> I think what John is saying is that people commonly use R^2 as measure of model fit where something like root mean squared error (RMSE) gives a better measure of model fit (by measuring the distance from the true model)

I don't mean to be rude, but that is definitely not what he is saying. There are two important things I'd like to clarify:

- It is wrong to call the alternative measure "the RMSE". The alternative that the article was proposing was a made-up measure called E^2 which measures the distance from the true model.

- The author is not suggesting that people use E^2 instead of R^2 for any case. In fact, in almost all cases it is impossible to use E^2, because calculating it requires you to know the true model, and if you know the true model it would be very unlikely that you'd be wasting your time measuring other models.

The author makes it clear that E^2 isn't really to be considered an alternative when he called it the "generally unmeasurable E^2".