Abstract
Purpose: The aim of this study was to investigate the interaction of training load quantification using heart rate (HR) and rating of perceived exertion (RPE)-based methodology, and the relationship between internal training load parameters and subjective training status (Fatigue) in high-level rowers during volume increased low-intensity training period.Methods: Training data from 19 high-level rowers (age 23.5 ± 5.9 years; maximal oxygen uptake 58.9 ± 5.8 ml·min−1·kg−1) were collected during a 4-week volume increased training period. All individual training sessions were analyzed to quantify training intensity distribution based on the HR time-in-zone method (i.e., HR Z1, HR Z2, and HR Z3) determined by the first and second ventilatory thresholds (VT1/VT2). Internal training load was calculated using session RPE (sRPE) to categorize training load by effort (i.e., sRPE1, sRPE2, and sRPE3). The Recovery-Stress Questionnaire for Athletes (RESTQ-Sport) questionnaire was implemented after every week of the study period.Results: No differences were found between the respective HR and effort-based zone distributions during the baseline week (p > 0.05). Compared to HR Z1, sRPE1 was significantly lower in weeks 2–4 (p < 0.05), while sRPE2 was higher in weeks 2–3 compared to HR Z2 (p < 0.05) and, in week 4, the tendency (p = 0.06) of the higher amount of sRPE3 compared to HR Z3 was found. There were significant increases in RESTQ-Sport stress scales and decreases in recovery scales mostly during weeks 3 and 4. Increases in the Fatigue scale were associated with the amounts of sRPE2 and sRPE3 (p = 0.011 and p = 0.008, respectively), while no associations with Fatigue were found for HR-based session quantification with internal or external training load variables.Conclusion: During a low-intensity 4-week training period with increasing volume, RPE-based training quantification indicated a shift toward the harder rating of sessions with unchanged HR zone distributions. Moderate and Hard rated sessions were related to increases in Fatigue. Session rating of perceived exertion and effort-based training load could be practical measures in combination with HR to monitor adaptation during increased volume, low-intensity training period in endurance athletes.
Highlights
Athletes frequently use manipulations in training load to stimulate training adaptation
Increased rating of perceived exertion (RPE) scores have been found in the last stages of short (5–7 days) and long in a 21-day cycling race, resulting in an increase of the slope of the relationship between HR and RPE Training Impulse (TRIMP) scores (Rodríguez-Marroyo et al, 2012). These studies and our current results clearly indicate that RPE might be a more sensitive parameter to calculate internal training load compared to methods based on HR time-in-zone calculations, especially during fatigue accumulation to prevent overtraining (Rietjens et al, 2005)
Our study indicates that during a volume increased low-intensity training cycle in rowers, RPE-based training quantification indicated a shift toward harder rated sessions compared to unhanged HR quantification
Summary
Athletes frequently use manipulations in training load (i.e., intensity, duration, and frequency) to stimulate training adaptation It has been clearly demonstrated in rowers that low-intensity training kilometers are positively related to success in championships (Hagerman and Staron, 1982; Steinacker, 1993; Mäestu et al, 2005), and periods of low-intensity and high-volume training are frequently used during preparation to optimize performance. Such increases in low-intensity training may reach up to 50% of the regular training volume (Rämson et al, 2008; Buchheit et al, 2013; Comotto et al, 2015; Thornton et al, 2017). With the aim to optimize performance in the training cycles, training sessions need careful planning and monitoring to improve performance and to avoid nonfunctional overreaching (a process of increased training load in combination with insufficient recovery) (Meeusen et al, 2013; ten Haaf et al, 2017), or even overtraining syndrome
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