The Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges tackle modeling areas in need of improvement, focusing the community on one accuracy-limiting problem at a time. In SAMPL challenges, participants predict a target property such as solvation free energy, given a target set of molecules. Then the corresponding experimental data remains inaccessible to the public until the challenge officially closes. By focusing on specific areas in need of improvement, SAMPL helps drive progress in computational modeling.