Article Text
Abstract
Background Proper load monitoring can help to determine if athletes are adjusting properly to training loads, minimizing the risk of developing illnesses and injuries.
Objective The main objective of this study was to find relationships between internal and external load variables, and fatigue to enable a better understanding of specific adaptations.
Design An 8-week prospective observational cohort study with 213 observations.
Setting U Sports Canadian volleyball athletes.
Patients (or Participants) Six female volleyball athletes (21±2 years, 179.8±6.1 cm, 72±9.5 kg) with competitive experience of at least three years and able to participate without any physical limitation.
Interventions (or Assessment of Risk Factors) Pre-practice heart rate variability (HRV), energy level, level of soreness, and hours of sleep were recorded before every practice. The number of jumps, the activity minutes, post-practice rating of perceived exertion (RPE), and HRV value the morning after were also collected. Day of the week, previous strength and conditioning practice, quality of sleep, and medical/physio attention were additional factors included in the analyses.
Main Outcome Measurements Fatigue expressed as the percentage of jump-loss (10%) was the dependent binary variable. A stepwise logistic regression analysis was used to analyze the relationship between fatigue, covariates, and factors.
Results Previous soreness and the number of jumps performed in practice or competition were the only factors found to be related to a significant level of fatigue experienced by the athletes (p<0.001).
Conclusions Although monitoring processes in team sports are today frequent, not all the load markers seem to have the same importance explaining the level of fatigue experienced by the athletes. Pre-practice level of muscle soreness and the number of jumps performed during the activity, a specific expression of external load in volleyball, reveal as the key elements to be controlled by coaches and practitioners to promote an optimal load adaptation.