web analytics

Posts Tagged ‘ Trade Analysis ’

With-or-Without-You Compilation

April 15, 2011
By

A collection of With-or-Without-You tables for playoff teams.  All regressions were stabilized with about 30 games worth of “average for the team” performance.  Not all regressions have the last game of the season included. Oklahoma City Thunder: WOWY equally weighted over season Eff Mar Off Eff Def Eff Games Equiv+/- Team 9.4 8.1 -1.3...
Read more »

Tags: , , , , , , , ,
Posted in NBA Rankings, NBA Stats, WOWY | No Comments »

With or Without You: OKC, Perk, and Nazr

April 13, 2011
By
With or Without You: OKC, Perk, and Nazr

In continuing my series of With-or-Without-You (WOWY) analyses, I will next look at my hometown Oklahoma City Thunder, one of the hottest teams going into the playoffs. In the first two posts on WOWY, I looked at Oklahoma City in January(before the trades), and yesterday I looked at the Bulls and their strength...
Read more »

Tags: , , , , , , ,
Posted in NBA Adjusted Efficiencies, NBA Stats, WOWY | 4 Comments »

The Carmelo Trade

February 22, 2011
By
The Carmelo Trade

Carmelo Anthony was FINALLY traded yesterday, in a mega 3-team deal. How did the teams make out? There are several good trade analyses around, but none of them are really focusing on the financial aspect. Kevin Pelton’s article is a good primer on the trade as a starting point, and Joe Treutlein at Hoopdata...
Read more »

Tags: , , , , , , ,
Posted in NBA Stats | 9 Comments »

DSMok1 on Twitter

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