APBRmetrics

I don't think I agree with this method of assessment. Generally, the highest picks go to the worst teams. It would be hard for any prospect to post a good BPM on the 76ers. If we judged prospects based on rookie BPM, we wouldn't think highly of Kevin Durant (-1.4) (as an example).

2. Computing power is a major obstacle to this type of study. I'd think data availability is a bigger issue. Consider, for example the SportVU data set: Estimating 100 bytes per sample, 25 samples per second, 60 seconds per minute, 48 minutes per game, 41 home games per team per season, 31 NBA team...

Trying to model the value of players' micro moves using sportvu coordinates is exactly what Chris and I have been doing (and I thought what this thread was about). We are very much interested in, for example, whether stationing a shooter in the weakside corner 3 keeps a help defender out of the lane...

Basketball is not a... in the sense that we can judge each decision (pass, drive, etc) independent of what has happened before and more importantly, what will happen after. we can't? why not?... For example, we might see a guard on one wing swing the ball to a big man at the top of the key. That pa...

Chris Baker and I have been looking at this. Here are some quick thoughts based on what we've encountered. 1. I like the suggestion in this thread to study the action/movements/formation of everyone based on the eventual success of the possession. Basketball is not a 1-step Markov process in the sen...

For simplicity, call restricted area and 3-point FGA "good" shots. Call the rest "bad" shots. I looked at the ratio of bad to good for teams in the last 19 seasons. Flip's teams accounted for the top 3 and 5 of the top 7. Every 2014 team and 29 2015 teams shot more good than bad....

Perhaps, but this does make a lot of sense logically. The "best" will converge on the single best approach. Skills will overlap, be similar, mindsets will be similar. A variety of very dissimilar parts will, as Steve says, have far more synergy. Does this logic enhance your interest in me...

Excellent post. Chris Baker and I looked into this idea a bit in Chapter 8: Introducing Player Involvement Metrics of Basketball Analytics (2013). We introduced ways to measure the balance in a team's production. For example, does the team spread the assists or is one player largely responsible for ...

Follow-up submission: CPR ratings are not a “draft in this order” list. No objective model should be used in that fashion because no model can account for everything that a team must consider when making their selections. The value in a draft model is highly dependent on how well its results can be ...

Lineup entropy might be of some use here in understanding how coaches use/vary lineups. A while back, I found some evidence that low lineup entropy in one season (more consistency in lineups) led to early season success the following year. http://www.basketballanalyticsbook.com/2013/12/01/lineup-ent...

For those interested, I published an article on the existence of hot hands in the 3-point competition (and home run derby) a couple years ago.

http://onlinelibrary.wiley.com/doi/10.1 ... 9/abstract

I think pace is an issue also. For Joseph Young to be rated almost as highly as Frank Kaminsky at the same age is a pretty big red flag. For him to be rated higher than Delon Wright seems almost criminal. I'm curious - using your methodology - how the Iona stars would rate. Or maybe the BYU stars. ...

CPR gets around this by focusing only on each individual’s top 10 performances in each statistic. if a player plays well against non-conference teams, or mid-level teams, and poorly against top tiered teams, does this not affect their rating?... CPR has been effective projecting both high picks tha...

Seth Tuttle has a CPR of 1.7. He slides in 52nd (just ahead of Christmas) on my rankings.

Steve

Rank Player CPR 1 D'Angelo Russell 10.4 2 Jahlil Okafor 9.1 3 Karl Towns, 7.6 4 Kevon Looney 7.1 5 Bobby Portis, 6.5 6 Myles Turner, 6.4 7 Cameron Payne 6.2 8 Stanley Johnson 5.6 9 Tyus Jones 5.5 10 Justise Winslow 5.2 11 R.J. Hunter 5.1 12 Christian Wood 5.0 13 Terry Rozier 4.7 14 Jordan Mickey 4.3...