Milwaukee Bucks Meta Wins Produced

Professor Berri just posted his  Original Win Score wins produced numbers at The Wages of Wins Journal, so now at the halfway point I am able to provide “Meta Wins Produced” numbers.  That’s where I combine my Marginal Win Score numbers, B-R.com’s “Win Shares”, and Original Win Score.  These are the three metrics I respect the most.

I apologize for my lame ass charts on this site.  I have to do better, but for now, the first number is MWS, the second number is Win Shares, the third is  OWS, and the fourth is Meta Wins Produced, an average of all 3.

……………………………MWS………..Win Shares……..WS……….META

Andrew Bogut………..3.5…………….3.6………………4.8…………4.0

Luke Ridnour…………2.8…………….3.6………………3.3………….3.2

Ersan Ilyasova……….2.1…………….2.6………………3.0…………2.6

Brandon Jennings…..2.8…………….2.3………………1.8………..2.3

Hak Warrick…………..1.4…………….2.1………………0.9………….1.5

Carlos Delfino…………2.6……………1.9……………….2.7…………2.4

Luc Moute……………..1.6……………1.6………………..1.6…………1.6

Charlie Bell…………….1.0……………1.2………………..0.2………..0.8

Kurt Thomas…………..0.4…………..0.5………………..0.2………..0.3

Michael Redd…………0.3……………0.5………………..(-0.1)…….0.2

Jodie Meeks…………..0.4……………0.4………………..0.6………..0.4

Comparison of the Metric Results

The results that were the most similar, strangely enough, were MWS and Win Shares, which had a 20.2% difference on average.  The two metrics are nothing alike in their calculations, but often produce very similar results and  I can’t explain why.  On the other hand, MWS and OWS, which are spawned from the same metric, had the greatest average difference at 30.3%.  That’s odd.  Finally, OWS and Win Shares differed by 28.3%.

The metric that was closest to the Meta Wins result was MWS, with a 13.2% average difference.  Win Shares was next with an average difference of 18.1%, followed by OWS at 20.5%.

MWS is on an island with respect to Ridnour, Ilyasova, and Jennings.  For the former two its on the low end.  For the latter its on the high end.  The reason is probably because it directly attributes statistics produced by counterpart opponents to the specific player.  Ridnour and Ilyasova suffer because of it,  Jennings benefits.  I don’t know if that means Jennings is a great “defender”, but point guards have a habit of playing less productively and less efficiently when Jennings is guarding them as opposed to Ridnour.

The one result that is identical in all three is Luc Moute’s 1.6 wins produced.  The strange thing about that is Moute does most of his contributing through defense and rebounding, not scoring.  The metrics tend to deviate on such players but not in this instance.

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4 Responses to “Milwaukee Bucks Meta Wins Produced”

  1. Josh Says:

    Ty,

    I did some correlations in Excel and the differences between the correlations are not that big.

    MWS to WinSh – .921
    MWS to WinSc – .917
    WinSh to WinSc – .899

    Basically, all the metrics are highly correlated and none of them stands out as particularly different from the others. It appears that about 90% of The wins total is the same from system to system.

    Josh.

  2. tywill33 Says:

    Thank you my man!! That’s awesome work!!!

    Hey, what happened to the Badgers on Sunday?? I heard they were down 16 at home to Penn State? Do they miss Luere (sp?) more than I reckoned. You said your analysis got about the same results, right? They shouldn’t struggle with PSU at home should they?

    Thanks again for the great information!

  3. Josh Says:

    Ty,

    They struggled more than they should have with Penn State. I think it comes down to PSU hitting shots that they don’t normally make.

    However, the loss of Leuer is huge. By my numbers, losing him is losing about 4.2 points of victory margin if he’s replaced by an average player. Ryan is good about not replacing his minutes with those of an average player, but it still means 2-3 points of victory margin lost. That moves Purdue from a 2 point favorite to something more like 5 points.

    One of the stats that I calculate is player efficiency margin. It’s the same stat as team efficiency margin against Div. 1 average opponent. It takes the difference between that player’s offensive efficiency and defensive efficiency. Leuer clocks in at 49.2. You have to divide that by 5 because of the other players on the team, so he is worth about 1/10th of a point above average every two possessions (one for the Badgers and one for the opponent).

    To give some context, here are the player efficiency margins for the only players over 40.0 in efficiency margin that I’ve calculated:

    Robbie Hummel – 50.0
    Draymond Green – 42.2
    Evan Turner – 43.6

    I only have results for OSU, MSU, NW, Michigan, PSU, and Purdue. And those were only when they played the Badgers. I’m planning to do the entire conference when kenpom.com updates player stats again this Sunday/Monday.

    The upshot is that Leuer is one of the very best in the conference and losing him hurts. That said, the Badgers are a reasonably deep team, so they can weather it better than some of the other teams in the conference.

    • tywill33 Says:

      Excellent work!

      What I love is, you seem to be the only one who agrees with me that basketball is contested between two sides of five players, and that the comparative production of any given five will decide the game (or “match” as the Professor from England whose NCAA Power Rankings I have in the links likes to say).

      As for Bucky, Leuer clearly rocks. That Nankavil (sp?) had a ball game last night… Hughes did not.

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