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采用百分比强度法评估足球运动中的加速和减速:超越绝对和任意阈值。

Adapting the percentage intensity method to assess accelerations and decelerations in football: moving beyond absolute and arbitrary thresholds.

作者信息

Silva Hugo, Nakamura Fábio Yuzo, Serpiello Fabio R, Ribeiro João, Roriz Paulo, Marcelino Rui

机构信息

Research Center in Sports Sciences, Health Sciences and Human Development, CIDESD, Creative Lab Research Community, Vila Real, Portugal.

Department of Physical Education and Sports Sciences, University of Maia, Maia, Portugal.

出版信息

Sports Biomech. 2024 Dec;23(12):3514-3525. doi: 10.1080/14763141.2024.2393188. Epub 2024 Aug 27.

Abstract

We adapted the percentage intensity approach to monitor accelerations and decelerations allowing players' individualisation. Forty-two players were monitored during four microcycles via global navigation satellite system devices. Raw velocity and time data were collected to calculate acceleration and deceleration magnitudes according to specific starting speed intervals, and the efforts intensities were established as very low (<25% of the maximal effort), low (25-50%), moderate (50-75%) and high (>75%). Linear regressions and Pearson correlation () analysed the relationship between maximal efforts and starting speeds; additionally, mean paired differences compared efforts magnitudes between subsequent starting speed intervals. Most very low intensity accelerations (86%) and decelerations (79%) started from <5 km.h. Correlation between maximal efforts and starting speeds were = -0.97 ( < .001) for acceleration, and = -0.94 ( < .01) for deceleration. Maximal acceleration decreased as starting speed increases (very large effect sizes), but deceleration is less starting speed dependent (unclear to large effect sizes). This adaptation allows practitioners to individualise accelerations and decelerations classification during real-life scenarios, leading to a more precise training prescription. The very low intensity interval could be excluded to consider only relevant efforts. Maximal acceleration should be collected for each starting speed interval because accelerations are starting speed dependents.

摘要

我们采用百分比强度法来监测加速度和减速度,以实现运动员的个性化。通过全球导航卫星系统设备,在四个微周期内对42名运动员进行了监测。收集原始速度和时间数据,根据特定的起始速度区间计算加速度和减速度大小,并将用力强度设定为极低(<最大用力的25%)、低(25%-50%)、中等(50%-75%)和高(>75%)。线性回归和皮尔逊相关性()分析了最大用力与起始速度之间的关系;此外,平均配对差异比较了后续起始速度区间之间的用力大小。大多数极低强度的加速度(86%)和减速度(79%)始于<5 km/h。加速度的最大用力与起始速度之间的相关性为 = -0.97(<0.001),减速度为 = -0.94(<0.01)。最大加速度随着起始速度的增加而降低(效应量非常大),但减速度对起始速度的依赖性较小(效应量不明确到较大)。这种调整使从业者能够在实际场景中对加速度和减速度分类进行个性化,从而制定更精确的训练处方。可以排除极低强度区间,只考虑相关用力。应针对每个起始速度区间收集最大加速度,因为加速度取决于起始速度。

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