The Practical Utility of Objective Training Load Indices in Division I College Soccer Players

• Troy A. Coppus ^[1] ; Travis Anderson ^[3] ; Eoin Hurley ^[2] ; Diane L. Gill ^[3] ; Pamela K. Brown ^[3]
  1. [1] Troy University

     Troy University

     Estados Unidos

     
  2. [2] University of Evansville

     University of Evansville

     Township of Pigeon, Estados Unidos

     
  3. [3] Department of Kinesiology, University of North Carolina Greensboro, Greensboro, North Carolina

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• Localización: Journal of strength and conditioning research: the research journal of the NSCA, ISSN 1064-8011, Vol. 36, Nº. 4, 2022, págs. 1026-1030
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • The aim of this study was to investigate the association of subjective session rating of perceived exertion with objective training load measures and explored data reduction approaches for 26 commonly measured objective load metrics. One National Collegiate Athletic Association Division I male soccer team (N = 28) provided 26 objective measures via a global positioning system and heart rate monitor system and self-report rating of perceived exertion measures for all team activities through the 12-week 2019 fall championship season. The singular associations between session rating of perceived exertion (sRPE) and objective load metrics were assessed via repeated-measures correlation and collectively assessed via elastic net regression. Principal components analysis was then used to reduce the dimensionality of objective load variables. Level of significance for the study was [alpha] <= 0.05. The training load variable had the highest correlation with sRPE (r = 0.85) among the 26 metrics. Twenty variables were retained in the elastic-net regression and demonstrated an R2 of 0.76. The principal components analysis demonstrated a 4-component solution. The components were qualitatively described as "moderate- or high-intensity external load," "low-intensity load," "high-intensity internal load," and "average internal load" and accounted for 46, 32, 16, and 6% of the variance, respectively. The sRPE metric had strong correlations with multiple objective measures, demonstrating its utility for practitioners monitoring training load in collegiate soccer with limited resources. Furthermore, the consolidation of 26 metrics into 4 components while retaining data variability allows coaches to focus on a small number of metrics and employ a data-driven approach to training.