web analytics

Posts Tagged ‘ With-or-Without-You ’

WOWY: NBA Finals Edition

May 31, 2011
By

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...
Read more »

Tags: , , , , , ,
Posted in NBA Stats | 1 Comment »

Chart: With or Without Inefficient Scorers

May 23, 2011
By
Chart: With or Without Inefficient Scorers

This is just a quick chart dump, based upon Neil Paine’s research at Basketball Reference:
Read more »

Tags: , , , , ,
Posted in NBA Stats | 1 Comment »

A Review of Adjusted Plus/Minus and Stabilization

May 20, 2011
By
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...
Read more »

Tags: , , , , ,
Posted in NBA Stats | 28 Comments »

Round 2 Predictions

April 30, 2011
By

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...
Read more »

Tags: , , , , ,
Posted in NBA Stats | No Comments »

Playoff Odds 2011

April 16, 2011
By

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%...
Read more »

Tags: , , , , , ,
Posted in NBA Stats | No Comments »

With-or-Without-You Compilation

April 15, 2011
By

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...
Read more »

Tags: , , , , , , , ,
Posted in NBA Rankings, NBA Stats, WOWY | No Comments »

With or Without You: OKC, Perk, and Nazr

April 13, 2011
By
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...
Read more »

Tags: , , , , , , ,
Posted in NBA Adjusted Efficiencies, NBA Stats, WOWY | 4 Comments »

With or Without You: The Bulls

April 12, 2011
By
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...
Read more »

Tags: , , , , ,
Posted in NBA Adjusted Efficiencies, NBA Stats, WOWY | 5 Comments »

With or Without You: OKC and Nick Collison

January 7, 2011
By
With or Without You: OKC and Nick Collison

The concept of With-or-Without-You is very basic. If you are playing, is our team better or worse? If the team is worse with you available, then that’s a really bad sign! It’s the core concept behind such basketball metrics as +/-, Statistical Plus/Minus and Advanced Plus/Minus. In baseball, Tom Tango and MGL work with...
Read more »

Tags: , , , , ,
Posted in NBA Adjusted Efficiencies, NBA Stats, WOWY | 4 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