web analytics

Posts Tagged ‘ Charts ’

Visualization: 2012 VORP Treemap

January 27, 2012
By

Inspired by Evan Zamir’s use of a treemap to visualize WARP over at The City, I created a treemap to visualize ASPM VORP for the 2012 season-to-date.  I used Google Docs and the treemap-gviz widget to construct the visualization.  I used the latest iteration of the ASPM framework to compile the data, and selected...
Read more »

Tags: , , , ,
Posted in NBA Stats | 2 Comments »

Chart: With or Without Inefficient Scorers

May 23, 2011
By
Chart: With or Without Inefficient Scorers

This is just a quick chart dump, based upon Neil Paine’s research at Basketball Reference:
Read more »

Tags: , , , , ,
Posted in NBA Stats | 1 Comment »

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 »

Team Charts 2011

April 15, 2011
By

Here are all of the Adjusted Efficiency Team Charts for the 2011 NBA regular season.  These are adjusted for opponent (average for their whole season), rest-day-situation, and location. Here are links to each image (so as to avoid flipping through the slideshow): Atlanta Hawks Boston Celtics Charlotte Bobcats Chicago Bulls Cleveland Cavaliers Dallas Mavericks...
Read more »

Tags: , , , , ,
Posted in NBA Adjusted Efficiencies, NBA Rankings, NBA Stats | 2 Comments »

DSMok1 on Twitter

To-Do List

  1. Google Motion Charts for each position, including salary and contract value
  2. Discussion of salary/contract value
  3. Aging curves for individual components (ORB%, Blk%, etc.)
  4. Comparison of residual exponents for rankings
  5. Comparison of various "value metrics" ability to "explain" wins
  6. Publication of spreadsheets used
  7. Work on using Bayesian priors in Adjusted +/-
  8. Work on K-Means clustering for player categorization
  9. Learn ridge regression
  10. Temporally locally-weighted rankings
  11. WOWY as validation of replacement level
  12. Revise ASPM with latest RAPM data
  13. Conversion of ASPM to" wins"
  14. Recursive WOWY Team Ratings
  15. Lineup Bayesian APM
  16. Lineup RAPM