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Posts Tagged ‘ NBA ’

NBA Final Regular Season Bayesian Ratings

April 15, 2011
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There is a !  I’m putting together an NBA Playoffs preview; this is the first of the data for that: Here is a table of playoff bound teams and their season-long adjusted efficiency ratings. Ratings are adjusted for location, pace (obviously, since these are per 100 possessions), opponent (recursively) and rest day situation. Previous...
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Posted in NBA Rankings, NBA Stats | 1 Comment »

With or Without You: OKC, Perk, and Nazr

April 13, 2011
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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...
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Posted in NBA Adjusted Efficiencies, NBA Stats, WOWY | 4 Comments »

With or Without You: The Bulls

April 12, 2011
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With or Without You: The Bulls

A couple of months ago, I introduced my method of With-or-Without-You(WOWY) for the NBA. This time, I'll revise and expand upon the method, and take a pre-playoff look at the hottest team going: the Chicago Bulls. As Kevin Pelton chronicled, the Bulls have actually been quite healthy this year--only Joakim Noah and Carlos Boozer...
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Posted in NBA Adjusted Efficiencies, NBA Stats, WOWY | 5 Comments »

NCAA Bayesian Analysis & DSMRPI

March 7, 2011
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NCAA Bayesian Analysis & DSMRPI

 I posted my NCAA Bayesian Ratings and methodology.  Today I thought I’d update the numbers quickly and add a new twist. What is the objective in basketball? To win the game! When doing a predictive rating system (like this Bayesian method) or even trying to tell how good teams are over this season (KenPom’s...
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Posted in NCAA Basketball | No Comments »

The Carmelo Trade

February 22, 2011
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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...
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Posted in NBA Stats | 9 Comments »

On Bayesian Predictive Efficiency Rankings

February 15, 2011
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Bayesian Update

It is fairly easy to construct a retrospective efficiency rating. Take the efficiencies for each game, correct for location and rest, and then solve using an OLS regression for each team’s true efficiency rating. Nice and neat. However, how should a predictive rating work? The best approach would be to adjust for what players...
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Posted in Google Motion Charts, NBA Adjusted Efficiencies, NBA Rankings, NBA Stats | 12 Comments »

NBA Adjusted Efficiency Rankings 2-6-2011

February 7, 2011
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NBA Adjusted Efficiency Rankings 2-6-2011

It’s been a while since I last put together the fully adjusted NBA efficiency rankings. Here are the latest ratings (prev is 1-13-2011, the last time I updated): If you will recall, I last time was puzzling over what exponent to use when minimizing |residuals|^n. I tried out a number of different exponents in...
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Posted in Google Motion Charts, NBA Adjusted Efficiencies, NBA Rankings, NBA Stats | 1 Comment »

ASPM VORP All-Stars 2011

February 4, 2011
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ASPM VORP All-Stars 2011

Well, everyone else has an All-Star post up already: The actual All-Stars Mike G at APBR, with his eWins selections (also PER shown) (his thread inspired me to write this up) EvanZ, with his ezPM on the West and East All-Stars Kevin Pelton, with his WARP All-Stars John Hollinger’s look at ESPN Zach Lowe’s...
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Posted in Advanced SPM, NBA Stats | 9 Comments »

ASPM Prediction: Magic vs. Heat

February 3, 2011
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ASPM Prediction: Magic vs. Heat

The ASPM spreadsheet (download here) has a sheet for estimating a game’s results, based on team rest, location, and the rotation of players expected to play. For a quick example, I’ll look at the Magic vs. Heat game this evening. Here’s the sheet: I estimated the minutes each player would play based upon the...
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Posted in Advanced SPM, ASPM Prediction, NBA Stats | 1 Comment »

ASPM Box Score: Thunder-Heat

January 31, 2011
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ASPM Box Score: Thunder-Heat

Yesterday’s Thunder-Heat game was a fun game to watch and a great game to investigate. Oklahoma City started out with a significant advantage in this game: OKC was at home (worth 3.24 pts/100 poss) and was playing on 1 day of rest (+1.94), while Miami was playing their 3rd game in 4 days, and...
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Posted in Advanced SPM, ASPM Box Score, NBA Stats | 6 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