Scoring, the process of selecting the biologically relevant solution from a pool of generated conformations, is one of the major challenges in the field of biomolecular docking. A prominent way to cope with this challenge is to incorporate information-based terms into the scoring function. Within this context, low-resolution shape data obtained from either ion-mobility mass spectrometry (IM-MS) or SAXS experiments have been integrated into the conventional scoring function of the information-driven docking program HADDOCK. Here, the strengths and weaknesses of IM-MS-based and SAXS-based scoring, either in isolation or in combination with the HADDOCK score, are systematically assessed. The results of an analysis of a large docking decoy set composed of dimers generated by running HADDOCK in ab initio mode reveal that the content of the IM-MS data is of too low resolution for selecting correct models, while scoring with SAXS data leads to a significant improvement in performance. However, the effectiveness of SAXS scoring depends on the shape and the arrangement of the complex, with prolate and oblate systems showing the best performance. It is observed that the highest accuracy is achieved when SAXS scoring is combined with the energy-based HADDOCK score.