The article is not about models being indistinguishable from random classifiers, the difference there should be very significant even on the tasks it discussed. Instead, the problem originates from the small differences in test set performance between the top N models. While that difference may very well increase when moving from binary classification to a more technically involved regression task, that is by no means guaranteed, and the main points of the article still apply.