The SAMPL (Statistical Assessment of the Modeling of Proteins and Ligands) blind challenges have been run since 2008 to test and improve computational methods, with the goal of innovating and advancing reliable predictive tools for drug design. SAMPL has served as a crowdsourcing platform for the computational community to test their methods on systems designed to focus on specific modeling challenges. Free energy techniques have been some of the most successful methods in the SAMPL challenges. As a result, SAMPL has raised awareness and understanding of some sources of error, and understanding of important molecular recognition events such as the importance of adequate sampling of water rearrangements. Several iterations of SAMPL have had a host-guest component examining the binding of small molecule "guests" to supramolecular "hosts", particularly macrocycles. Supramolecular chemistry has seen a substantial increase in popularity in recent years, particularly as hosts have industrial and medical applications through compound stabilization or enhancing solubility, drug delivery, and as sequestration agents. In addition, since hosts are typically much smaller and more rigid than biomolecules, they make reasonable surrogates to proteins to help test and improve computational methods for BFEs. Recent SAMPL host-guest challenges have demonstrated that some methods can predict binding free energies within 1 kcal/mol, but in some instances they continue to present some modeling difficulties. The lessons learned from SAMPL host-guest challenges can push improvement and innovation of computational methods, and eventually with protein-ligand systems which is another phase of the SAMPL series of challenges.