ABSTRACT
BACKGROUND: Monitoring of training load is done to improve physical performance and minimize the incidence of injuries. The study examined the correlation between accumulated training load parameters based on periods with maturity (i.e., maturity offset and peak height velocity -PHV- and wellness variables -e.g., stress and sleep quality-). The second aim was to analyze the multi-linear regression between the above indicators. METHODS: Twenty elite young U14 soccer players (M = 13.26 ± 0.52 years, 95% CI [13.02, 13.51]) were evaluated over 26 weeks (early, mid, and end-season) to obtain stress, sleep quality, and measures of workload in the season (accumulated acute workload [AW], accumulated chronic workload [CW], accumulated acute: chronic workload ratio [ACWLR], accumulated training monotony [TM], accumulated training strain [TS]). RESULTS: The analysis revealed a moderate, statistically significant negative correlation between sleep quality and training monotony (r = -0.461, p < 0.05). No significant correlations were observed between other variables (p > 0.05). In the multi-linear regression analysis, maturity, PHV, sleep, and stress collectively accounted for variances of 17% in AW, 17.1% in CW, 11% in ACWLR, 21.3% in TM, and 22.6% in TS. However, individual regression coefficients for these predictors were not statistically significant (p > 0.05), indicating limited predictive power. CONCLUSION: The study highlights the impact of sleep quality on training monotony, underscoring the importance of managing training load to mitigate the risks of overtraining. The non-significant regression coefficients suggest the complexity of predicting training outcomes based on the assessed variables. These insights emphasize the need for a holistic approach in training load management and athlete wellness monitoring.
Subject(s)
Physical Conditioning, Human , Soccer , Humans , Soccer/physiology , Soccer/injuries , Adolescent , Physical Conditioning, Human/methods , Physical Conditioning, Human/physiology , Male , Sleep Quality , Linear Models , Athletic Performance/physiology , Stress, PsychologicalABSTRACT
BACKGROUND: It is considered that the maturity condition of young football players is related to their physical performance during short high-intensity efforts dependent on anaerobic power ability. Hence, the aim was to determine possible relationships between maturity status and training intensity by measuring the footballer´s peak height velocity (PHV), maturity offset and anaerobic power. METHODS: Seventeen youth male players of different playing positions participated in the study and performed tests at three different stages of the season (early-, mid- and end-season) All the anthropometric parameters and biomarkers related to maturation were controlled during the season. The training intensity and load was monitored and the anaerobic power of the players was assessed by a running-based anaerobic sprint test (RAST). RESULTS: The analysis of all the recorded data revealed a positive relationship between PHV and anaerobic power in the early- and end-season stages (p < 0.05). Maturity offset and anaerobic power (mean RAST) showed an absolute correlation in early- and end -season stages (r: - 0.39 to 0.91). The multiple linear regression analysis revealed that min RAST was the best predictor for both PHV and maturity offset. The analysis of the training intensity and workloads showed a positive effect on the performance in the fitness test (p < 0.05). Additionally, players experienced less fatigue at the end-season stage than at the early-season. CONCLUSIONS: The results show that coaches might benefit from monitoring training loads and the maturity status of the players in order to enhance their physical performance during the season.
