In materials discovery workflows it is desirable to use models that are fast to evaluate for preliminary screening of a large number of candidates. Semi-local DFT has been used extensively for this purpose. However, such models must be sufficiently reliable to at least capture the correct trends. Here, we perform statistical analysis across our dataset to examine whether selected DFT models are sufficiently predictive of GW +BSE quantities. The PAH101 dataset may similarly serve as a resource for researchers interested in comparing the results of other DFT and TDDFT models to GW +BSE.