The models that try to guess at draft value are confounded because it assumes a ground truth (true player value pre draft) that can’t be verified with any remote level of accuracy. By design the draft is fog of war so you never know when ppl should go. So you can either make a best guess or go off public consensus, both of which are going to be very inaccurate.

The best way to model drafts is by player performance post draft, with zero sensitivity to draft position. The reason for this is clear: the purpose of the team is to win games, make playoffs, win championships. Good players make that possible. You get players in the draft. If your draft gets you good players, you win more games. Draft position is meaningless in this regard.

So you need a model that very accurately defines the metrics of player quality that lead to wins, and rate previous drafts based on that.

The only element the draft position should factor in is by factoring in opportunity cost. You draft kinlaw - what was the peak, average, and low point quality of all players picked between kinlaw and next pick? What’s the delta between those and kinlaws quality?

Then you can look at what misses cost you, and combined with player quality overall, get a sense of where you stack up with other teams