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Shot Effect on Shooting Accuracy

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  • igor eduardo küpfer
    Roland s site (http://www.82games.com/index.htm) provides some very cool data, lots of stuff to chew on. My first bite is to test DeanO s hypothesis on the
    Message 1 of 3 , Oct 12, 2003
      Roland's site (http://www.82games.com/index.htm) provides some very cool
      data, lots of stuff to chew on. My first bite is to test DeanO's hypothesis
      on the relationship between shot clock and offensive effectiveness. The site
      breaks down the amount of clock into four discrete states:

      Elapsed shot clock time
      0-10 seconds
      11-15
      16-20
      21-24

      The leaguewide averages for Effective FG% by shot clock state:

      0-10 11-15 16-20 21-24

      51.8% 46.0% 44.7% 40.8%

      These differences are statistically significant. Here, I'll paste the ANOVA
      results from the Minitab output:


      Analysis of Variance for Eff%%
      Source DF SS MS F P
      state 3 0.181590 0.060530 115.42 0.000
      Error 112 0.058738 0.000524
      Total 115 0.240329
      Individual 95% CIs For Mean
      Based on Pooled StDev
      Level N Mean StDev ------+---------+---------+---------+
      0-10 29 0.51786 0.01880 (-*-)
      11-15 29 0.46021 0.02815 (-*--)
      16-20 29 0.44652 0.02102 (--*-)
      21-24 29 0.40759 0.02259 (-*--)
      ------+---------+---------+---------+
      Pooled StDev = 0.02290 0.420 0.455 0.490 0.525


      Here's the breakdown of each team's EFF% relative to their total EFF% within
      each shot clock state (EFF%_state - EFF%_season)

      TEAM 0-10 11-15 16-20 21-24

      ATL 4.1% -1.5% -2.3% -7.7%
      BOS 2.5% 0.2% -0.7% -8.2%
      CHI 5.9% -4.7% -4.0% -3.8%
      CLE 4.4% -2.4% -2.4% -7.2%
      DAL 4.2% 0.6% -2.7% -11.2%**
      DEN 4.1% -1.1% -3.2% -5.9%
      DET 5.7% -0.3% -2.6% -9.2%
      GS 4.7% -3.9% -3.1% -6.5%
      HOU 4.4% -2.0% -1.4% -5.3%
      IND 4.2% 0.5% -4.1% -6.8%
      LAC 7.3%** -4.2% -3.3% -8.2%
      LAK 4.7% -2.9% -2.3% -5.9%
      MEM 4.6% -1.9% -3.4% -7.0%
      MIA 4.5% -4.5% 1.1%** -5.1%
      MIL 3.5% -0.1% -2.4% -6.3%
      MIN 5.9% -1.6% -5.6%* -8.0%
      NJ 4.8% -3.7% -3.1% -4.9%
      NO 4.7% 0.5% -3.4% -8.4%
      NY 2.6% -0.1% -2.2% -3.7%
      ORL 2.7% -0.4% -3.3% -5.4%
      PHI 5.2% -2.8% -4.0% -3.8%
      PHX 3.1% 0.7% -3.7% -7.7%
      POR 4.2% -1.1% 0.0%* -9.1%
      SAC 2.7% -1.2% -3.0% -4.9%
      SAN 4.0% -0.7% -1.9% -7.0%
      SEA 5.4% -0.2% -4.7% -5.1%
      TRN 5.1% -2.9% -3.5% -3.1%
      UTA 5.1% 0.5% -2.1% -9.2%
      WAZ 3.6% 1.9% -1.7% -7.3%

      * Significant at 5%
      ** significant at 1%

      It's pretty clear from this that teams consistently shoot _much_ worse at
      the tail end of shot clocks.

      ed
    • Mike G
      ... very cool ... My own first reaction to 82games is to wonder if it isn t too good to be true. But I ll put my skepticism aside for the moment. ...
      Message 2 of 3 , Oct 14, 2003
        --- In APBR_analysis@yahoogroups.com, igor eduardo küpfer
        <igorkupfer@r...> wrote:
        > Roland's site (http://www.82games.com/index.htm) provides some
        very cool
        > data, lots of stuff to chew on.

        My own first reaction to 82games is to wonder if it isn't too good
        to be true. But I'll put my skepticism aside for the moment.


        >My first bite is to test DeanO's hypothesis
        > on the relationship between shot clock and offensive
        effectiveness. The site
        > breaks down the amount of clock into four discrete states:

        > The leaguewide averages for Effective FG% by shot clock state:
        >
        > 0-10 11-15 16-20 21-24
        >
        > 51.8% 46.0% 44.7% 40.8%
        >
        > These differences are statistically significant...

        Presumably, the 0-10 sec 'state' includes offensive putbacks, as
        well as fast-breaks and the occasional backcourt steal.

        I've averaged the teams' rates into a league-wide rate table,
        summarized thus:

        range Att. eFG% Pts FGA 24sec
        00-10 .397 .518 33.2 32.0 5
        11;15 .250 .460 18.6 20.2 13
        16-20 .230 .447 16.6 18.6 18
        21-24 .124 .408 08.1 10.0 22.2
        total 1.00 .473 76.5 80.8 12.1
        35.6 .680

        'range' is what Ed was calling shot clock 'state'.

        The 'Att.' column is the % of shots taken in the various ranges of
        the shot clock.

        eFG% does not, apparently, include points from FT.

