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Re: player minutes chart

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  • tamada@oxy.edu
    ... this ... Fascinating stuff, this really is utilizing the minutes played statistic for all it s worth. A couple of minor suggestions: 1. It looks like
    Message 1 of 14 , Jun 8, 2001
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      --- In APBR_analysis@y..., "Mike Goodman" <msg_53@h...> wrote:
      > I am responding to my own earlier post. I am editing some of
      this
      > chart to factor in the changing schedule, from 66 games in 1952, to
      > 82 games by 1967.

      Fascinating stuff, this really is utilizing the minutes played
      statistic for all it's worth. A couple of minor suggestions:

      1. It looks like you're literally looking at total minutes played;
      I'd suggest minutes per game instead. For two reasons: it
      automatically corrects for the "games per season" problem that
      you've been wrestling with. And it will help correct for injuries,
      and comebacks from injuries, which can cause a player's minutes
      to seemingly plummet or skyrocket. Injuries will also affect minutes
      per game, but less so than total minutes.

      2. The issue of players' minutes changing due to their individual
      improvement or aging is a potentially important but complex one.
      You mentioned that it sort of evens out, as young players improve
      and old players decline, but that assumes a sort of long run
      equilibrium. I can imagine that there have been times when the
      NBA was in the middle of a period of influx of new talent (probably
      most all the time) or conversely a period of decay in which old
      players declined but failed to get replaced by an equal amount of new
      talent (probably much rarer, except maybe when an unusual "baby boom"
      of talent, such as 1984, starts aging).


      Are the concentration factors based on players' total minutes?
      That might be the best way to do things, but it might cause the
      concentration factors to be overly influenced by the star players
      who get the most minutes. E.g. if 2 players both doubled their
      minutes from 400 to 800, but one superstar diminished from 3,200 to
      2,800, the grand total is unchanged and the concentration factor would
      be 1.0. But I wonder if we should instead give each of the three
      players equal weight, with individual concentration factors of 2.0,
      2.0, and .875, for an average of 1.625. (This is assuming I've got the
      correct formula for calculating concentration factors.)

      That example shows a danger of my suggestion, as there will be a lot
      of marginal players with tiny minutes whose individual concentration
      factors can be huge or tiny, and which might unduly influence the
      overall index.

      Maybe there's an intermediate way... logarithms, medians instead of
      means or totals, etc.

      I won't be reading email for almost a month, so I regrettably won't
      be able to participate in this discussion for much longer, until July.

      It occurs to me that my minutes-per-game suggestion might be
      problematic when players change their number of games played, in
      addition to their number of minutes per game ... a lot here to think
      about.


      --MKT
    • Mike Goodman
      ... to ... minutes ... One problem with using minutes-per-game is that, while mathematically compensating for the player who was injured, in fact that player s
      Message 2 of 14 , Jun 8, 2001
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        --- In APBR_analysis@y..., tamada@o... wrote:
        > --- In APBR_analysis@y..., "Mike Goodman" <msg_53@h...> wrote:
        > > I am responding to my own earlier post. I am editing some of
        > this
        > > chart to factor in the changing schedule, from 66 games in 1952,
        to
        > > 82 games by 1967.
        >
        > Fascinating stuff, this really is utilizing the minutes played
        > statistic for all it's worth. A couple of minor suggestions:
        >
        > 1. It looks like you're literally looking at total minutes played;
        > I'd suggest minutes per game instead. For two reasons: it
        > automatically corrects for the "games per season" problem that
        > you've been wrestling with. And it will help correct for injuries,
        > and comebacks from injuries, which can cause a player's minutes
        > to seemingly plummet or skyrocket. Injuries will also affect
        minutes
        > per game, but less so than total minutes.

        One problem with using minutes-per-game is that, while
        mathematically compensating for the player who was injured, in fact
        that player's minutes are picked up by other players; and so there
        would be a skewed total for his team, and for the league.

        > 2. The issue of players' minutes changing due to their individual
        > improvement or aging is a potentially important but complex one.
        > You mentioned that it sort of evens out, as young players improve
        > and old players decline, but that assumes a sort of long run
        > equilibrium. I can imagine that there have been times when the
        > NBA was in the middle of a period of influx of new talent (probably
        > most all the time) or conversely a period of decay in which old
        > players declined but failed to get replaced by an equal amount of
        new
        > talent (probably much rarer, except maybe when an unusual "baby
        boom"
        > of talent, such as 1984, starts aging).
        >
        Completely valid points. But wouldn't a mass retirement or mass
        influx be evened out over a few years at most? If there were serious
        ups and downs not attributable to league expansion, I would wonder
        about this, yet as the sample size grows in later years, the trend is
        invariably toward talent concentration.

