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Posts Tagged ‘ Player Ratings ’

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 »

A Review of Adjusted Plus/Minus and Stabilization

May 20, 2011
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A Review of Adjusted Plus/Minus and Stabilization

As I prepare to release my first work based on the Adjusted Plus/Minus and derivative methods, I felt it would be wise to write a plain-English review of the state-of-the-art of Adjusted Plus/Minus and its derivatives, or at least what is known in the public domain. What is Plus/Minus? Plus/Minus, at its core, simply...
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Posted in NBA Stats | 10 Comments »

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 »

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 »

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 »

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 »

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 »

Center Comparison Chart (and K-Means Clustering)

January 19, 2011
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Center Comparison Chart (and K-Means Clustering)

Last week, I unveiled a Google Motion Chart that included a large number of advanced stats comparing point guards. This week, we'll start at the other end: centers. I actually am including players classified as either C or PF/C by BasketballValue, where I got the position information. Most people feel that the position...
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Posted in Advanced SPM, Google Motion Charts, K-Means Clustering, NBA Stats | 8 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