> simple regression models outperform the fanciest machine learning ideas for this problem
This reminds me of a classic paper: "Improper linear models are those in which the weights of the predictor variables are obtained by some nonoptimal method; for example, they may be obtained on the basis of intuition, derived from simulating a clinical judge's predictions, or set to be equal. This article presents evidence that even such improper linear models are superior to clinical intuition when predicting a numerical criterion from numerical predictors."
Dawes, R. M. (1979). The robust beauty of improper linear models in decision making. American psychologist, 34(7), 571.