They would actually tell me that I am trying to do Grad Statistics despite only having an undergrad degree in Math so I might be punching outside of my weight class.
A binary classification though opens itself up to problems so ranking the players and by extension being able to go "if I draft a 1st round QB, or as
@RavensMania suggests an upper first round QB, what is my expected return?" is a better solution.
If you want to bring things I am avoiding into it though I am desperately avoiding trying to factor in those additional picks because I do not want to have to bring in this scenario: "You are going to draft position a QB and then position A, B, C, or D. If your draft pick performs about level X then your next year draft pick will be at one of the other 3 positions but if not it will be at one of the original 4. If your QB performs at an average level then you can use your 2nd pick also at one of the remaining 3 but if not you draft a QB again. What is the probability that you hit on your QB and 1-2 other first round picks? Furthermore what is the probability that you are at more non QB successful picks than the team with only 2 first round picks? What is the expected difference between your success and their success?"
I can solve that problem using even the knowledge I had but it would be exhausting. The Miner Problem is terrible and would have to be worked in there and I just would rather focus on not having to do that along with a bunch of other calculations that on their own I could do but would take me about an hour to do.
Also the reason I focus on the first round is because you are not looking for a QB to be the guy in round 4. You are looking for backups at that point and anything more is gravy.