Miras-Moreno Sergio, Pérez-Castilla Alejandro, Weakley Jonathon, Rojas-Ruiz Francisco J, García-Ramos Amador
Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Granada, Spain.
Department of Education, Faculty of Education Sciences, University of Almería, Almería, Spain.
Int J Sports Physiol Perform. 2025 Jan 21;20(3):335-344. doi: 10.1123/ijspp.2024-0337. Print 2025 Mar 1.
A recent advancement in velocity-based training involves estimating the maximum number of repetitions to failure (RTF) by analyzing the fastest velocity recorded within a set. A systematic review examining the fundamental characteristics of the RTF-velocity relationship is still lacking.
This study aimed to (1) determine the basic properties of the RTF-velocity relationships (goodness of fit, reliability, and accuracy) and (2) offer guidance on implementing various methodological factors that can impact the RTF accuracy prediction.
Data were sourced from 3 databases: PubMed, SPORTDiscus, and Scopus. Studies were qualified for inclusion if they involved at least 2 sets performed to failure with different loads, utilized multijoint weight-lifting exercises, and monitored the RTF and fastest velocity for each set.
Six studies demonstrated (1) robust goodness of fit, (2) acceptable to high between-sessions reliability for the velocities associated to each RTF (1-15 RTF), and (3) acceptable RTF prediction accuracy during fatigue-free sessions (long interset rest), but, when fatigued (ie, short interset rest) the accuracy was compromised except for athletes with high training experience (eg, >2 y training-to-failure experience).
The relationship properties remain unaffected regardless of the exercise (upper- vs lower-body), equipment (Smith- vs free-weight), velocity variable (mean and peak velocity), and resting time (from 5 to 10 min). However, the modeling procedure used (multiple- vs 2-point) did alter the accuracy. The individualized RTF-velocity relationships can be constructed through a linear regression model, but the failure experience seems to be a critical factor to increase its accuracy.
基于速度的训练的一项最新进展是通过分析一组动作中记录的最快速度来估计至疲劳重复次数(RTF)。目前仍缺乏一项系统评价来研究RTF与速度关系的基本特征。
本研究旨在(1)确定RTF与速度关系的基本特性(拟合优度、可靠性和准确性),以及(2)为实施可能影响RTF准确性预测的各种方法因素提供指导。
数据来源于3个数据库:PubMed、SPORTDiscus和Scopus。纳入的研究需满足以下条件:至少进行2组不同负荷至疲劳的动作,采用多关节举重练习,并监测每组动作的RTF和最快速度。
六项研究表明:(1)拟合优度良好;(2)与每个RTF(1 - 15次RTF)相关的速度在不同训练时段之间的可靠性为可接受至高;(3)在无疲劳训练时段(组间休息时间长),RTF预测准确性可接受,但在疲劳状态下(即组间休息时间短),除训练经验丰富的运动员(如>2年至疲劳训练经验)外,准确性会受到影响。
无论运动类型(上身与下身)、设备(史密斯机与自由重量器械)、速度变量(平均速度和峰值速度)以及休息时间(5至10分钟)如何,关系特性均不受影响。然而,所使用的建模程序(多点与两点)确实会改变准确性。个性化的RTF与速度关系可以通过线性回归模型构建,但失败经验似乎是提高其准确性的关键因素。