The previous discussion on the non-normality of ABFE distributions using an ensemble size of 100 for a subset of systems provides categorical evidence that predicting ABFEs from one-off simulations is highly unreliable. We extend that analysis here by using the entire dataset of 219 protein-ligand complexes for which we have used an ensemble size of 10. Table includes the variation of MUE, RMSE, Pearson's r and Spearman's ρ across replicas for the EQ approach. In other words, it includes those values obtained for the full dataset of 219 complexes on using only a single replica (denoted by "Replica ID") out of the ensemble of 10 for each complex. This gives ten different MUEs, RMSEs, r and ρ values for the full dataset ranging between 1.16-1.38 kcal/mol, 1.54-1.81 kcal/mol, 0.61-0.70 and 0.63-0.71, respectively. The table also includes values of all these statistical measures when ABFEs are obtained using ensemble sizes 3, 5, 8 and 10 (denoted as "ES3-10") for both approaches. In case of the NEQ approach, the results were obtained using 50 transitions per replica in each direction. Using the EQ approach, MUE, RMSE, r and ρ using ES3 are 1.09(0.07) kcal/mol, 1.46(0.08) kcal/mol, 0.72(0.03) and 0.71(0.04), respectively, which are all better than the corresponding best values using any single replica. Increasing the ensemble size from 3 to 10 leads to a steady improvement in these metrics with ES10 yielding corresponding values of 0.93(0.05) kcal/mol, 1.22(0.06) kcal/mol, 0.77(0.03) and 0.76(0.04), respectively. The same is true for the NEQ approach as well, with MUE, RMSE, r, ρ values improving from 1.39(0.08) kcal/mol, 1.80(0.09) kcal/mol, 0.63(0.04), 0.61(0.05) for ES3 to 1.15(0.07) kcal/mol, 1.52(0.09) kcal/mol, 0.70(0.04), 0.68(0.04) for ES10 respectively. This further indicates that the ensemble based approach makes results more reliable irrespective of the method used.