Abstract
Background/objective: Cardiovascular measures are important for prescription of appropriate training load; however, little data exist in this respect on handball players. We aimed to explore post- and age-dependent influences of anthropometric determinants on heart rate (HR) and its variability (HRV) in young male handball players (14–21 years) and associations between the different parameters, applying both classical statistical and machine learning methods.
Methods: Participants (n = 85) were included in the study for 11 months. Anthropometric parameters, HR, R-R interval (RRi), root mean square of successive difference of RRi (RMSSD), and its corrected values (by division or multiply with powers of RRi; C_RMSSDs) were analyzed.
Results: The anthropometric data were dependent on the age, primarily in pivots and goalkeepers, but only moderate effects of the age and post were detected in the cardiovascular parameters. High level of correlations was between the anthropometric and cardiovascular parameters in the oldest subgroup, and in the wing and pivot players. The associations between RRi and RMSSD values decreased by the division of RMSSD with RRi, with distinct phenomenon in the different age- and post-based subgroups. Clustering and decision tree regression analyses exposed the crucial feature of RMSSD for determining 3 clusters.
Conclusion: This study firstly revealed the potential significance of the corrected values of HRV parameters in young handball players and revealed complex relationships between the cardiovascular parameters. The proposed systemic analyses explored age- and post-based differences in autonomic function suggesting that individual alterations from the mean values in different subgroups might indicate changes in performance.