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Posts Tagged ‘ NBA ’

Adjusted 4-Factors Visualization

February 22, 2012
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Adjusted 4-Factors Visualization

Evan Zamir at The City recently unveiled Adjusted 4-Factors at the individual level, using a 2.5 year sample size and a Ridge Regression approach. The results are very interesting. Here, I’m simply converting his initial work into an interactive visualization. Powered by Tableau
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Posted in NBA Stats | 1 Comment »

Visualization: 2012 VORP Treemap

January 27, 2012
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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...
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Posted in NBA Stats | 2 Comments »

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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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 »

Chart: With or Without Inefficient Scorers

May 23, 2011
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Chart: With or Without Inefficient Scorers

This is just a quick chart dump, based upon Neil Paine’s research at Basketball Reference:
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Round 2 Predictions

April 30, 2011
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Quickly (Updated WOWY Bayesian Ratings, roughly done due to lack of time:) CHI ATL MIA BOS OKC MEM LAL DAL 98.4% 1.6% 69.9% 30.1% 67.1% 32.9% 52.3% 47.7% CHI vs ATL MIA vs BOS OKC vs MEM LAL vs DAL 4 to 0 45.3% 4 to 0 10.3% 4 to 0 9.1% 4 to...
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NBA Hex Colors

April 28, 2011
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I’ve been playing around with some charts, and I thought it might be nice to have the NBA team colors in hex format: Team Color1 Color2 Color3 Color4 ATL #1B1C48 #FF2728 #C2C3BD   BOS #00611B #000000     CHA #3E6085 #F26432 #D1D2D4   CHI #B00203 #000000     CLE #8B0034 #F9B433 #002859   DAL...
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Visualization: The Brightest Stars in the NBA

April 27, 2011
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Visualization: The Brightest Stars in the NBA

I’m working on a new metric to quickly measure a player’s single-game contribution (a slightly more complex “game score”). I’ve tabulated the results for every game played this year, and that lets me do this: Here are the brightest stars in the NBA, by dominant superstar performances this year. I’m giving 3 points for...
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Posted in NBA Stats | 6 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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Tightened Rotations

April 16, 2011
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After a ton of math and fudging, I’ve come up with these estimates for how much a “tightened rotation” will help each team in the playoffs. I took close games between playoff teams in the past 1.5 months, figured out the top rotation (MPG/player) for each team when everyone’s healthy, and took the max...
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Posted in NBA Stats | 3 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