Lifting velocity predicts the maximum number of repetitions to failure with comparable accuracy during the Smith machine and free-weight prone bench pull exercises Miras Moreno, Sergio Pérez Castilla, Alejandro Rojas Ruiz, Francisco Javier García Ramos, Amador Level of effort Fatigue Linear position transducer Strength training Velocity-based training This study compared the accuracy of the fastest mean velocity from set (MVfastest) to predict the maximum number of repetitions to failure (RTF) between 2 variants of prone bench pull (PBP) exercise (Smith machine and free-weight) and 3 methods (generalized, individualized multiplepoint, and individualized 2-point). Twenty-three resistance-trained males randomly performed 2 sessions during Smith machine PBP and 2 sessions during free-weight PBP in different weeks. The first weekly session determined the RTF-MVfastest relationships and subjects completed single sets of repetitions to failure against 60-70-80-90%1RM. The second weekly session explored the accuracy of RTFs prediction under fatigue conditions and subjects completed 2 sets of 65%1RM and 2 sets of 85%1RM with 2 min of rest. The MVfastest associated with RTFs from 1 to 15 were greater for Smith machine compared to free-weight PBP (F ≥ 42.9; P < 0.001) and for multiplepoint compared to 2-point method (F ≥ 4.6; P ≤ 0.043). The errors when predicting RTFs did not differ between methods and PBP variants, whereas all RTF-MVfastest relationships overestimated the RTF under fatigue conditions. These results suggest that RTF–MVfastest relationships present similar accuracy during Smith machine and free-weight PBP exercises and it should be constructed under similar training conditions. 2023-10-24T10:39:37Z 2023-10-24T10:39:37Z 2023-08-30 info:eu-repo/semantics/article S. Miras-Moreno et al. Lifting velocity predicts the maximum number of repetitions to failure with comparable accuracy during the Smith machine and free-weight prone bench pull exercises. Heliyon 9 (2023) e19628[https://doi.org/10.1016/j.heliyon.2023.e19628] https://hdl.handle.net/10481/85213 10.1016/j.heliyon.2023.e19628 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional Elsevier