The aim of this study was to assess the sensitivity of accelerometer-derived metrics for monitoring fatigue during an intermittent exercise protocol. Fifteen university students were enrolled in the study (age 20 ± 1 years). A submaximal intermitted recovery test (Sub-IRT) with a duration of 6 min and 30 s (drill 1) was performed. In order to increase the participants' fatigue, after that, a repeated sprint protocol (1×6 maximal 20 m sprints) was performed. Following that, participants repeated the Sub-IRT (drill 2) to evaluate the external and internal training load (TL) variations related to fatigue. Apex 10 Hz global navigation satellite system (GNSS) units were used to collect the variables total distance (TD), high metabolic distance (HMD), relative velocity (RV), average metabolic power (MP), heart rate maximal (HRmax) and mean (HRmean), muscular (RPEmus) and respiratory rating of perceived exertion (RPEres), dynamic stress load (DSL), and fatigue index (FI). A Bayesian statistical approach was used. A likelihood difference (between drill 1 and drill 2) was found for the following parameters: TD (BF₁₀ = 0.33, moderate per H₀ ), HMD (BF₁₀ = 1.3, anecdotal), RV (BF₁₀ = 0.29, moderate per H₀ ), MP (BF₁₀ = 1.3, anecdotal), accelerations (BF₁₀ = 1.6, anecdotal ), FI (BF₁₀ = 4.7, moderate), HRmax (BF₁₀ = 2.2, anecdotal), HRmean (BF₁₀ = 4.3, moderate), RPEmus (BF₁₀ = 11.6, strong), RPEres (BF₁₀ = 3.1, moderate), DSL (BF₁₀ = 5.7, moderate), and DSL•m^-1 (BF₁₀ = 4.3, moderate). In conclusion, this study reports that DSL, DSL•m^-1, and FI can be valid metrics to monitor fatigue related to movement strategy during a standardized submaximal intermittent exercise protocol.

Benjamin Carty

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