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Re: [APBR_analysis] Re: 97% correlation

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  • Gabe Farkas
    2 thoughts: 1) Ben was known for his defense before Tayshaun got there, and i d wager that his PER would indicate just that. 2) i wasn t making any point about
    Message 1 of 30 , Jul 22, 2004
      2 thoughts:

      1) Ben was known for his defense before Tayshaun got
      there, and i'd wager that his PER would indicate just
      that.

      2) i wasn't making any point about team success
      correlating to individual positional achievement.
      rather, i was suggesting that success at one position
      might have something to do with the success of one's
      teammates.


      --- mrintp2000 <shzys@...> wrote:
      > I remember having this very discussion about
      > Tayshaun Prince before
      > the NBA finals. I contended that his opposing PER
      > showed that he was a
      > great defender. Most people wanted to give the
      > credit to Ben Wallace.
      > My response was "why not just give the credit for
      > Ben's defense to
      > Tayshaun?" That wouldn't make sense either.
      >
      > I believe Roland did a study on the correlation
      > between success at an
      > individual position and winning percentage. He found
      > no higher
      > correlation with one position over another.
      >
      >
      > --- In APBR_analysis@yahoogroups.com, Gabe Farkas
      > <gabefark@y...> wrote:
      > > I don't necessarily agree with your point #1.
      > Could
      > > you speculate that Ben Wallace's imposing
      > defensive
      > > presence in the middle (a) discouraged opposing
      > guards
      > > from taking the ball into the lane more, thus
      > forcing
      > > them to settle for outside shots, and (b) ed to
      > more
      > > blocks when these players did decide to drive the
      > > ball?
      > >
      > > Thus, those PGs, SGs and SFs had slightly lower
      > PERs,
      > > and consequently Chauncey's, Rip's and Tayshaun's
      > > PER-diffs were slightly inflated?
      > >
      > > I would be interested to see a correlative
      > analysis
      > > between the PER-diff of every position vs the
      > average
      > > of the other 4. In other words, look at the
      > > statistical correlation of the PER-diff of the C
      > vs
      > > (PG+SG+SF+PF)/4, and then the same with PF vs
      > > (PG+SG+SF+C) and so on and so forth for all 5
      > > positions.
      > >
      > >
      > > --- mrintp2000 <shzys@n...> wrote:
      > > > Because the Team-PER-diff is a sum of the Player
      > > > PER-Diff's. This
      > > > correlation shows that there is no synergistic
      > > > effect whatsoever,
      > > > again-it's a simple sum. There are many
      > important
      > > > implications of
      > > > this, here are a few
      > > > 1. No position on the floor is more important
      > than
      > > > any other
      > > > 2. You don't need a top ten player to have a
      > title
      > > > contending team
      > > > 3. The tremendous value of a superstar is
      > > > effectively quantified (KG
      > > > +16 for example is worth more than 3X as much as
      > say
      > > > Kenyon Martin +5)
      > > >
      > > > Back to the PER. First, the PER is the only
      > system
      > > > I've seen that
      > > > stands up to subjective analysis. It had MJ
      > rated #1
      > > > all those years,
      > > > and then Shaq #1 for 5 years straight. Maybe
      > you
      > > > guys disagree?
      > > >
      > > > Second, the PER allows players to contribute in
      > a
      > > > multitude of ways
      > > > yet still be considered effective players.
      > Third,
      > > > the PER-diff
      > > > accurately accounts for defense. Well with maybe
      > a
      > > > 25% "fudge factor"
      > > > when the defensive assingment might be
      > mismatched:(
      > > >
      > > > Again, the real value here is we can take a very
      > > > effective rating
      > > > system for individual players, and simply add
      > that
      > > > up to create an
      > > > equally effective rating for teams.
      > > >
      > > > --- In APBR_analysis@yahoogroups.com,
      > "wizardskev"
      > > > <kevinbroom@r...>
      > > > wrote:
      > > > > I'm not knocking PER differential at all. My
      > point
      > > > is that by taking
      > > > > the team differential from a very simple
      > linear
      > > > system -- pts + reb +
      > > > > ast + stl + blk - missed fga - missed fta - to
      > -
      > > > pf -- I get the same
      > > > > 97% correlation with winning percentage. Why
      > go
      > > > through all the
      > > > > complex calculations necessary for PER if we
      > can
      > > > get the same result
      > > > > using a simpler system?
      > > > >
      > > > > --- In APBR_analysis@yahoogroups.com, "Mike G"
      > > > <msg_53@h...> wrote:
      > > > > > --- In APBR_analysis@yahoogroups.com,
      > > > "wizardskev" <kevinbroom@r...>
      > > > > > wrote:
      > > > > > > I'm still waiting for someone to explain
      > why a
      > > > .97 correlation with
      > > > > > > PER should be viewed as The Holy Grail,
      > when
      > > > using a different
      > > > > > linear
      > > > > > > stat method, I got the same correlation.
      > A
      > > > 97% correlation is very
      > > > > > > strong, no doubt. But why focus on PER
      > when
      > > > another (simpler)
      > > > > > method
      > > > > > > gets the same result?
      > > > > >
      > > > > > As has been mentioned, the correlation
      > between
      > > > team point-
      > > > > > differential is also about .97, so there
      > isn't
      > > > any improvement when
      > > > > > you factor in rebounds, turnovers, etc.
      > > > > >
      > > > > > My own quasi-linear correlation (not a
      > > > "differential") is only
      > > > > > about .68 correlation; it improves when I
      > adjust
      > > > winning % by
      > > > > > Conference (+.025 for the West, -.025 for
      > the
      > > > East).
      > > > > >
      > > > > > When I use my Sagarin correction, I get a
      > .985
      > > > correlation.
      > > > > >
      > > > > > However, I believe there's some merit to the
      > > > free-standing nature of
      > > > > > the PER-diff -- if you have that data.
      > Since I
      > > > like to evaluate
      > > > > > seasons from the distant past, I'm
      > determined to
      > > > use "existing
      > > > > > stats" for my formulae.
      > > > > >
      > > > > >
      > > > > > And thanks (mrintp) for the tip on Excel. I
      > > > didn't have to
      > > > > > download; under Tools, there's Add-Ins; then
      > > > just check Analysis
      > > > > > ToolPak, and you're in business. (Excel
      > 2000)
      > > >
      > > >
      > >
      > >
      > >
      > >
      > > __________________________________
      > > Do you Yahoo!?
      > > New and Improved Yahoo! Mail - 100MB free storage!
      > > http://promotions.yahoo.com/new_mail
      >
      >


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