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ASPM VORP All-Stars 2011

February 4, 2011
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Well, everyone else has an All-Star post up already:

So what does ASPM say?  Well, the best measure for an All-Star game would be total overall contributed value, so I’ll look at Value over Replacement Player (VORP) to quantify who should be in.  Obviously, some positions are deeper than others–particularly in the West at PG.

Here is a colorful table of the West All-Stars (minus Yao Ming and whomever the commish picks to replace him):

The West All-Stars 2011

Okay–the point guards are dominating in the West.  In fact, 4 of the top 6 players are PG’s.  Perhaps ASPM is biased towards PG’s a bit?  Then again, conventional wisdom on who the best players in the West are sort of lines up with the PG-heavy line of thinking.  Nash and Love are the 2 primary “snubs”, though one of them should get in to replace Yao.  Carmelo and Tim Duncan are lesser… however, the fans wanted to see Carmelo, and Duncan is Tim Duncan!  Besides, there aren’t a lot of “centers” in the West at all.  Marc Gasol is the best true 5!

On to the East, where the crop is much shallower:

ASPM VORP All Star 2011 East

The East All-Stars 2011

Much cleaner.  The fans made good choices, and the coaches mostly did as well.  Josh Smith should be in over his teammate Joe Johnson (again), and perhaps Brand over Bosh (hey, did anybody notice Elton Brand is having a good year?), but other than that it’s pretty clear.

The MVP debate has also been raging.  Many people are backing Rose, and the stat-geek crowd is strongly opposing that.  I don’t oppose it as strongly as most; Rose is 3rd in the league in VORP right now, with only CP3 carrying a team to a much greater extent than he has been.  Of course, CP3 is WAY ahead of Rose in this metric, so I still support CP3 for MVP….

EDIT: the data in the tables above may be found HERE.

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9 Responses to ASPM VORP All-Stars 2011

  1. EvanZ on February 4, 2011 at 11:08 am

    Top 3 in my MVP race thus far:

    Howard 7.25
    James 6.97
    Paul 6.76

    • DanielM on February 4, 2011 at 11:51 am

      What part of Howard’s value is on defense vs. offense? And for the other 2? I’m obviously hamstrung on defense by only using steals, rebounds, and blocks plus a team defense adjustment.

      • EvanZ on February 4, 2011 at 4:58 pm

        Here it is broken down into O100, D100, and REB100:

        Howard: 0.29 3.88 3.09
        James: 4.10 3.30 -0.42
        Paul: 6.71 0.01 0.04

        • DanielM on February 5, 2011 at 10:08 am

          How come James is negative on rebounding but Paul is neutral? I always thought James was an excellent rebounder for his position.

        • Greyberger on February 5, 2011 at 11:53 am

          Good defensive rebounder for position, poor offensive rebounder.

        • EvanZ on February 8, 2011 at 12:42 pm

          Yeah, to follow up on greyberger’s point LeBron’s ORR (with respect to counterpart) is about 20%. Compare that to Melo (the top-rated SF rebounder according to ezPM) who has a 33.5% ORR. Melo’s DRR is 85% compared to LeBron’s 75%. Melo’s REB100 is +1.72.

        • EvanZ on February 8, 2011 at 12:44 pm

          LeBron plays some minutes at the 4 (maybe 15% by eyeball), which probably doesn’t help either.

  2. Ben on February 4, 2011 at 2:34 pm

    I really love the Contract and Value stuff in your spreadsheet.

    There seems to be something strange with Ben Gordon’s and Gilbert Arenas’ minutes estimates though.

    • DanielM on February 5, 2011 at 10:09 am

      For Arenas, he has two separate records (1 for Orlando, 1 for Washington). I’ll see if I can spot what’s going on with Gordon.

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To-Do List

  1. Salary and contract value discussions and charts
  2. Multi-year APM/RAPM with aging incorporated
  3. Revise ASPM based on multi-year RAPM with aging
  4. ASPM within-year stability/cross validation
  5. Historical ASPM Tableau visualizations
  6. Create Excel VBA recursive web scraping tutorial
  7. Comparison of residual exponents for rankings
  8. Comparison of various "value metrics" ability to "explain" wins
  9. Publication of spreadsheets used
  10. Work on using Bayesian priors in Adjusted +/-
  11. Work on K-Means clustering for player categorization
  12. Learn ridge regression
  13. Temporally locally-weighted rankings
  14. WOWY as validation of replacement level
  15. Revise ASPM with latest RAPM data
  16. Conversion of ASPM to" wins"
  17. Lineup Bayesian APM
  18. Lineup RAPM
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