Quote:
Originally Posted by FanCos
Hi, I hope I do not sound too harsh, but wanted to point out something that might make you reconsider your approach.
What you producded here is something called endogenous selection effect. From the draftees in the later rounds, you are effectively picking those who turned out to be good players. As such, this confounds your analysis of the expected value of a draft pick considerably.
Ex ante, the teams do not know which prospects will turn out to be 100+ games OHL players. So you are involded here in ex post analysis, where you actually compute some sort of conditional probability: suppose that given a player passes the threshold of 100 games, what will be his ppg.
Of course, that particular sample of draft picks which turns out to record more than 100 games essentially consists of good players irrespective of the draft round  now they would not otherwise play more than 100 games, right? The problem is, the teams do not have but partial information which ones, and that's why they are spread around multiple draft rounds. This restricted sample is also reason you do not find statistically significant difference between later draft rounds.
**So to compute the expected value of a draft pick, you have to feature in the drecreasing probability that a player will be actually good enough to play more than 100 games.
**EDIT: Sorry, I did not read the last post in the thread properly before replying. However, what I said about the lack of statistically significant results between rounds is still correct.

Thanks for your comment FanCos, I genuinely welcome this kind of feedback :)
First I will reply to your original objection. If I understand you correctly I think I may have simply failed to explain my intent and method well enough and will try to do so again below.
However if am misunderstanding your objection, please reply with an improved method. I googled endogenous selection effect and bias and, reading parts of your explanation, I admit that I am not sure I fully understand you.
When you said: "So to compute the expected value of a draft pick, you have to feature in the decreasing probability that a player will be actually good enough to play more than 100 games." This is what I have done. I looked at all the picks (F&D) for each round in the 5 years and calculated the % of those players (in each round) that exceeded 100 games. These are the sample set I need to characterize (mean & SD PPG). However I can't assume that all future player drafted will exceed 100 GP because, as we'd expect, players drafted in lower rounds are less likely to make and remain on roster.
So, for example, referring to Round 2 Forward data in the PDF:
57 were drafted ("# Drafted")
45 played over 100 career games ("# > 100GP")
79% of 2nd rounders played over 100 games ("% >100GP"; 45/57)
0.56 is the average PPG of these 45 players ("AvePPG")
0.44 is the Probability Adjusted Pick Value PPG ("PPG Value"; 0.56 x 79% = 0.44)
What I am suggesting this means is that, based on these data, the likely average productive value of future 2nd round forward picks is equal to .44 PPG. Some 2nd round picks will be wasted because of various reasons (won't sign, be good enough, or will quit, etc).
Similarly, the Probability Adjusted Pick Value PPG for a 5th round pick is .21. This method and this number does in fact reflect "the decreasing probability that a (5th round) player will be actually good enough to play more than 100 games."
Now to your revised objection. I do realize I probably shouldn't have used the phrase "statistically significant" because I was using it informally based on the standard deviations and PPG values being quite close and overlapping.
I am speculating that, rather than a methodological limitation to my proposed approach, the reason that forwards that exceeded 100 games have closely matched average & SD PPG is simply that if they didn't perform within that band, they would be simply moved off the roster to make room for the players that can.
Let me know if this response satisfies your objections. Thanks again.