Can the velocity profile in the bench press and the bench pull sufficiently estimate the one repetition maximum in youth elite cross-country ski and biathlon athletes?

卧推和卧拉的速度曲线能否充分估计青少年精英越野滑雪和冬季两项运动员的单次最大重复重量?

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Abstract

INTRODUCTION: In recent years, load-velocity profiles (LVP) have been frequently proposed as a highly reliable and valid alternative to the one-repetition maximum (1RM) for estimating maximal strength and prescribing training loads. However, previous authors commonly report intraclass correlation coefficients (ICC) while neglecting to calculate the measurement error associated with these values. This is important for practitioners, especially in an elite sports setting, to be able to differentiate between small but significant changes in performance and the error rate. METHODS: 49 youth elite athletes (17.71±2.07 years) were recruited and performed a 1RM test followed by a load-velocity profiling test using 30%, 50% and 70% of the 1RM in the bench press and bench pull, respectively. Reliability analysis, ICCs and the coefficient of variability, were calculated and supplemented by an agreement analysis including the mean absolute error (MAE) and mean absolute percentage error (MAPE) to provide the resulting measurement error. Furthermore, validity analyses between the measured 1RM and different calculation models to estimate 1RM were performed. RESULTS: Reliability values were in accordance with current literature (ICC = 0.79-0.99, coefficient of variance [CV] = 1.86-9.32%), however, were accompanied by a random error (mean absolute error [MAE]: 0.05-0.64 m/s, mean absolute percentage error [MAPE]: 2.7-9.5%) arising from test-retest measurement. Strength estimation via the velocity-profile overestimated the bench pull 1RM (limits of agreement [LOA]: -9.73 - -16.72 kg, MAE: 9.80-17.03 kg, MAPE 16.9-29.7%), while the bench press 1RM was underestimated (LOA: 3.34-6.37 kg, MAE: 3.74-7.84 kg, MAPE: 7.5-13.4%); dependent on used calculation model. DISCUSSION: Considering the observed measurement error associated with LVP-based methods, it can be posited that their utility as a programming strategy is limited. The lack of accuracy required to discriminate between small but significant changes in performance and error, coupled with the potential risks of under- and overestimating 1RM, can result in insufficient stimulus or increased injury risk, respectively. This further diminishes the practicality of these methods, particularly in elite sports settings.

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