Compare the kernel density estimates of two histograms

Question

I want to compare model results to the actual data distributionally, e.g., say there is an 80% overlap between the two distributions. I could use earth movers distance on the histograms, but then the bin size would be arbitrary.

I'm using the following code to plot the two distributions visually using kernel density estimates. Is there a different way that lets me calculate the similarity of the two distributions?

sns.distplot(actual,hist = False, kde = True,color='tab:blue', kde_kws = {'shade': True, 'linewidth': 2.5}, label ="Actual")
sns.distplot(model, hist = False, kde = True,color='tab:orange', kde_kws = {'shade': True, 'linewidth': 2.5}, label ="Model")