When introduced to never before seen datapoints, an overfitted model will perform very poorly, despite reporting high accuracy during its training. If this trend can be observed, it's safe to assume overfitting has taken place.
It's highly dependent on the structure, but it's generally seen as prudent to have a linear relationship between the number of datapoints and degrees of freedom.
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