Velocity Variables: Determining Predictive Metrics during the Back Squat and Bench Press to Failure at Different Relative Loads.

IF 3 2区 医学 Q2 SPORT SCIENCES
Daniel J Lawson, Alex A Olmos, Samuel J Mosiman, Stephanie A Sontag, Jacob R Goodin, J Jay Dawes
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引用次数: 0

Abstract

Abstract: Lawson, DJ, Olmos, AA, Mosiman, SJ, Sontag, SA, Goodin, JR, and Dawes, JJ. Velocity Variables: Determining Predictive Metrics during the Back Squat and Bench Press to Failure at Different Relative Loads. J Strength Cond Res XX(X): 000-000, 2025-This study aimed to determine a best velocity variable and prediction model for estimating repetitions to failure (RTF) across 3 relative loads (%1RM) comparing the average concentric velocity (ACV) of a single repetition set (ACVSingle), ACV from the first repetition (ACVFirst), ACV across all repetitions (ACVMean), and the fastest repetition velocity (FRV) achieved during the back squat and bench press exercises. Twenty-six (n = 26; males = 18, females = 8) resistance-trained individuals performed 3 sets to failure at 90, 80, and 70% of their 1RM on both exercises for 2 testing sessions. Repeated measures mixed effects models were constructed for univariate, adjusted (corrected for sex), and interaction (velocity*sex) models from Visit 2 data. Model selection criteria were determined by the smallest residual mean error (RME) and standard deviation (SD), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) serving as fit indicators. Best fit models were cross-validated by applying fixed-effects coefficients from Visit 2 to Visit 3 velocity variables, estimating RTF and calculating error as the predicted versus observed variable delta. The ACVSingle adjusted model demonstrated the best fit for the squat (RME = 0.0056, SD = 3.7731, AIC = 360.88, BIC = 363.24). The FRV interaction model demonstrated the best fit for the bench press (RME = 0.0303, SD = 2.4011, AIC = 300.71, and BIC = 303.07). Although no single predictor exhibited superiority across all intensities, ACVSingle and FRV provide lower prediction error variability under specific conditions, with the best predictor determined by both intensity and exercise.

速度变量:在不同的相对负荷下确定后蹲和卧推失败的预测指标。
摘要:Lawson, DJ, Olmos, AA, Mosiman, SJ, Sontag, SA, Goodin, JR, Dawes, JJ。速度变量:在不同的相对负荷下确定后蹲和卧推失败的预测指标。[J] Strength Cond Res XX(X): 000-000, 2025-本研究旨在确定一个最佳的速度变量和预测模型,用于估计三种相对负荷(%1RM)下的重复失败(RTF),比较单次重复(ACVSingle)的平均同心速度(ACV)、第一次重复(ACVFirst)的平均同心速度(ACV)、所有重复(ACVMean)的平均同心速度(ACV)以及在后蹲和卧推练习中达到的最快重复速度(FRV)。26名(n = 26;男性= 18,女性= 8)接受阻力训练的个体在两组测试中分别以90%、80%和70%的1RM进行三组训练,直到失败。对访问2数据中的单变量、调整(性别校正)和交互(速度*性别)模型构建重复测量混合效应模型。以最小残差平均误差(RME)和标准差(SD)确定模型选择标准,赤池信息准则(AIC)和贝叶斯信息准则(BIC)作为拟合指标。通过应用访问2至访问3速度变量的固定效应系数,估计RTF并计算预测与观测变量delta的误差,对最佳拟合模型进行交叉验证。ACVSingle调整模型最适合深蹲(RME = 0.0056, SD = 3.7731, AIC = 360.88, BIC = 363.24)。FRV交互作用模型最适合台式压力机(RME = 0.0303, SD = 2.4011, AIC = 300.71, BIC = 303.07)。虽然没有单一的预测器在所有强度下都表现出优势,但ACVSingle和FRV在特定条件下提供了较低的预测误差变异性,最佳预测器由强度和运动决定。
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来源期刊
CiteScore
6.70
自引率
9.40%
发文量
384
审稿时长
3 months
期刊介绍: The editorial mission of The Journal of Strength and Conditioning Research (JSCR) is to advance the knowledge about strength and conditioning through research. A unique aspect of this journal is that it includes recommendations for the practical use of research findings. While the journal name identifies strength and conditioning as separate entities, strength is considered a part of conditioning. This journal wishes to promote the publication of peer-reviewed manuscripts which add to our understanding of conditioning and sport through applied exercise science.
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