Andrey Pascal, Fischer-Sonderegger Karin, Taube Wolfgang, Tschopp Markus
Department of Elite Sport, Swiss Federal Institute of Sport Magglingen SFISM, Magglingen, Bern, Switzerland.
Department of Neurosciences and Movement Science, University of Fribourg, Fribourg, Switzerland.
PLoS One. 2025 May 9;20(5):e0321275. doi: 10.1371/journal.pone.0321275. eCollection 2025.
In soccer, relative population-specific acceleration intensity thresholds are required to create meaningful activity profiles. These thresholds can be derived from the maximal acceleration-initial running speed (amax-vinit) regression line, whose determination has so far required time-consuming testing. The aims of this study were to introduce a new method for determining population-specific amax-vinit regression lines in soccer using game locomotion data and to assess its validity as a function of the amount of data used. The method accounts for both the amount of data used and the distribution of high-intensity accelerations across the velocity measurement range when identifying maximal accelerations in game locomotion data. This is intended to minimize the risk of selecting submaximal accelerations or predominantly maximal accelerations with a positive random measurement error. Game locomotion data were collected from 55 male youth elite soccer players using a GPS-based tracking system. Multiple population-specific amax-vinit regression lines were determined using locomotion data from one to five games per athlete. Furthermore, each athlete completed an acceleration test to determine his test-based amax-vinit regression line. The mean biases for the regression coefficients (i.e., amax-intercept and slope) were estimated and assessed using standardization and Bayesian analysis. Regression lines based on locomotion data from two or three combined games showed trivial biases for both coefficients. However, due to the large uncertainty in the estimates, the chance of equivalence was only assessed as possibly equivalent. The proposed game-based method represents a viable and easy-to-implement alternative to the test-based method for determining population-specific amax-vinit regression lines in soccer. This simplifies the process of determining relative population-specific acceleration intensity thresholds, which are required for creating meaningful activity profiles.
在足球运动中,需要特定人群的相对加速度强度阈值来创建有意义的活动概况。这些阈值可以从最大加速度 - 初始跑步速度(amax - vinit)回归线得出,到目前为止,其确定需要耗时的测试。本研究的目的是引入一种新方法,用于使用比赛移动数据确定足球运动中特定人群的amax - vinit回归线,并评估其作为所用数据量的函数的有效性。该方法在识别比赛移动数据中的最大加速度时,既考虑了所用数据的量,也考虑了高强度加速度在速度测量范围内的分布。这旨在将选择次最大加速度或主要是具有正随机测量误差的最大加速度的风险降至最低。使用基于全球定位系统的跟踪系统从55名男性青年精英足球运动员收集比赛移动数据。使用每名运动员一到五场比赛的移动数据确定多条特定人群的amax - vinit回归线。此外,每名运动员完成一次加速度测试,以确定其基于测试的amax - vinit回归线。使用标准化和贝叶斯分析估计并评估回归系数(即amax截距和斜率)的平均偏差。基于两场或三场组合比赛的移动数据得出的回归线显示,两个系数的偏差都很小。然而,由于估计中的不确定性很大,等效性的可能性仅被评估为可能等效。所提出的基于比赛的方法是一种可行且易于实施的替代方法,可替代基于测试的方法来确定足球运动中特定人群的amax - vinit回归线。这简化了确定相对特定人群加速度强度阈值的过程,而这些阈值是创建有意义的活动概况所必需的。