Determining relative population-specific acceleration intensity thresholds in soccer using game locomotion data
Methodological challenges and possible solutions
DOI:
https://doi.org/10.51224/SRXIV.415Keywords:
soccer, activity profile, acceleration thresholds, relative thresholds, population-specific thresholdsAbstract
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 present a new method for determining population-specific amax-vinit regression lines in soccer using game locomotion data and to assess its validity. Game locomotion data from 41 male youth elite soccer players were collected using a GPS-based tracking system. The amax-vinit regression lines were determined using locomotion data from one to five games per athlete. The proposed method overcomes several limitations of existing methods by accounting for the number of games combined and the individual distribution of high-intensity accelerations over the velocity measurement range when identifying maximal accelerations. Further, the athletes took an acceleration test to determine their test-based amax-vinit regression line. Mean biases were estimated for the regression coefficients (i.e., amax-intercept and slope) and assessed via standardization and Bayesian analysis. Regression lines based on 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. Thus, the presented 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.
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Copyright (c) 2024 Pascal Andrey, Karin Fischer-Sonderegger, Wolfgang Taube, Markus Tschopp (Author)
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