What is the difference between normalized peak of correlation, versus peak of correlation divided by its average?
To add some perspective, you could go back to the probabilistic interpretation of correlation.
Remember that the correlation is used because it measures the degree of similarity under some linear generative model of the signal knowing the template (additive gaussian noise). The autocorrelation gives a measure of the log-Probability.

To go back to your question, there are a number of free parameters, notably the variance of noise, and this relates to your choice of normalisation.