TRAINING LOAD AND SLEEP BEHAVIOR: ASPECTS RELATED TO THE STRESS LEVEL, PHYSICAL PERFORMANCE AND RECOVERY PROCESS IN ATHLETES DURING A PRE-SEASON TRAINING MICROCYCLE IN ATHLETES
Training Load, Sleep Behavior, Performance
Introduction: The magnitude of the training load and the state of recovery represent the main means to promote organic adaptations related to sports performance. For this reason, several studies have proposed to monitor the effects of training load on psychophysiological parameters, including sleep behavior. Objective: To investigate the effects of training loads on sleep behavior and its influence on the variables of stress, performance and recovery in young athletics practitioners. Methods: Twenty subjects of both genders (age of 18.2 (± 2.1) years, height of 173.61 (± 21) cm and weight of 63.36 (± 9.96) kg) participated in the study. underwent one week of training, two training sessions a day, totaling 8 sessions. The internal training load (CIT) was measured using the session PSE method and the external training load (CET) using the Player Load method. The daily CIT (CITd) was considered as the sum of the CIT of the morning and afternoon sessions on each day, while the daily CET (CETd) was the average of the morning and afternoon sessions on each day. Sleep time was quantified by actigraph and sleep diary. The repeated measures anova test was performed with Bonferroni post hoc to compare time x effect of training loads (CT), sleep time (TS) and Pearson's linear correlation between CT and TS. Results: The assessment of sleep behavior showed changes for 12 subjects with TS of 422.5 (± 81.36) min. The CTs did not influence the TS during the training microcycle - CITd and TS with r = 0.01 p = 0.94 (day 01), r = -0.27 p = 0.25 (day 02), r = - 0.04 p = 0.86 (day 03) and r = 0.23 p = 0.34 (day 04) and CETd and TS with r = -0.16 p = 0.49 (day 01), r = 0 , 04 p = 0.87 (day 02), r = 0.1 p = 0.68 (day 03) and r = -0.20 p = 0.38. Different sleeping environments (usual and unusual) did not influence the TS with t (18) = 0.06 p = 0.95 (day 01); t (18) = 1.48 p = 0.15 (day 02); t (18) = 0.5 p = 0.62 (day 03) and t (18) = 7.23 p = 0.15 (day 04). Difference in the TS was not able to influence the levels of stress, performance and recovery during the training microcycle. Finally, the perception of recovery was greater for athletes who practiced 6.1 (± 2.1) water compared to those who did not practice 4 (± 1.6) with a significant difference of t (77.922) = 4.79 p = 0.00. Conclusion: Pre-season training loads did not affect sleep behavior in young athletes. Napping proved to be an interesting recovery strategy on days with two training sessions.