In the present paper, the advantages of GEO over GEO are used for a systematic analysis of geometric performance of approximations for main-group structures. By using GEO in place of GEO in tandem with accurate semiexperimental geometries, 15-17 the analysis does not rely on the expensive CCSD(T) calculations nor on a proxy reference as it was the case in the previous study. While the previous study focused on the GEO analysis at a fixed basis set, here we observe how the changes in a basis set affect the geometric performance of approximations. From this analysis, we find that some of the worst performers at a large basis sets are one of the top performers at a smaller basis due to error cancellations. We dedicate special attention to the geometric performance of different classes of DFT methods, and analyze how it varies with the amount of exact exchange. A harmonic approximation to GEO enables us to directly link and partition GEO into contributions from errors in specific geometric parameters. This analysis reveals different patterns for different classes of DFT approximations and tells us how these patterns change with a basis set size.