We find that ranked methods using force fields (OpenFF2.0.0, AMOEBA, and GAFF2) had better R 2 than did ML and dockingbased methods, and only the top two approaches had values greater than 0.50. Figure shows the R 2 for ranked methods with the highest coefficient of determination coming from EE/Openff-2.0/TIP3P/MD-EE/WL_RL.02_L.01 followed by DDM/AMOEBA/BAR and vDSSB/GAFF2/OPC3/HREM. The MACHINE-LEARNING/NNET/DRAGON-descriptors had the lowest R 2 value of 0.15. Ranking molecules by binding free en- ergy or affinity (from strongest to weakest) to identify and prioritize potential leads is also of great importance, perhaps more important than accuracy, since in a drug discovery setting free energy methods would likely be employed to help prioritize synthesis. In such a workflow, correct rank ordering can be more important than absolute accuracy. When only considering ranked methods for WP6, 3 out of 5 methods had t values greater than 0.50 and are all methods using a force field (Table ). The EE/Openff-2.0/TIP3P/MD-EE/WL_RL.02_L.01 and DDM/AMOEBA/BAR methods had the highest t values of 0.61 and 0.58, followed by 0.50 and 0.44 for methods using GAFF2 (ELIE/GAFF2-ABCG2/TIP3P/MD/MMPBSA and vDSSB/GAFF2/OPC3/HREM respectively), while MACHINE-LEARNING/NNET/DRAGON-descriptors had the lowest at 0.21. Predictions with methods using the AMOEBA force field have been among the most accurate (if not the most accurate) in SAMPL7 (OA, exoOA, and TrimerTrip), and SAMPL8 (TEMOA and TEETOA). These results have shown the importance of modeling explicit polarization for host-guest systems, particularly when the host or guest (or both) are highly polar or charged; such as host-guest systems present in SAMPL7-8. For WP6 in SAMPL9, AMOEBA had considerable success achieving among the highest correlation metrics (Figure ). In terms of accuracy, DDM/AMOEBA/BAR was not among the top 2 methods and did not have superior performance across all metrics, for a change. Perhaps this is because other issues were more accuracy-limiting for this particular set of compounds. In the past, torsion tuning of the host has led to improved agreement with experimental BFE measurements.