Given that accuracy of ranking host-guest complexes was low in SAMPL9, we surveyed the capability of a method (ranked or non-ranked) to predict the strongest and weakest binder correctly. For WP6, 5 Overall, we find that both docking and ML-based methods do particularly well in terms of error statistics on WP6 host-guest binding, but have relatively lower correlation statistics than force field based methods. This may be because the larger degree of empirical training (to binding data) in ML and docking methods results in predictions which tend to be near the center of the true range of affinities, resulting in good error statistics, but at the expense of correlation with experimental values. (As a thought experiment, consider a simple null model which predicted that all binding free energies were equal but had the correct mean; such a model could achieve relatively low error but the correlation would be zero.)