@PlusEVAnalytics Yes, this should be an obvious approach to any good modeler. Curating a good feature set through EDA should lead to outperforming those throwing it all into ML models. You also get the benefit of knowing the data at a deeper level, making iterating easier if performance declines
@RiggsBarstool This is me. 13 HDCP who fired a 77 (+6) last year and rarely gets out because of kids. If he does it again or the 5 HDCP has a round you have to question it
@adplacksports 2x based on data golf? I haven’t flushed out their calc entirely but find it interesting they have it that much larger than others. The adjustments don’t really align imo. Zalatoris only gets a 0.1 adjustment whereas Noren (if he was in field) would get 0.3 and he’s made 1/4 cuts