        'Pts' thus is a measure of points from FG.

        FGA is a number I've calculated as ( FGA = Pts x 2 / eFG% ).

        Under '24sec' is an estimated average time of shot-release within
        the associated range. Thus, shots taken at 11-15 sec are considered
        to all be taken at 13 sec, for purposes of calculation.

        The average time on the clock when a shot is attempted is here
        estimated at 12.1 (from the parameters in the chart).

        The number 35.6 is 2880 seconds ( = 48 x 60 ) divided by total FGA.
        Thus a team attempts a FG every 35.6 seconds.

        The factor .680 is ( 2 x 12.1 / 35.6 ), or the percent of time that
        ultimately leads to a FG attempt. Presumably the other 32% leads to
        FT and turnovers.


        Now, if we assume this .68 number is constant, and plug in
        alternative parameters, we can estimate how scoring and shooting %
        might change with other shot-clock states.

        Suppose a team manages to get their shots off more quickly, without
        hurting their shooting percentages:

        range Att. eFG% Pts FGA 24sec
        0-10 .420 .518 37.1 35.8 5
        11;15 .270 .460 21.2 23.0 13
        16-20 .240 .447 18.3 20.5 18
        21-24 .070 .408 04.9 06.0 22.2
        total 1.000 .477 81.4 85.2 11.5
        33.8 .680

        Reducing last-seconds shots by almost half has boosted eFG% by a
        mere .004; but the decreased time-per-possession has upped scoring
        by 5 PPG.


        What about increasing the shot-clock to 30 seconds? While this
        introduces a number of unknowns, we can play around with some
        possibilities.

        Suppose eFG% remain the same for early, late, and middle parts of
        the shot clock. Further, let's assume the .68 is constant. And for
        starters, assume (optimistically) that teams continue to shoot
        within 12.5 seconds, on average:

        range Att. eFG% Pts FGA 30sec
        0-10 .400 .518 32.4 31.3 5
        11;18 .360 .460 26.0 28.2 14
        19-26 .210 .447 14.7 16.4 22
        27-30 .030 .408 1.9 2.3 28
        total 1.000 .479 75.0 78.3 12.5
        36.8 .680

        Here, I've merely tweaked the Att. column to add up to 1.00. Now,
        last-second shots are only a quarter of the frequency they really
        are. But amazingly (to me), eFG% is only up .006

        Meanwhile, scoring has actually dropped by 1.5 PPG; and this is
        perhaps unrealistically optimistic.


        Another possibility in the 30-seconds-to-shoot fantasy is that teams
        might still let the clock run out at the same frequency:

        range Att. eFG% Pts FGA 30sec
        0-10 .400 .518 29.1 28.1 5
        11;18 .250 .460 16.2 17.6 14
        19-26 .230 .447 14.4 16.2 22
        27-30 .120 .408 6.9 8.4 28
        total 1.000 .474 66.6 70.3 13.9
        41.0 .680

        This is the pessimistic end. While eFG% is effectively unchanged,
        total points have plummeted by 10 PPG, due to the increase of 1.8
        sec/possession.


        While I've made assumptions within these scenarios, the numerical
        evidence supports the idea that lengthening the shot clock could
        only reduce scoring in the NBA.

        But I'm not 100% convinced. What we can't prove beforehand is that
        players would perform identically under the changed conditions.
        Specifically, would aggressive defenders maintain their stamina for
        the extra 6 seconds?







        Mike G
      • Stephen Greenwell
        ... I would agree with this because of the simple principle that a smaller shot clock means more possessions. Lengthening the shot clock would require less
        Message 3 of 3 , Oct 15, 2003
          >While I've made assumptions within these scenarios, the numerical
          >evidence supports the idea that lengthening the shot clock could
          >only reduce scoring in the NBA.

          I would agree with this because of the simple principle that a smaller shot
          clock means more possessions. Lengthening the shot clock would require
          less shots, especially from teams like the Miami Heat who already run
          agonizingly slow. Lowering the shot clock ensures that quicker (and thus
          more) shots are taken. I'm sure that there's a point of diminished returns
          though, where the extra shots gained are cancelled out by the lower
          accuracy rating.

          >But I'm not 100% convinced. What we can't prove beforehand is that
          >players would perform identically under the changed conditions.
          >Specifically, would aggressive defenders maintain their stamina for
          >the extra 6 seconds?

          That would make for a very interesting study. Does defensive intensity and
          aggressiveness change at the shot clock diminishes? You could check it out
          by seeing if there's an increased rate of steals and blocks during the last
          five or ten seconds of the shot clock. I would imagine that the rate would
          be higher, because teams usually try to put more pressure on the ball as
          the shot clock winds down, and the offense is more often then not forced to
          take a low percentage shot.

          Along the same lines as the defenders maintaining stamina for an extra six
          seconds - Would it be possible to chart defensive effectiveness based on
          per possession based on shot clock left? Even more interestingly, how
          about defensive effectiveness for individual players as game time
          accumulates? i.e. How less effective is Bruce Bowen after 15 minutes then
          at the start of a game? This would be vital information for coaches for
          rely on defensive stoppers like Bowen and Michael Curry, and I can't say
          that I've ever run across it. The only way I would know of to determine
          such information would be to study individual game box scores and
          videotape, which is impossible since I'm in college right now ;)
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