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Posts Tagged ‘ Bayesian Analysis ’

WOWY: NBA Finals Edition

May 31, 2011
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It’s time for the With-or-Without-You analysis of the NBA Finals teams: Dallas and Miami. For this review, I will consider a player to not have played (i.e. “Without You”) if the player played 20% or less of their average MPG. This allows us to look into the coach’s rotation decisions a bit more, while...
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Posted in NBA Stats | 1 Comment »

Bayesian Power Ratings: NBA Finals Edition

May 27, 2011
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I have updated my Bayesian Power Ratings, using the techniques described in previous posts: On Bayesian Predictive Efficiency Ratings NBA Final Regular Season Bayesian Efficiency Ratings Here are the Bayesian Ratings, updated through the end of the conference finals:
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Posted in NBA Stats | 2 Comments »

Playoff Odds 2011

April 16, 2011
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Here are my Bayesian WOWY + Tightened Rotations NBA projections for 2011! (Note: I’d still bump the Lakers up, personally… and I’m going to pick OKC>DEN for matchup and homerism reasons) Seed Tm WOWY Shortened Combined ReStdev Win 1st Win 2nd Win Conf Win Title 1 CHI 10.40 0.16 10.56 11.9 96.85% 67.32% 44.34%...
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Posted in NBA Stats | No Comments »

With-or-Without-You Compilation

April 15, 2011
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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...
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Posted in NBA Rankings, NBA Stats, WOWY | No Comments »

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 »

Bayesian Golf Ratings and Masters Preview

April 6, 2011
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That’s right, golf.  I’m taking up where Ken Pomeroy left off.  A year or two ago, he developed a rating system for golfers–basically, he created a huge regression of all players and all specific rounds at tournaments.  Each round was assigned a level of difficulty, and each player was assigned an overall rating.  His...
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Posted in Golf | 11 Comments »

Final 4 Update

April 2, 2011
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VCU and Butler have continued their run.  Before the tournament, I had them highly because they elevated their games in the regular season when playing good opponents.  They have both continued that and increased that trend. One confounding issue now with adding the “Raising their Game” (“Ag25″ in the table below) bonus is that...
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Posted in NCAA Basketball | No Comments »

Sweet 16 Update

March 23, 2011
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Well, the first weekend of the NCAA Tournament is in the books.  I don’t have much time to post, so I’ll make it quick: Predictions did fairly well. In the 8 closest 1st-round games by my pregame predictions (averaging a 52.72% favorite) my stats went only 25%–otherwise, everything matched up really well.  The other...
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Posted in NCAA Basketball | No 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