In reaction discovery, the search space of discrete reaction parameters such as catalyst structure is often not explored systematical-ly. We have developed a tool set to aid the search of optimal catalysts in the context of phosphine ligands. A virtual library, kra-ken, that is representative of the monodentate P(III)-ligand chemical space was utilized as the basis to represent the discrete lig-ands as continuous variables. Using dimensionality reduction and clustering techniques, we suggested a Phosphine Optimization Screening Set (PHOSS) of 32 commercially available ligands that samples this chemical space completely and evenly. We present the application of this screening set in the identification of active catalyst for various cross-coupling reactions and how well-distributed sampling of the chemical space facilitates identification of active catalysts. Furthermore, we demonstrate how proximi-ty in ligand space can be a useful guide to further explore ligands when very few active catalysts are known.