Accuracy or error statistics such as RMSE (root mean-squared error), ME (mean error), and MAE (mean absolute error), provide a measure of how well a computational method agrees with experimental results. Correlation statistics such as R 2 (coefficient of determination) and t (Kendall Tau correlation coefficient) provide information on how well a computational method ordered guests and ranked them best to worst, relative to experiment. The SAMPL9 host-guest challenge statistical analysis was carried out using Python scripts adapted from previous SAMPL iterations and we used the same error and correlation metrics that include RMSE, R 2 , m (linear regression slope), t, ME, and MAE. The uncertainty in the metrics was determined by using bootstrapping with replacement as described in literature. To identify and compare the predictive accuracy of methods towards individual host-guest systems, the RMSE, MAE, and ME of each were computed while considering all methods.