        > Are the concentration factors based on players' total minutes?
        > That might be the best way to do things, but it might cause the
        > concentration factors to be overly influenced by the star players
        > who get the most minutes. E.g. if 2 players both doubled their
        > minutes from 400 to 800, but one superstar diminished from 3,200 to
        > 2,800, the grand total is unchanged and the concentration factor
        would
        > be 1.0. But I wonder if we should instead give each of the three
        > players equal weight, with individual concentration factors of 2.0,
        > 2.0, and .875, for an average of 1.625. (This is assuming I've got
        the
        > correct formula for calculating concentration factors.)
        >
        > That example shows a danger of my suggestion, as there will be a
        lot
        > of marginal players with tiny minutes whose individual
        concentration
        > factors can be huge or tiny, and which might unduly influence the
        > overall index.
        >
        > Maybe there's an intermediate way... logarithms, medians instead of
        > means or totals, etc.
        >
        > I won't be reading email for almost a month, so I regrettably won't
        > be able to participate in this discussion for much longer, until
        July.
        >
        > It occurs to me that my minutes-per-game suggestion might be
        > problematic when players change their number of games played, in
        > addition to their number of minutes per game ... a lot here to
        think
        > about.
        >
        >
        > --MKT

        Again we have reached more agreement than I am comfortable with!
        I wish we could find some holes in the logic, or at least some seams.
        Even casually asking my acquaintances seems to produce the same
        response, intuitively or analytically: players must be getting
        better.
      • harlanzo@yahoo.com
        ... I agree with your conclusion on player improvement. I was trying to think of a way of independently verifying that point. The one way that it struck me
        Message 3 of 14 , Jun 8, 2001
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          --- In APBR_analysis@y..., "Mike Goodman" <msg_53@h...> wrote:

          > Even casually asking my acquaintances seems to produce the same
          > response, intuitively or analytically: players must be getting
          > better.

          I agree with your conclusion on player improvement. I was trying to
          think of a way of independently verifying that point. The one way
          that it struck me to do this is to check players' best years and see
          whether their peaks coincide with the generally believed development
          of players (ie rising production from 21-27/28 and then gradual
          decline). Indeed, it did seem that an inordinate number of players
          hit their statistical peaks in 61-62 well before we might believe
          they would. I have not looked at this thoery in depth but its just a
          thought.
        • Mike Goodman
          ... to ... see ... development ... a ... Another suggestion (offline) has been that players have longer careers these days. Whereas 13 years was about the
          Message 4 of 14 , Jun 9, 2001
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            --- In APBR_analysis@y..., harlanzo@y... wrote:
            >
            > I agree with your conclusion on player improvement. I was trying
            to
            > think of a way of independently verifying that point. The one way
            > that it struck me to do this is to check players' best years and
            see
            > whether their peaks coincide with the generally believed
            development
            > of players (ie rising production from 21-27/28 and then gradual
            > decline). Indeed, it did seem that an inordinate number of players
            > hit their statistical peaks in 61-62 well before we might believe
            > they would. I have not looked at this thoery in depth but its just
            a
            > thought.

            Another suggestion (offline) has been that players have longer
            careers these days. Whereas 13 years was about the limit for players
            entering before 1965, there are now quite a few players who go for 15-
            20 years. In general, their last few seasons would consist of
            minutes diminishing below that of their rookie seasons.
            Which brings me to another point: I don't think it matters where
            in your career you peak (early, middle, late), in terms of league-
            wide averages. Rather, it matters how many minutes you played as a
            rookie, and how many you play in your last season, and that is all.
            While a good many players hang on to the bitter end, perhaps
            winding up their career with a 100-minute season, there are very few
            who get 100 minutes as a rookie, and build up to major minutes
            later. Most good, long-career players are good as rookies.
            So, regardless of the intervening years, only one's first and last
            seasons really add up to anything in the league totals. If you get
            2000 minutes as a rookie, you may peak at 3000 or 2500, or whatever;
            if you play 10 years and end up with a 500 minute season, you lost
            1500 minutes over 10 years. When you are looking at large numbers of
            players, the curve smooths out everyone's peaks and valleys, and it
            looks as though every year it is tougher to get minutes; but at least
            part of this measurement is bogus.
            Now we come to another sticking-point; we could figure everyone's
            rookie minutes, final-season minutes, and career length, to get an
            average annual minutes-lost number. But this would not distinguish
            between an aging factor and a competition factor.
            So these numbers may mean nothing. Or they may mean something.
            Anyone?
          • Mike Goodman
            Responding to one of my own posts, again. I went ahead and tabulated the careers of some 1500 players, using seasons spent with a single team. I have broken
            Message 5 of 14 , Jun 22, 2001
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              Responding to one of my own posts, again.
              I went ahead and tabulated the careers of some 1500 players, using
              seasons spent with a single team. I have broken them down by career
              length, from single-season careers to a 17+ year group.
              The 2nd and 3rd columns are the minutes played as rookie, and in
              final season.

