NBA Western Conference MWS win production breakdown

Earlier today I posted  a chart featuring each Eastern Conference team’s performance in the 3 main statistical categories that make up the win metric I call “Marginal Win Score”.  To be honest with you, I don’t know why I haven’t done such a breakdown before.  Its  actually one of the more interesting things I have done in a very long time (I’ve been in an “idea” slump that matches the Bucks shooting slump).  I guess I’ve never looked specifically at how each team produces wins.

Tonight I follow the earlier post with a chart featuring the same breakdown, this time for Western Conference teams.  To review, the three main categories making up the chart are “Efficient Scoring” per game (Points – FGAs – .5FTAs); “Possession Creation” per game (Rebs + Stls – TOs); and “Net Helpful Acts” per game (.5Ass + .5Blks – .5PFs).  The first category measures a team’s ability to turn possessions into points; the second category measures a team’s ability to gain and protect possession of the basketball; and the last category measures those other box score statistics that do not create points or possessions, but tend to impact a team’s ability to do so.

Once again, when you are reading the chart, the first column of numbers is the team and opposition Efficient Scoring per game, the second column is the team and opposition Possessions Created per game, the third column is Net Helpful Acts per game, the fourth column is the team’s “Total Win Contribution”, which is just the sum of the first three columns (the team’s overall Marginal Win Score) divided by 10 (for the five players on the court at all times, with half their time spent on offense and half on defense).  The last two columns are the expected winning percentage that corresponds to the given Total Win Contribution, and the final record the team would be expected to achieve if it kept up the numbers.  The teams are listed according to the order they and their division appear in the basketball-reference.com Western Conference standings.

As I said in the Eastern Conference post, if you want to know where your team is particularly strong or weak, compare its team and opposition numbers against the corresponding NBA average in each particular category.  For Scoring Efficiency the average is (5.30), for Possession Creation the average is (33.80) and for Net Helpful Acts, the average is (2.40).  If your team is doing better than the average in any particular “Team” category, you can generally say their “offense” in that particular category is helping produce wins above average.  The reverse can be concluded about your team’s “defense” by doing the same comparison with the team’s “Opp” averages.

I will reserve comments about the particular Western Conference teams production for a follow-up post, other than to make a point regarding the Phoenix Suns.  Phoenix demonstrates how bad defense can completely nullify even great offense.  The Suns are one of the best scoring teams in the NBA, but its only getting them a .500% result in the efficient scoring category because they are allowing virtually the same production to their opponents.

Also, one last point.  Or two points.  One, it appears that the very best a team can do in scoring efficiency is somewhere in the +11 points range.  Why that is the top point, I don’t know.  And secondly, I hope these two charts illustrate for Bucks fans just how unusually pathetic the Bucks lack of “ball-into-basket” skills truly are.

NBA WESTERN CONFERENCE MWS STATISTICAL BREAKDOWN

Utah Jazz 7.28 33.55 3.05
Opp 5.11 33.19 0.88
MWS 2.71 0.36 2.07 0.514 0.59% (48-34)
OKC Thunder 8.22 36.06 1.71
Opp 6.99 32.25 1.17
MWS 1.23 3.81 0.54 0.558 0.60% (49-33)
Denver Nuggets 11.07 33.42 1.61
Opp 7.15 35.52 2.84
MWS 3.92 2.11 -1.23 0.481 0.58% (48-34)
Port Trailblazers 2.47 34.73 2.55
Opp 7.41 30.41 1.34
MWS -4.94 -2.52 1.21 0.059 0.51% (42-40)
Minn Twolves 4.01 34.85 1.21
Opp 11.02 37.25 4.81
MWS -7.01 -2.41 -3.59 -1.301 0.28% (23-59)
LA Lakers 8.14 38.35 3.68
Opp 1.88 35.13 2.75
MWS 6.26 3.22 0.93 1.051 0.68% (56-26)
Phoenix Suns 11.57 30.95 2.82
Opp 11.88 36.44 2.51
MWS -0.31 -5.49 0.32 -0.548 0.41% (33-49)
GS Warriors 5.34 35.11 2.11
Opp 9.78 37.13 5.78
MWS -4.44 -2.02 -3.67 -1.013 0.33% (27-55)
LA Clippers 4.25 33.27 2.35
Opp 7.28 33.78 2.81
MWS -3.03 -0.51 -0.46 -0.401 0.43% (36-46)
Sac Kings -0.74 33.96 0.27
Opp 7.62 34.44 2.52
MWS -8.36 -0.48 -2.25 -1.109 0.31% (26-56)
SA Spurs 11.21 37.59 5.01
Opp 4.21 32.81 2.36
MWS 7.01 4.78 2.65 1.444 0.75% (61-21)
Dall Mavericks 9.69 35.35 4.79
Opp 1.63 34.83 2.16
MWS 8.06 0.52 2.63 1.121 0.69% (57-25)
NO Hornets 4.51 35.28 1.64
Opp 4.12 31.91 2.37
MWS 0.39 3.37 -0.73 0.303 0.55% (45-37)
Houston Rockets 9.09 34.48 4.01
Opp 6.98 33.83 1.63
MWS 2.11 0.65 2.38 0.514 0.59% (48-34)
Memphis Grizzlies 3.64 35.06 1.69
Opp 7.15 33.41 2.95
MWS -3.51 1.66 -1.26 -0.311 0.45% (37-45)
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4 Responses to “NBA Western Conference MWS win production breakdown”

  1. Fred Bush Says:

    You don’t seem to be counting current records in your projections. I realize it’s basically a throwaway stat but a better way to do it would be to take the current record as a given and use the % to project how many of the remaining games the team will win. So instead of the Spurs being projected at 61-21 (75%), we would take their current 29-4 record, give them 75% wins in their remaining 49 games (37-12), and end up with 66-16.

  2. tywill33 Says:

    Actually, I like your idea. That’s exactly how I should have done it, but I was lazy. But you’re right in all respects.

    Ty

  3. Larry Gore Says:

    It is actually a bit debatable which is better as the current record has been affected by random variance while the projection assumes neutrality on random variance and neutrality on random variance is the safer assumption. But the current record captures team game to game performance consistency and clutchtime performance while the projection does not. So as I said it is debatable.

  4. Larry Gore Says:

    My terminology is somewhat overlapping here. “Game to game performance consistency” is at least partly random variance. Part of it is different than that though, in my mind.

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