Predicting a range is clearly useful, but having the value fall into that range or hit the mean value of the range does not always mean the prediction is better.

Example:
Prediction 1: 90-100; Prediction 2: 50-150. Actual: 101
The first is clearly the better prediction, although the actual is outside the range and further from the mean than the second.

What you really want to do is 1) reward a predicted mean value (i.e. max+min/2) that is close to the actual; 2) reward a smaller range preferentially to a larger range.