To get a better sense of the efficiency gains of NCMC compared to standard MD we constructed statistical models from the data of the MSM and the NCMC simulations. For the MSM we took the estimated MSM transition matrix directly after clustering the 1.286 µs into four clusters corresponding to the four binding modes. For the NCMC simulation, we assigned each iteration to a particular macrostate using the dihedral order parameter as defined in Sec 2.7. We used those state assignments from those 5000 iterations to generate a transition matrix. To generate the synthetic data, we started from state A2 and iteratively applied the transition matrices to get trajectories of states. A new state could be the same as the previous, depending on the transition probabilities given by that particular transition matrix. This process was repeated, and the total state populations at each iteration were recorded. We performed 5000 propogation iterations for the MD and NCMC transition matrices with 1000 trials each. This allowed us to cheaply estimate uncertainties in the populations of each state at each time point by taking the standard deviation in the estimated population across all trials. Overall, this analysis facilitated an assessment of the rate of convergence of the populations.