Chen Zongwei, Xiao Fengping, Mao Yaxu, Zhang Xiuli, García-Ramos Amador
School of Physical Education and Sports Science, South China Normal University, Guangzhou, China.
Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Granada, Spain.
J Strength Cond Res. 2025 Apr 1;39(4):e530-e537. doi: 10.1519/JSC.0000000000005040. Epub 2024 Dec 19.
Chen, Z, Xiao, F, Mao, Y, Zhang, X, and García-Ramos, A. An efficient and accurate approach for estimating the free-weight back squat 1-repetition maximum based on the 2-point method and optimal minimal velocity threshold. J Strength Cond Res 39(4): e530-e537, 2025-This study aimed to compare the accuracy of nine 1-repetition maximum (1RM) estimation methods based on velocity recordings during the free-weight back squat. In a counterbalanced order, 39 resistance-trained male subjects performed 2 sessions against 6 loads (∼40, 50, 60, 70, 80, and 90% of 1RM) and 2 sessions against only 2 loads (∼40 and 90% of 1RM) followed by the actual 1RM attempts. The first session of each procedure was used for obtaining minimal velocity thresholds (MVTs) and the second session was used for 1RM estimation. Predicted 1RMs were calculated by entering 3 MVTs (i.e., actual MVT [i.e., the MVT associated with the actual 1RM], general MVT [i.e., 0.30 m·second -1 ], and optimal MVT [i.e., the MVT that minimizes the differences between the actual and predicted 1RMs]) into 3 load-velocity relationship (LVR) regression equations (multiple-point [i.e., using data of 6 loads from the multiple-point test], extracted 2-point [i.e., using data of the lightest and heaviest loads from the multiple-point test], and 2-point [i.e., using data of 2 loads from the 2-point test]). Alpha was set at 0.05. The main findings revealed that only the 1RMs predicted by the optimal MVT showed acceptable accuracy (raw errors ≤0.8 kg, absolute errors ≤4.0%) compared with the actual 1RM. The analysis of variance failed to reveal a significant main effect of the "type of LVR model" ( p = 0.079). Therefore, we recommend using the 2-point method combined with the optimal MVT to obtain an efficient and accurate 1RM estimation during the free-weight back squat.
陈,Z,肖,F,毛,Y,张,X,以及加西亚 - 拉莫斯,A。一种基于两点法和最佳最小速度阈值估算自由重量深蹲1次最大重复量的高效准确方法。《力量与体能研究杂志》39(4): e530 - e537,2025年——本研究旨在比较基于自由重量深蹲过程中速度记录的九种1次最大重复量(1RM)估算方法的准确性。39名经过阻力训练的男性受试者以平衡顺序进行了2组针对6种负荷(约为1RM的40%、50%、60%、70%、80%和90%)的训练以及2组仅针对2种负荷(约为1RM的40%和90%)的训练,随后进行实际的1RM尝试。每个程序的第一组训练用于获取最小速度阈值(MVT),第二组训练用于1RM估算。通过将3个MVT(即实际MVT [即与实际1RM相关的MVT]、通用MVT [即0.30米·秒⁻¹]和最佳MVT [即使实际与预测1RM之间差异最小的MVT])代入3个负荷 - 速度关系(LVR)回归方程(多点法 [即使用多点测试中6种负荷的数据]、提取两点法 [即使用多点测试中最轻和最重负荷的数据]以及两点法 [即使用两点测试中2种负荷的数据])来计算预测的1RM。显著性水平设定为0.05。主要研究结果表明,与实际1RM相比,只有由最佳MVT预测的1RM显示出可接受的准确性(原始误差≤0.8千克,绝对误差≤4.0%)。方差分析未能揭示“LVR模型类型”的显著主效应(p = 0.079)。因此,我们建议在自由重量深蹲过程中使用两点法结合最佳MVT来获得高效准确的1RM估算。