Evidence map›Paper›PMID 42455824›Full record

ArticlePloS one2026

Reliability and validity of the individual GPS game data-based maximal acceleration-initial running speed regression line in youth elite soccer players.

Pascal Andrey, Karin Fischer-Sonderegger, Wolfgang Taube, Markus Tschopp

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Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Pascal AndreyDepartment of Elite Sport, Swiss Federal Institute of Sport Magglingen SFISM, Magglingen, Bern, Switzerland.ORCID https://orcid.org/0000-0002-0812-8899
Karin Fischer-SondereggerDepartment of Elite Sport, Swiss Federal Institute of Sport Magglingen SFISM, Magglingen, Bern, Switzerland.
Wolfgang TaubeDepartment of Neurosciences and Movement Science, University of Fribourg, Fribourg, Fribourg, Switzerland.
Markus TschoppDepartment of Elite Sport, Swiss Federal Institute of Sport Magglingen SFISM, Magglingen, Bern, Switzerland.ORCID https://orcid.org/0009-0007-3446-2907

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern load monitoring in soccer increasingly employs relative individualized acceleration intensity thresholds derived from individual maximal acceleration-initial running speed (amax-vinit) regression lines. This study examined the reliability and validity of soccer players' individual amax-vinit regression lines determined solely from game locomotion data. Using a GPS-based tracking system, we prospectively collected game locomotion data from 159 male youth elite soccer players over one season and repeatedly determined their amax-vinit regression lines using a recently introduced game data-based method. To examine the influence of data volume, regression lines were determined using different numbers of consecutive games. As a criterion measure, the amax-vinit regression line was determined using an acceleration test in 55 athletes. Reliability was assessed via the typical error (TE) and the intraclass correlation coefficient (ICC), and validity via the typical error of the estimate (TEE) and the Pearson correlation coefficient. The magnitude of errors and correlation coefficients was assessed using standardization and published thresholds, respectively. Reliability improved gradually with increasing data volume, resulting in TEs of 3.4% (amax intercept), 7.3% (vinit intercept), and 10.3% (slope). Nonetheless, all TEs were large in magnitude, and ICCs very low to low. Validity was unaffected by data volume, with TEEs consistently ~7% (amax intercept), ~ 12% (vinit intercept), and ~17% (slope). All TEEs were assessed as extremely large, and Pearson correlations as impractical. These findings indicate that the game data-based method currently lacks the precision required for individual-level applications, and this limitation cannot be resolved simply by including more games. Therefore, establishing relative individualized acceleration intensity thresholds within a team still requires a test-based approach. Moreover, the results suggest that properties inherent in GPS-based game locomotion data, rather than data volume, underlie the observed imprecision. We propose that substantial future improvements will depend on more precise tracking systems.

Indexed as

AccelerationAthletesAthletic PerformanceGeographic Information SystemsRunningSoccerAdolescentHumansMaleRegression AnalysisReproducibility of Results

Identifiers

PMID42455824
PMCPMC13372162

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.