School of Sport, Exercise & Rehabilitation, Faculty of Health, University of Technology Sydney, Sydney, Australia.
Connacht Rugby, Galway, Co., Galway, Ireland.
J Strength Cond Res. 2023 Jul 1;37(7):1463-1469. doi: 10.1519/JSC.0000000000004393. Epub 2022 Nov 30.
Howarth, DJ, McLean, BD, Cohen, DD, and Coutts, AJ. Sensitivity of countermovement jump variables in professional rugby union players within a playing season. J Strength Cond Res 37(7): 1463-1469, 2023-The aim of this study was to explore the measurement sensitivity of a wide range of countermovement jump (CMJ) variables to a full European professional rugby union season. A secondary purpose was to compare 3 different data treatment methods for the calculation of CMJ variables. Twenty-nine professional rugby union players (mean ± SD; age 24 ± 4 years, height 183.7 ± 8.0 cm, body mass 101.6 ± 10.7 kg) completed a minimum of 12 CMJ testing sessions on Thursdays-a day preceded by a rest day and a minimum of 96 hours after a match-throughout a season. Measurement sensitivity, quantified by signal-to-noise ratio (SNR), was determined for 74 CMJ variables and was calculated by dividing the signal, (week-to-week variation expressed as a coefficient of variation [CV%]) by the noise (interday test/retest reliability expressed as CV%). We also identified variables which had no overlap between the 95% confidence intervals (CIs) for the signal and the noise. The 3 data treatment methods for comparison were (a) mean output across 3 jump trials (Mean3), (b) single output from the trial with the highest jump (BestJH), and (c) the trial with the highest flight time to contraction time ratio (BestFTCT). Most variables had an SNR >1.0 (Mean3 = 60/74; BestFTCT = 59/74; BestJH = 48/74). Fewer variables displayed a nonoverlap of 95% CIs (Mean3 = 23/60; BestFTCT = 22/59; BestJH = 16/48). Most CMJ variables during a professional rugby season demonstrated a signal that exceeded measured noise (SNR > 1.0) and that using the Mean3 or BestFTCT data treatment methods yields a greater number of variables considered sensitive within a season (i.e., SNR > 1.0) than when using BestJH. We also recommend the calculation of the 95% CIs for both signal and noise, with nonoverlap indicative of a greater probability that the responsiveness of the variable at team level (i.e., SNR) also applies at the individual level. As sensitivity analysis is cohort and environment specific, practitioners should conduct a sensitivity analysis using internal signal and noise data to inform their own monitoring protocols.
Howarth、DJ、McLean、BD、Cohen、DD 和 Coutts、AJ。职业橄榄球联盟运动员在整个赛季中进行反跳测试时，各种反跳变量的敏感性。《力量与调节研究杂志》37（7）：1463-1469，2023-本研究旨在探讨广泛的反跳（CMJ）变量在整个欧洲职业橄榄球联盟赛季中的测量敏感性。次要目的是比较 3 种不同的数据处理方法计算 CMJ 变量的差异。29 名职业橄榄球联盟运动员（平均±标准差；年龄 24±4 岁，身高 183.7±8.0cm，体重 101.6±10.7kg）在整个赛季中，每周四至少进行 12 次 CMJ 测试（周四之前休息一天，至少在比赛后 96 小时）。通过信噪比（SNR）来确定 74 个 CMJ 变量的测量敏感性，信噪比是通过将信号（表示为变异系数 [CV%] 的每周变化）除以噪声（表示为日内测试/重测可靠性的 CV%）来计算的。我们还确定了信号和噪声 95%置信区间（CI）之间没有重叠的变量。比较的 3 种数据处理方法是（a）3 次跳跃试验的平均值（Mean3），（b）最高跳跃试验的单个输出（BestJH），（c）最高飞行时间与收缩时间比的试验（BestFTCT）。大多数变量的 SNR >1.0（Mean3=60/74；BestFTCT=59/74；BestJH=48/74）。显示信号和噪声 95%CI 无重叠的变量较少（Mean3=23/60；BestFTCT=22/59；BestJH=16/48）。职业橄榄球队赛季中的大多数 CMJ 变量表现出信号超过测量噪声（SNR>1.0），并且使用 Mean3 或 BestFTCT 数据处理方法比使用 BestJH 方法产生更多被认为在赛季内敏感的变量（即 SNR>1.0）。我们还建议为信号和噪声计算 95%CI，信号和噪声之间没有重叠表明该变量在团队层面上的反应性（即 SNR）也适用于个体层面的可能性更大。由于敏感性分析具有队列和环境特异性，因此从业者应使用内部信号和噪声数据进行敏感性分析，以告知自己的监测协议。
