Chemists often use statistical analysis of reaction data with molecular descriptors to identify structure-reactivity relationships, which can enable prediction and mechanistic understanding. In this study, we developed a broadly applicable and quantitative classification workflow that identifies reactivity cliffs in 11 Ni- and Pd-catalyzed cross-coupling datasets using monodentate phosphine ligands. A distinctive ligand steric descriptor, minimum percent buried volume [%Vbur (min)], is found to divide these datasets into active and inactive regions at a similar threshold value. Organometallic studies demonstrate that this threshold corresponds to the binary outcome of bisligated versus monoligated metal and that %Vbur (min) is a physically meaningful and predictive representation of ligand structure in catalysis.