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Historical NBA ASPM (and Hall Rating) Released

June 14, 2013
By

At long last, historical Advanced Statistical Plus/Minus and VORP has been released! The permanent page is located at http://godismyjudgeok.com/DStats/aspm-and-vorp/historical-nba-aspm/. Reminder: the full statistical derivation for Advanced Statistical Plus/Minus and Value over Replacement Player is available for critique.

In addition, this visualization is including Hall Rating, a new stat modeled after the Hall of Stats’ approach for baseball. It is calculated as
(Value over Replacement Player) + x*(Value over Average)
where x is calculated such that the overall sum of VORP is equal to the overall sum of x*VOA. For all calculations, the minimum VOA is taken to be 0. This stat gives a good overall perspective on a player’s overall quality as a player, while not penalizing those who hung on to long.

Incidentally, Michael Jordan is the best player of all time (well, at least since 1974), by a huge margin. I never would have guessed that!

LeBron has his sights set on #2, and has already reached #4.

Usability note: to link a specific view of this dashboard, click on the linked chain icon at the bottom of the viz next to the envelope icon.

One Response to Historical NBA ASPM (and Hall Rating) Released

  1. Lion on October 2, 2013 at 7:18 pm

    That’s a great Job,now it would be great if you could do the exact same thing only for the playoffs. Can you do the same thing only for the playoffs?

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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
  19. Learn SQL