HIIT Models in Addition to Training Load and Heart Rate Variability Are Related With Physiological and Performance Adaptations After 10-Weeks of Training in Young Futsal Players - Campos, Fernando de Souza; Borszcz, Fernando Klitzke; Flores, Lucinar Jupir Forner; Barazetti, Lilian Keila; Teixeira, Anderson Santiago; Hartmann Nunes, Renan Felipe; Guglielmo, Luiz Guilherme Antonacci (Frontiers in Psychology, 2021)
Introduction: The present study aimed to investigate the effects of two high-intensity interval training (HIIT) shuttle-run-based models, over ten weeks on aerobic, anaerobic, and neuromuscular parameters, and the association of the training load and heart rate variability (HRV) with the change in the measures in young futsal players. Methods: Eleven young male futsal players (age: 18.5 ± 1.1 years; body mass: 70.5 ± 5.7 kg) participated in this study. This pre-post study design was performed during a typical 10 weeks training period. HIIT sessions were conducted at 86% (HIIT86; n = 6) and 100% (HIIT100; n = 5) of peak speed of the FIET. Additionally, friendly and official matches, technical-tactical and strength-power training sessions were performed. Before and after the training period, all players performed the FIET, treadmill incremental, repeated sprint ability (RSA), sprint 15-m, and vertical jump tests (CMJ and SJ), and the HRV was measured. Training load (TL) was monitored using the session rating of perceived effort. Data analysis was carried out using Bayesian inference methods. Results: The HIIT86 model showed clear improvements for the peak oxygen uptake (VO2peak), peak speed in the treadmill incremental test, first and second ventilatory thresholds, RSA best and mean times, CMJ, and SJ. The HIIT100 model presented distinct advances in VO2peak, peak speed in the treadmill incremental test, RSA mean time, and CMJ. Between HIIT models comparisons showed more favorable probabilities of improvement for HIIT86 than HIIT100 model in all parameters. TL data and HIIT models strongly explained the changes in the RSA mean and best times (R² = 0.71 and 0.87, respectively), as well as HRV changes, and HIIT models explained positively VO2peak changes (R² = 0.72). All other changes in the parameters were low to moderately explained. Conclusion: The HIIT86 proved to be more effective for improving aerobic, RSA, and neuromuscular parameters than HIIT100 during a typical 10-week futsal training period. So, strength and conditioning specialists prescribing shuttle-run intermittent exercises at submaximal intensities can manage the individual acceleration load imposed on athlete increasing or decreasing either the set duration or the frequency of change of direction during HIIT programming.