There's not much reason to think that it's being fooled, though, unless there's been some massive change in either the NHL or the leagues that feed it. You are correct that the model is decidedly unproven.
Reasons that I'm skeptical:
1. His model makes an arbitrary cutoff for what constitutes a star: 0.45 ppg for a defenseman and 0.7 ppg for a forward (my numbers above were a bit off, I went back and checked.) Where did these numbers come from? Why are they significant? What if I tweak them up or down 0.05 ppg, do the model's results suddenly go down the toilet?
2. His method seems to be to assume that players that score a lot in their feeder leagues will generally score a lot in the NHL, and thus have a better chance at becoming a "star". That seems like an uncontroversial position, and the biggest insight, that short and Russian players are overlooked, is not exactly novel. I don't know about Kucherov, but I'm pretty sure I remember Point, DeBrincat, and some of the other guys he pumps as late round steals were seen as steals from the moment they were drafted.
As an aside, he's a big Marco Rossi booster and so am I. I don't think you need his fancy model to think that Rossi went too late in 2020, but if he ends up as a "star", I'll absolutely count it as a win for him.
3. He really hasn't provided evidence that having more stars on your team is the key to winning.
I think time will settle this one. If he ranks draft eligible prospects according to star probability, we can go back and check his list against who teams actually chose and who is right more often.