              career avg. minutes
              length season annual decline
              ----- ----------- ----- --------------
              yrs. # first last net min. pct.
              1 326 (500) (500)
              2 156 685 561 -123 123 .180
              3 129 873 626 -247 124 .142
              4 93 916 688 -229 76 .083
              5 76 1032 678 -354 88 .086
              6 65 1150 784 -367 73 .064
              7 86 1368 660 -709 118 .086
              8 78 1415 734 -681 97 .069
              9 96 1266 953 -313 39 .031
              10 106 1448 912 -537 60 .041
              11 92 1393 983 -410 41 .029
              12 70 1534 1020 -513 47 .030
              13 57 1779 1101 -678 57 .032
              14 42 1734 1030 -704 54 .031
              15 24 1436 1053 -383 27 .019
              16 19 1881 1037 -844 56 .030
              17+ 16 1997 480 -1516 89 .044
              __________________________________________
              7.7 1531 1240 805 -435 65 .052


              This thing has sat on my desktop long enough; I am not ashamed to
              say I don't know what to make of it.
              One thing is clear: "weak" players (those with brief careers) have
              a steeper decline, both in minutes and pct. of minutes, than do
              stronger (longer) players. Is it possible to produce a "natural
              decline" factor, as distinguished from a "talent concentration"
              factor, by comparing the decline rates of stronger and weaker players?
              Something about guys who go past 16 years and hanging on to the
              bitter end? I don't know how much these 16 players can skew the
              overall group, but it does illustrate how a bias can result when
              talented young players come in at 2000 minutes and leave at 500.

              --- In APBR_analysis@y..., "Mike Goodman" <msg_53@h...> wrote:
              I don't think it matters where
              > in your career you peak (early, middle, late), in terms of league-
              > wide averages. Rather, it matters how many minutes you played as a
              > rookie, and how many you play in your last season, and that is all.
              > While a good many players hang on to the bitter end, perhaps
              > winding up their career with a 100-minute season, there are very
              few
              > who get 100 minutes as a rookie, and build up to major minutes
              > later. Most good, long-career players are good as rookies.
              > So, regardless of the intervening years, only one's first and
              last
              > seasons really add up to anything in the league totals. If you get
              > 2000 minutes as a rookie, you may peak at 3000 or 2500, or
              whatever;
              > if you play 10 years and end up with a 500 minute season, you lost
              > 1500 minutes over 10 years. When you are looking at large numbers
              of
              > players, the curve smooths out everyone's peaks and valleys, and it
              > looks as though every year it is tougher to get minutes; but at
              least
              > part of this measurement is bogus.
              > Now we come to another sticking-point; we could figure
              everyone's
              > rookie minutes, final-season minutes, and career length, to get an
              > average annual minutes-lost number. But this would not distinguish
              > between an aging factor and a competition factor.
              > So these numbers may mean nothing. Or they may mean something.
              > Anyone?
            • Dean Oliver
              ... using ... Mike -- I think all this work with minutes is very interesting. Not precisely sure what to make of it either, but it _seems_ relevant and
              Message 6 of 14 , Jun 22, 2001
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                --- In APBR_analysis@y..., "Mike Goodman" <msg_53@h...> wrote:
                > Responding to one of my own posts, again.
                > I went ahead and tabulated the careers of some 1500 players,
                using
                > seasons spent with a single team. I have broken them down by career
                > length, from single-season careers to a 17+ year group.
                > The 2nd and 3rd columns are the minutes played as rookie, and in
                > final season.
                >
                > career avg. minutes
                > length season annual decline
                > ----- ----------- ----- --------------
                > yrs. # first last net min. pct.
                > 1 326 (500) (500)
                > 2 156 685 561 -123 123 .180
                > 3 129 873 626 -247 124 .142
                > 4 93 916 688 -229 76 .083
                > 5 76 1032 678 -354 88 .086
                > 6 65 1150 784 -367 73 .064
                > 7 86 1368 660 -709 118 .086
                > 8 78 1415 734 -681 97 .069
                > 9 96 1266 953 -313 39 .031
                > 10 106 1448 912 -537 60 .041
                > 11 92 1393 983 -410 41 .029
                > 12 70 1534 1020 -513 47 .030
                > 13 57 1779 1101 -678 57 .032
                > 14 42 1734 1030 -704 54 .031
                > 15 24 1436 1053 -383 27 .019
                > 16 19 1881 1037 -844 56 .030
                > 17+ 16 1997 480 -1516 89 .044
                > __________________________________________
                > 7.7 1531 1240 805 -435 65 .052

                Mike --

                I think all this work with minutes is very interesting. Not precisely
                sure what to make of it either, but it _seems_ relevant and
                informative. (Maybe for doing something like James' career projection
                stuff...)

                For instance, it's interesting that players with longer careers never
                fall to the level of 2 year players -- in terms of minutes. That
                probably means that they are still better than the 2 year players even
                after 16 years in the game.

                Another way to look at the data would be to calculate the minutes for
                players in their peak year and what year that typically was.
                Calculate a decline rate in minutes per year from the year of peak.
                I'm guessing that the peak minute year flatterns out at about 5 years,
                based on the typical assumption that players' careers peak at age
                27-28.

                Dean Oliver
                Journal of Basketball Studies
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