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Re: SABR/Sports Econ update

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  • schtevie2003
    ... college ... be ... should be able ... find the ... Pardon my ignorance, but what is DI? That aside, if you are going to do yeoman s work, here are my two
    Message 1 of 52 , Aug 8, 2003
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      --- In APBR_analysis@yahoogroups.com, "Daniel Dickey"
      <danthestatman@h...> wrote:
      >
      >
      > >
      > >And yes, I also believe that someone will be able to come up
      > >with a statistical formula which allows us to better relate
      college
      > >rebounding stats to pro ones. (In fact, I wouldn't expect this to
      be
      > >very difficult at all.)
      > >.
      >
      >
      > I'll try to get on this - I work on all DI stats, I'll try to find a decent
      > correlation for rebounding/pace/strength of competition. I
      should be able
      > to come up with something fairly useful pretty quickly - IF I can
      find the
      > DI opponent team stats I'd need.
      >
      Pardon my ignorance, but what is DI? That aside, if you are
      going to do yeoman's work, here are my two cents worth on what
      I would expect would be a decent, simple correlation. Take
      offensive (or conversely defensive) rebounding percentages for
      college teams (expressed as probability of rebounding a
      reboundable ball - and yes there is the issue of factoring out
      missed-freethrow "gimme" rebounds, but that shouldn't bias the
      results too much) and then prorate them on a per minute basis
      for the players in question. Then do the same calculation for the
      same players as professionals, and then see what the
      correlation is. I don't think pace should factor much into it (and I
      don't think it was the point of my rebounding remark above).
      Furthermore, as the rebound remarks were related to the draft
      savviness of NBA cognoscenti, comparing the results to draft
      order (position by position) would be an interesting result (not
      that people typically draft for rebounding, but the larger issue is
      to what degree should they.)
    • igor eduardo küpfer
      ... From: Gary Collard To: APBR_analysis@yahoogroups.com Sent: Thursday, August 07, 2003 12:13 PM Subject: Re: [APBR_analysis] SABR/Sports Econ update ... That
      Message 52 of 52 , Aug 8, 2003
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        ----- Original Message -----
        Sent: Thursday, August 07, 2003 12:13 PM
        Subject: Re: [APBR_analysis] SABR/Sports Econ update

        Jim Armstrong wrote:
        >
        > On Mon, Aug 04, 2003 at 04:00:38PM -0500, Gary Collard wrote:
        > > I'm not sure why that was so controversial.  The concept of market size in
        > > the NFL is pretty much meaningless, since most league revenue is shared
        > > equally.  The reason that a Yankees in baseball have such an advantage is
        > > that they have local TV revenues that are an order of magnitude or more
        > > greater than most (all?) of the other teams and is significant compared to
        > > national revenue, thus they can afford to have a payroll that is 60%
        > > greater than any other team even before they pay the luxury tax as they do
        > > in 2003.  In the NFL, there is no local TV at all, and (over a period of
        > > years, letting spikes in bonus payments wash out) little payroll deviation,
        >
        > Actually, if you look at the distribution of team player payrolls, the NFL
        > and the NBA are quite comparable (see standard deviation in data below).

        That is why I specifically said "over a period of years, letting spikes in
        bonus payments wash out" in the case of the NFL.  The one year payroll
        numbers you listed are meaningless to my point, do you have the data to run
        them for the last 5 years or more?  That will tell you who has the "harder"
        cap.

        --
        Gary Collard
        Maybe the coefficient of variation (SD / Mean * 100) is a more apt measure for comparing the variation of payrolls for different sports across seasons.
         
        Year     NHL     NFL     NBA     MLB
        1994    28.3     8.7    15.2    26.6
        1995    26.6    12.7    24.1    27.7
        1996    43.3    11.9    21.9    31.4
        1997    #N/A    15.3    28.9    33.0
        1998    #N/A    12.1    27.0    37.4
        1999    33.4    12.0    23.0    43.1
        2000    37.4    13.8    23.6    38.3
        2001    31.1    13.5    24.6    38.3
        2002    33.0    18.1    20.6    36.6
        2003    35.9    #N/A    24.0    38.9
         
        On this measure, NBA teams show less variation in payroll than baseball and hockey teams, but the NFL teams are more level than any of them.

        Data from Rodney Fort's excellent resource: http://users.pullman.com/rodfort/SportsBusiness/BizFrame.htm
         
        ed
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