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Re: Predicting Wins and Losses From a Single Player Stat

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  • sonicdk2
    ... in ... against ... Yup. Lowest was 11 points (twice), highest was 32 (3 times) rexcept for that outlier. GP s standard deviation in scoring was 5.427
    Message 1 of 6 , May 19, 2002
      --- In APBR_analysis@y..., "thedawgsareout" <kpelton08@h...> wrote:
      > The Seattle perspective:
      > that Payton is a rather consistent scorer. I don't believe he was
      in
      > single-digits more than once or twice this season, but his peak
      > scoring is not as high as many players. He was only over 30 a
      > handful of times, with a real outlier in his 43-point effort
      against
      > the Clippers.
      Yup. Lowest was 11 points (twice), highest was 32 (3 times) rexcept
      for that outlier. GP's standard deviation in scoring was 5.427
      points, which is pretty low.


      looking at a number of extraneous variables, such as the combination
      > of teammates and the team's success.
      multiple regression on win/loss might help--put minutes played or
      margin of victory/loss as first predictor and then the stat of
      interest such as points scored as second predictor and see what you
      get. But I'm not sure how to carry it out properly since the
      predictor variables are likely to be correlated, which tends to
      invalidate the result. Anybody have any ideas?
      >


      Any chance of turning it into a
      > guest column at SonicsCentral?
      I dunno. If you get a draft of a guest column within the next week,
      then I guess you'll know....
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