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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Tags: NBA, NBA Playoffs, Projections, Statistics, Team Ratings, With-or-Without-You
Posted in NBA Stats | No Comments »
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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Tags: Bayesian Analysis, NBA, NBA Playoffs, Projections, Statistics, Team Ratings, With-or-Without-You
Posted in NBA Stats | No Comments »
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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Tags: NBA, NBA Playoffs, Projections, Team Ratings
Posted in NBA Stats | 3 Comments »
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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Tags: Bayesian Analysis, Google Motion Charts, NBA, NBA Playoffs, Projections, Statistics, Team Ratings
Posted in NBA Rankings, NBA Stats | 1 Comment »
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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Tags: Bayesian Analysis, Game Prediction, NCAA Tournament, Projections, Statistics, Team Ratings
Posted in NCAA Basketball | No Comments »
If you are choosing NCAA tournament picks in a LARGE group (like ESPN), then, if possible, you need to account for what the masses have chosen in making your own selections. Fortunately, ESPN publicly shows what everyone has picked–and that lets us account for them. As the number of people approaches infinity, the formula...
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Tags: Bayesian Analysis, NCAA Basketball, NCAA Tournament, Projections, Statistics, Team Ratings
Posted in NCAA Basketball | No Comments »
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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Tags: Advanced SPM, NBA, Player Ratings, Projections, Salaries, Statistics, Trade Analysis, VORP
Posted in NBA Stats | 9 Comments »
A few days ago, I put up a massive post on . Nathan Walker (the Basketball Distribution) commented that I should apply the system to NCAA basketball, and so I have. Thanks to Ken Pomeroy’s incredible NCAA basketball database, the data was quite easy to obtain. Since he already compiles a fully adjusted efficiency...
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Tags: Bayesian Analysis, NCAA Basketball, Projections, Stat Theory, Statistics, Team Ratings
Posted in NBA Adjusted Efficiencies, NBA Rankings, NCAA Basketball | 1 Comment »
It is fairly easy to construct a retrospective efficiency rating. Take the efficiencies for each game, correct for location and rest, and then solve using an OLS regression for each team’s true efficiency rating. Nice and neat. However, how should a predictive rating work? The best approach would be to adjust for what players...
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Tags: Bayesian Analysis, Google Motion Charts, NBA, Projections, Stat Theory, Statistics, Team Ratings
Posted in Google Motion Charts, NBA Adjusted Efficiencies, NBA Rankings, NBA Stats | 12 Comments »
The ASPM spreadsheet (download here) has a sheet for estimating a game’s results, based on team rest, location, and the rotation of players expected to play. For a quick example, I’ll look at the Magic vs. Heat game this evening. Here’s the sheet: I estimated the minutes each player would play based upon the...
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Tags: Advanced SPM, Game Prediction, NBA, Projections, Statistics
Posted in Advanced SPM, ASPM Prediction, NBA Stats | No Comments »
