We cross-compared methods employing different force fields to assess how much the force field and/or method impacted computed binding free energies. In particular, the RMS difference between free energies calculated with different reference BFE calculation protocols with the APR method provides evidence that force-field selection, may dictate the level of success for ABFEs for certain systems. As described earlier in section 2.4, these methods differed only in the force-field used to parameterize the hostguest complex. With the APR approach, different force fields led to different calculated binding free energies for the WP6 dataset (Figure ). Using GAFF2 with the APR approach to predict affinity of WP6 complexes resulted in greater error compared to OpenFF 1.2.0 and OpenFF 2.0.0, with RMS differences of 5.38 (GAFF2 versus OpenFF 1.2.0) and 4.19 kcal/mol (GAFF2 versus OpenFF 2.0.0), respectively. In comparison, the different iterations of OpenFF (OpenFF 1.2.0 and OpenFF 2.0.0) with the APR approach gave a lower RMS difference of 1.62 kcal/mol. In contrast, force field differences did not result in as disparate predictions for the bCD/HbCD dataset with the APR approach. Using GAFF2 with the APR approach compared to OpenFF 1.2.0 and OpenFF 2.0.0 had RMS differences of 1.22 (GAFF2 versus OpenFF 1.2.0) and 1.43 kcal/mol (GAFF2 versus OpenFF 2.0.0), while the RMS difference between the OpenFF versions was 0.52 kcal/mol. On the other hand, using GAFF2 with a different method (i.e ELIE/GAFF2-ABCG2/TIP3P/MD/MMPBSA) achieved better performance compared to APR, and we also observed that the use of OpenFF2.0.0 with a different method (i.e EE/Openff-2.0/TIP3P/MD-EE/All_data had better statistical performance. In the case of the latter, however, we speculate the discrepancy may be due to 3 systems in particular (WP6-G1, WP6-G5, and WP6-G8) that were consistent outliers between the two approaches (discussed in section 3.3).