Docking is commonly used for initial screening to identify potential ligand candidates and leads, to then be assessed by more computationally expensive approaches to prioritize and advance ligands through the pipeline. In SAMPL, docking has rarely been used to predict binding strength, though docking is commonly used by some methods to obtain a starting pose of a complex. Recently, a systematic assessment examined how well docking scores can predict BFEs , using the Autodock4 and Vina docking programs. This retrospective study examined all host-guest systems from SAMPL6 to SAMPL8. In this study, docking (with Autodock4) outperformed most methods including expensive and complex MD-based or QM-based computational methods used in those SAMPL iterations. For SAMPL9, the same authors submitted predictions obtained using Vina, where binding scores were calculated using the smina code (from and the improved vinardo scoring function (method DOCKING/SMINA/VINARDO). Similar to the results in reference , when considering all methods including non-ranked, DOCKING/SMINA/VINARDO outperforms most methods in several of the calculated statistical metrics (see Table ). The RMSE and MAE (1.70 and 1.36 kcal/mol, respectively) for this approach was the best of all submissions, but had a poor R 2 of 0.14. At ranking WP6 systems, DOCK-ING/SMINA/VINARDO performed at about mid-tier among challenge submissions with a t of 0.33. The reported performance of scoring via docking across different host-guest system categories (from SAMPL6 through SAMPL9) suggests that docking may be suitable for supramolecular system studies and design, and indeed could potentially serve as a reference model in future SAMPL challenges.