Quick post on an in process update of my draft model. Essentially I am working in the consensus high school ratings provided by the Recruiting Services Consensus Index (RSCI) for college basketball.
There are a couple of challenges to this, the first being that not every top pro prospect gets a RSCI rating, especially when looking at foreign prospects. Second, in the analysis I found that there is a quick degradation of the information conveyed by the ratings, which can reach into the hundreds. Essentially for NBA prospects I was only able to pick up a signal in the top twenty or so rankings, and even then a log scale transformation seemed to pick up information best in the training data. Keep in mind, for example, that the current favorite for the regular season MVP, Steph Curry, was not even rated by the RSCI service, because he wasn't considered good enough in high school to even rate.
Age entering the draft and RSCI rating are positively correlated. Essentially players who are highly rated coming out of high school are more likely to enter the draft earlier, because of the regard scouts and teams hold them in, and, therefore, the more money they can make by leaving. A less heralded player may both take more time to earn a starting position on the team and even with a similar freshman year performance would be more likely to stay in school as a first round selection would be far from guaranteed until a longer record of high performance is demonstrated.
Therefore, the biggest single difference, other than the new variable, between the RSCI-PAWS (beta) and the PAWS model is the age adjustment. The age coefficient falls be approximately 13% by including the RSCI ratings, which ends up aiding some non-blue chip rated prospects entering the draft a bit older.
In terms of draft order the most significant difference is Jahlil Okafor moving from third to first, and D'Angelo Russell moving from first to second. Willie Stein also moves up due, in part, to the lessened emphasis on age.