I'm quite confident in predicting that generic models are much more likely to be overfitted than to have too few degrees of freedom.

It's easy to regularize estimation in a model class that's too rich for your data. You can't "unregularize" a model class that's restrictive enough not to contain an adequate approximation to the truth of what you're modeling.