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

Coppus, TA, Anderson, T, Hurley, E, Gill, DL, and Brown, PK. The practical utility of objective training load indices in Division I college soccer players. J Strength Cond Res 36(4): 1026-1030, 2022-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 R 2 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. /p> [ABSTRACT FROM AUTHOR]