Beginning with work of Zeilberger on classical pattern counts, there are a variety of structural results for moments of permutation statistics applied to random permutations. Using tools from representation theory, Gaetz and Ryba generalized Zeilberger's results to uniformly random permutations of a given cycle type. We introduce regular statistics and characterize their moments for all cycle types, generalizing all results in this literature that we are aware of. Our approach splits into two steps: first characterize such statistics as linear combinations of indicator functions for partial permutations, then identifying the moments of such indicators. As an application, we show that many regular statistics exhibit a law of large numbers depending only on fixed point counts and a similar variance property that depends also on two--cycle counts. These results first appeared in arXiv:2206.06567, which is no longer intended for publication. Our original proof of the moment result for indicators of partial permutations relied on representation theory and symmetric functions. A referee generously shared a combinatorial argument, allowing us to give a self-contained treatment of these results that does not rely on representation theory.