From the perspective of 2D chemical descriptors, error in docking activity predictions is separated into noise and systematic components. This error framework explains how fitting docking scores to a 2D-QSAR equation often improves accuracy as well as its logical limits. Intriguingly, in examined cases where multiple docking models (e.g., multiple crystal structures or multiple scoring functions) are available for an enzyme, the noise component of error dominates the difference between the more accurate and less accurate docking models. When this is true, the QSAR equation fit statistics can rank each docking-score set's accuracy in the absence of experimental activity data.