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Posts Tagged ‘ Player Ratings ’

ASPM Notes and Viz Update

December 6, 2012
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ASPM Notes and Viz Update

I have added another pane to my 2012-13 ASPM/VORP Tableau Visualization, allowing a better look at the distribution of talent across positions in the NBA. Powered by Tableau The new position vs. ASPM chart is quite interesting: there is an amazing lack of talent/performance right now at the 2,3, and 4 positions outside of...
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2012-2013 ASPM & VORP Released

November 14, 2012
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A quick note: 2012-2013 ASPM & VORP have now been released! See the new 2013 ASPM page. A few early notes: The cream is already rising to the top after 4 to 8 games for each team. LeBron James is #1 in total VORP, with an ASPM almost exactly the same as last year....
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Overrated and Underrated via RAPM (Part 2)

November 10, 2012
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Overrated and Underrated via RAPM (Part 2)

A week ago, I discussed overrated and underrated players over the past 12 years, evaluated by comparing popular box-score stats with Jeremias Engelmann’s 12 year average Regularized Adjusted Plus/Minus (RAPM) dataset. For a primer on the virtues of RAPM (in large samples), see my article reviewing the state-of-the-art of adjusted plus/minus and stabilization. This...
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Posted in NBA Stats | 6 Comments »

Underrated and Overrated Via RAPM

November 2, 2012
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Underrated and Overrated Via RAPM

In several of my recent articles, I have been using Jeremias Engelmann’s 12 year average RAPM dataset. Here, I will look at what players may have been underrated or overrated by even advanced stats over the course of the last 12 years. I decided to use PER and WS/48 as my advanced stats to...
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Posted in NBA Stats | 10 Comments »

RAPM vs. MPG (A Look at Replacement Level)

October 30, 2012
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RAPM vs. MPG (A Look at Replacement Level)

One of the big ongoing questions in NBA stats and player valuation is where to set “replacement level”.  I believe an empirical approach to determining that level is best. Jeremias Engelmann has produced an outstanding resource in his 12 year average RAPM data.  Since so many years are used, it is quite stable; however,...
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2013 NBA ASPM Team Projections

October 29, 2012
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Here are my 2013 NBA Team Projections, based on my ASPM player projections. For playing time, I roughly used ESPN’s Fantasy Projections, tweaked so each team totaled 475% of the minutes (I assumed the rest of the minutes would go to replacement level (-3.25) players). Here are my regular season projections: I have updated...
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Posted in NBA Stats | 9 Comments »

2012 NBA VORP per Game Vizualization

June 5, 2012
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Just playing around with Tagxedo. Here are the top 100 players of the 2012 NBA regular season, as measured by VORP-Gm (VORP per game played), only including play for the team the player ended up with (if traded).
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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 | 28 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 »

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