In summary, we have investigated the influence of different analysis choices on the results of ensemble MMPBSA based free energy calculations. The basis of our tests are two datasets which cover common computational chemistry challenges -one which is based on a set of related ligands and the other a highly diverse set of ligands with differing binding modes. In order to obtain successful rankings across the two datasets we found it necessary to incorporate receptor and ligand strains. Using the 2traj-ar ESMACS protocol we obtained Spearman correlations of between 0.60 [CI: 0.46-0.91] and 0.66 [CI: 0.50-0.94] for two different starting structures despite differences in charge and scaffold in the ligands. The lower confidence bounds of both these estimates are comparable to the average correlation coefficient from the 1traj protocol 0.46 [CI: 0.16-0.84], suggesting the results is statistically significant despite the relatively modest size of the dataset (which contains a total of 27 ligands). It should be noted that increase in computational cost is minimal here as the only additional simulations required are of the ligand (which are much smaller than either complex or receptor) with the receptor energy replaced by a constant. Hence, for prospective day to day applications, we recommend accounting for both ligand and receptor strain through independent ligand simulations and either further simulation of the apo receptor (as in the 3 traj ESMACS protocol) or the use of an average value for the receptor energies (2traj-ar).