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The prediction of one-repetition maximum (1RM) is highly relevant for strength and conditioning. The optimal minimum-velocity threshold (MVT) was recently proposed to increase the accuracy of 1RM predictions. Individual load-velocity profiles (LVP) were obtained in 18 athletes enrolled in recreational soccer. Reliability analyses were computed for all LVP-derived variables. Estimations of 1RM were made based on general (0.3 m.s− 1), pre-individual (mean velocity at 1RM obtained in a preliminary session) and optimal MVT (velocity that eliminates the difference between actual and predicted 1RM, determined in a preliminary session). The accuracy of 1RM predictions was examined using absolute-percent error and Bland-Altman plots. Between-day reliability of the LVP and 1RM was good (intraclass-correlation coefficients – ICCs>0.9 and coefficients of variation – CVs<5%). The individual and optimal MVT reached moderate-to-good reliability (ICCs>0.9 and CVs<10%, respectively). The predictions based on the optimal MVT displayed greater accuracy than those obtained with the individual and general MVT (absolute percent error: 2.8 vs. 5.5 vs. 4.9%, respectively). However, wide limits of agreement (LoA) were found between actual and estimated 1RM using this approach (~15 kg). Data indicate that the optimal MVT provides better estimations of 1RM for the free-weight back squat than the general and the individual MVT. [ABSTRACT FROM AUTHOR]

The prediction of one-repetition maximum (1RM) using the submaximal load–velocity relationship (LVR) is highly relevant for the field of strength and conditioning. The optimal minimum velocity threshold (MVT) was recently proposed to increase the accuracy of 1RM predictions. However, using the average optimal MVT would allow for more practical estimations. LVRs of the free-weight back squat were obtained in 53 participants, throughout 2 sessions. LVRs were obtained using the multi- and two-point methods. Estimations of 1RM were made based on the average actual MVT (1RM velocity) and the average optimal MVT. The accuracy of 1RM predictions was examined using absolute-percent error and Bland-Altman plots. Cross-validation was performed using a leave-one-out approach. The number of selected loads did not affect the slope, y-intercept, optimal MVT or the accuracy of 1RM predictions. Predictions based on the average optimal MVT displayed greater accuracy than those obtained with the average actual MVT (~6% vs. ~8% absolute-percent error, respectively). However, wide 95% limits of agreement (LoA) were found between actual and estimated 1RM using both approaches (~13%1RM). The average optimal MVT offers more accurate 1RM estimations than the average actual MVT. However, errors prove substantial, making it challenging to precisely track minor changes in 1RM. [ABSTRACT FROM AUTHOR]

We investigated whether a single session of absolute incremental loading is valid to obtain the individual load-velocity profile (LVP) and 1 repetition maximum (1RM) for the free-weight parallel back squat. Twenty strength-trained male subjects completed 3 testing sessions, including a baseline 1RM session and 2 LVP sessions (LVPrel based on incremental relative loads and LVPabs based on absolute load increments until 1RM). The 1RM load was compared between the baseline and LVPabs. The load at zero velocity (load-axis intercept [L0]), maximal velocity capacity (velocity-axis intercept [V0]), slope, and area under the load-velocity relationship line (Aline) were compared between the LVPrel and LVPabs using equivalence testing through 2 one-sided t-tests. Measurement accuracy was calculated using the absolute percent error. The 1RM measured at baseline and LVPabs was equivalent and presented a low absolute percent error (1.2%). The following LVP parameters were equivalent between LVPrel and LVPabs: 1RM, L0, and Aline because the mean difference between sessions was close to zero and the Bland-Altman limits of agreement (1RM:5.3 kg; L0:6.8 kg; Aline: 9.5 kg⋅m-1⋅s-1) were contained within the a priori defined ± equivalent margins (5% for 1RM and L0 and 10% for Aline). The aforementioned variables presented a low absolute percent error. However, slope and V0 were not equivalent between sessions. In conclusion, a single session of absolute incremental loading is a valid approach to obtain the L0 and Aline of the individual LVP and 1RM, and can be used to efficiently track the magnitude of neuromuscular adaptations throughout the training cycles for the free-weight back squat. [ABSTRACT FROM AUTHOR]

Fitas, A, Santos, P, Gomes, M, Pezarat-Correia, P, Schoenfeld, BJ, and Mendonca, GV. Prediction of one repetition maximum in free-weight back squat using a mixed approach: the combination of the individual load-velocity profile and generalized equations. J Strength Cond Res 38(2): 228-235, 2024--We aimed to develop a mixed methods approach for 1 repetition maximum (1RM) prediction based on the development of generalized equations and the individual load-velocity profile (LVP), and to explore the validity of such equations for 1RM prediction. Fifty-seven young men volunteered to participate. The submaximal load-velocity relationship was obtained for the free-weight parallel back squat. The estimated load at 0 velocity (LD0) was used as a single predictor, and in combination with the slope of the individual LVP, to develop equations predictive of 1RM. Prediction accuracy was determined through the mean absolute percent error and Bland-Altman plots. LD0 was predictive of 1RM (p, 0.0001), explaining 70.2% of its variance. Adding the slope of the LVP to the model increased the prediction power of 1RM to 84.4% (p, 0.0001). The absolute percent error between actual and predicted 1RM was lower for the predictions combining LD0 and slope (6.9 vs. 9.6%). The mean difference between actual and estimated 1RM was nearly zero and showed heteroscedasticity for the LD0 model, but not for the combined model. The limits of agreement error were of 31.9 and 23.5 kg for LD0 and LD0 combined with slope, respectively. In conclusion, the slope of the individual LVP adds predictive value to LD0 in 1RM estimation on a group level and avoids error trends in the estimation of 1RM over the entire spectrum of muscle strength. However, the use of mixed methods does not reach acceptable accuracy for 1RM prediction of the free-weight back squat on an individual basis. [ABSTRACT FROM AUTHOR]