Which below statement regarding overfitting is NOT correct?

Question $9$ options:

Overfitting happens when a model has too many parameters relevant to the amount of data.$$

A model that has been overfit usually has poor R$^2($coefficient of determination$)$ value to capture the proportion of variability in the data set that is used to build the model.

When overfitting happens, the model captures noise in the data rather than meaningful relationships.$$

A model that has been overfit usually has poor predictive power.$$