For a while I have been playing around with a version of my draft model that includes the position the player was taken in the draft. The idea is completely derivative of Layne Vashro's "Humble" version of hs Expected Win Peak model. But it's a good idea, certainly as a test of the model and exploratory exercise.
The are two advantages to this approach, looking at the change in the coefficients we can infer something about what scouts and teams are picking up that raw player stats are not seeing and we can get an estimate of the relative independent percentage contribution of the expert opinion in addition to the stats.
The big mover in terms of relative coefficient value between the P-AWS model and the Scouting Informed model is the age adjustment. That was somewhat expected given that the age adjustment in the P-AWS model consistently came in 10%-15% higher than the aging curve I developed looking at NCAA players. In effect, because highly scouted players tend to enter the draft earlier, a portion of the age coefficient acts as a proxy for some of the things team scouting values. In the Scouting Informed version, age falls to 10% below the age curve, indicating that there maybe a slight overvaluation of youth in actual drafts.
The downside is that we don't actually know who will be drafted so can not actually adopt the same methodology with our projected draft class, but only approximate it. Also, draft order itself only represents a blunt approximate of the scouting consensus with heavy doses of GM idiosyncrasies, 'fit' and need considerations and the like thrown into the mix. (cough Anthony Bennett cough). Ideally one would want to have specific draft contemporary scouting analysis to feed into the model that could be tested independently and weighted in relavent pieces, for example, defensive ratings, character ratings, shooting mechanics, and so on, to maximize the information in the model.
But, absent that level of detail the lump sum rating still provides some information. One of the more valuable insights is the scale of difference between the pre stats P-AWS model and the Scouting Informed version.
Here is an image of the table using Draft Express as the draft order proxy:
And here's the table in Google Doc's: Table Link.
The biggest mover is Adreian Payne, who I like, but the P-AWS model doesn't. In the last two out of sample drafts, older bigs have been the largest outliers, and when the model is separated into front and back court players the age curve is less strongly correlated to back court players. So, I can imagine that Payne is a player the stats model underestimates.
Another big mover is Wiggins, though he still rates as only the eighth best player.
Stats model favorite Jordan Adams has a large relative fall, but still ranks in the top ten.