in performance ratings would mean big differences in
      performance and comparing across positions would end up mixing the
      stat value of those two players with the comparative stat value of
      the two positions involved (pg vs sf, etc). i dont see how this
      particularly helps a lot. it does allow comparisons of player
      performance compared to the norm for their position but it is not
      necessary to introduce the 4 average players to do that.

      leaving out the theoretical 4 other players out and just using
      individual data seems easier and closer to reality to me. you can do
      that with your formulas just fine and your weights are your weights
      and can be compared and debated just the same as any linear weight
      system. rewarding the individual rebounder fully still seems fair
      me even if it produces a big man heavy in top rankings end result.
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