###### Abstract  
This study explored the goodness-of-fit and the effect of fatigue on the precision of both generalized and individualized relationships between the velocity loss (%VL) magnitude and the percentage of completed repetitions with respect to the maximal that can be performed to failure (%Rep) in the Smith machine parallel back-squat exercise. Twenty-nine resistance-trained males completed four sets to failure, with a rest period of 2 min, against 75% of the one-repetition maximum. Generalized and individualized %Rep-%VL equations determined in the first set were used to estimate %Rep when a 20%VL was achieved during the three successive sets. Individualized %Rep-%VL relationships (R\({}^{2}\) = 0.84-0.99) showed a greater goodness-of-fit than the generalized %Rep-%VL relationship (R\({}^{2}\) = 0.82). However, the accuracy in the %Rep estimation was always low (absolute errors \(>\) 10%) and comparable for both regression models (\(p\) = 0.795). %Rep was progressively overestimated when increasing the number of sets using the MV\({}_{\text{fastest}}\) of the first set (from 15% to 45%), but no meaningful overestimations were observed using the MV\({}_{\text{fastest}}\) of each set (-2%). In conclusion, neither the generalized nor the individual %Rep-%VL equations provide accurate estimations of %Rep during the parallel back-squat exercise executed under fatigue. fatigue; level of exertion; neuromuscular fatigue; resistance training velocity-based training 2020  
by guiding each individual to execute a predetermined number of repetitions per exercise set [4]. Yet, extensive research has shown that this method is flawed due to significant differences among individuals in the maximum repetitions they can perform to failure at a specific relative load [5; 6]. This suggests that when individuals lift the same relative load completing the same number of repetitions, their exertion levels may vary (i.e., the number of repetitions they could still perform may differ). Given that the neural and morphological changes resulting from RT are greatly influenced by the volume of training [7; 8], it is crucial to explore more precise ways of prescribing repetition volume during RT. Currently, strength and conditioning experts can instantly receive feedback on the velocity of each repetition during RT [9; 10]. It is widely recognized that, when repetitions are carried out with maximum concentric effort, there is a gradual reduction in barbell velocity as fatigue sets in [11; 12]. Earlier research has shown that (i) the reduction in velocity during RT (i.e., the percentage of velocity decline between the fastest and last repetition of the set; %VL) correlates strongly with both mechanical (e.g., decrease in jump height) and metabolic (e.g., increase in blood lactate levels) indicators of fatigue [13; 14]; and (ii) there is a robust association between %VL and the percentage of performed repetitions relative to the maximum number that can be achieved until failure (%Rep) across different loads [5; 6]. Drawing on this evidence, numerous researchers have suggested that %VL could provide a more objective measure of exertion in a set compared to traditional methods of RT prescription [5; 13]. In particular, employing %VL might promote a more uniform exertion level among individuals due to the minimal variability in %Rep at different levels of %VL [5; 6]. Nonetheless, it remains unclear whether to use generalized or individualized %Rep-%VL correlations for more precise repetition prescriptions. In this context, a superior accuracy has been observed using individualized %Rep-%VL relationships over generalized ones in the bench press performed in a Smith machine [15]. However, considering the dependency of %Rep-%VL relationships on the specific exercise [6], further investigation is necessary to determine if individualized %Rep-%VL relationships could also enhance accuracy in other RT exercises.