Let’s talk about Kevin Yu, I think most of us are aware of how good his T2G game is right now. I was quite surprised to see this week’s model price him in the outright at 157 (course fit&history), the baseline model has him at 118. For the avoidance of confusion, I expected Yu to be priced shorter.
I guess my question is, how does the model account for players who have no course history, like Yu?
Intuitively, just thinking about Yu’s game, I’d have thought he is a great fit for Scottsdale (let’s forget he is a Scottsdale resident for the purpose of this question since I wouldn’t expect any model to account for those sorts of variables), he’s a weak putter, he’s got great T2G stats, he does well on risk/reward holes, but he’s priced above his baseline at Scottsdale. Is this because we have no data for Yu playing the course or am I missing something? Would be great to understand a bit more about how the model incorporates no course history.
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You can get a better idea of how we came up with Yu’s final skill on the skill decomposition page. He is getting a lot of positive bumps off baseline, but for course history he gets a negative for having never played. Course fit only uses a player’s attributes (e.g. DD, DA) and so is not dependent on them having played the course. Our fit stuff is pretty basic, so this week it essentially gives the good players a small positive bump.
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