Stress plays a significant role in competitions and in the training of sports participants, and coaches are no exception. To better cope with stressful situations, close monitoring of coaches’ stress levels before, during, and after training and competitions is recommended. According to studies, the use of cortisol (C) and alpha-amylase (AA) as biomarkers for monitoring acute stress is recommended. Therefore, the aim of our study was to compare HR, salivary C and AA, and STAI scores before, during, and after handball matches and training sessions. The study examined one professional handball coach, aged 37, in stress markers (salivary cortisol (C) and alpha-amylase (AA) concentrations), heart rate (HR), and the State-Trait Anxiety Inventory (STAI) scores in five matches/training sessions in the First Qatar Handball League. Statistical analysis included the calculation of descriptive statistic parameters, Mann–Whitney U test for differences between match–training time points, and the effect size analysis (Cohen’s d) to calculate the magnitude of differences between match–training time points. Presented markers (C and AA) had statistically stronger reactions before, during, and after the matches than the corresponding time points of the training sessions, similar to HR data and STAI scores. Results indicate that, before and during the matches, the analyzed markers of stress increased, which might lead to the conclusion that coaches are more anxious than frightened before and during matches. Thus, stress-coping strategies for handball coaches should be more focused on stress anticipation and anxiety control.

Stress was previously defined as a response to any demand for change. These demands are noticeable during sport events, not only in athletes but also in coaches. Therefore, this study aimed to determine the influence of slow-paced breathing (SPB) on acute stress to handball coaches during official matches. One professional handball coach, aged 37 (height, 180 cm; weight, 80 kg), took part in the study. His salivary cortisol (C) concentration and alpha-amylase (AA) activity were measured, and his heart rate (HR) was monitored during six official matches. In the first three matches the SPB training protocol was not followed. From match four to match six, the coach performed SPB training every day and directly before the match. The decrease observed in AA was statistically significant with a large effect size (1.80). The trend of change in HR is visible and similar for matches with and without SPB. However, for SPB matches, there is a lower starting point compared to matches without SPB (89.81 ± 6.26 and 96.62 ± 8.10, respectively). Moreover, values of AA on SPB matches were smaller before the match (93.92 ± 15.89) compared to the same time point in non-SPB matches (115.30 ± 26.00). For AA, there is a significant effect size in the half-time (2.00) and after the match (−2.14). SPB matches showed a lower increase in AA. SPB might be used as one of the possible tools that could help coaches in achieving a desirable mental state during the match.

Background: This study investigates the psychophysiological stress profiles of professional basketball players by simultaneously analyzing two distinct neuroendocrine pathways: the sympathetic–adrenal–medullary (SAM) system, via salivary alpha-amylase (AA), and the hypothalamic–pituitary–adrenal (HPA) axis, via salivary cortisol (C). While competitive environments are known to elicit significant stress, the interaction between game-specific variables—such as playing time (PT) and tactical position—and those biomarkers remains insufficiently explored in real-time, official match settings. Methods: Twelve professional male basketball players were monitored across four official matches. Salivary samples were collected, and stress biomarkers (AA and C) were analyzed at three timepoints: pre-match, half-time, and post-match. Results: Results indicate that stress responses are non-uniform and highly context-dependent. A significant spike in AA was observed during the first match (p < 0.001; ES = 0.82; 95% CI −0.01–1.66), where concentrations rose from a pre-match mean of 247.9 ± 232.59 U/mL to a post-match peak of 674.39 ± 693.33 U/mL. Cortisol responses did not vary significantly across matches but exhibited a strong positive correlation with PT (p = 0.01; R = 0.76), identifying that C may serve as a primary marker of individual physical workload. Positional analysis revealed significant divergence in HPA activation; guards (0.55 ± 0.31 µg/dL) and centers (0.51 ± 0.22 µg/dL) exhibited higher cortisol levels compared to forwards (0.24 ± 0.18 µg/dL), reflecting the high cognitive/decision-making load of guards and the mechanical/physical contact load of centers. Conclusions: The observed differences in AA and C liberation suggest that stress responses during matches are influenced by a complex interaction of physiological and psychological stimuli characteristic of competitive basketball. Consequently, these findings indicate the importance and value of a dual-biomarker approach which might provide a framework for optimized training load management and recovery protocols in elite basketball.

The aim of this study is to predict the "adult" body height of female volleyball players by using the method of Sherar et al. The sample of participants included 49 senior Croatian female volleyball players (22.14±1.26 years). Varibales assessed were: Body height, Body mass, Age at Peak height velocity (PHV), Coefficient of variation in PHV, Prediction of adult height, and Variation in predicted adult height. T test was used to analyze the differences between active volleyball players and drop-outs, 8 years after the first measurement of anthropometric characteristics, with the level of significance set at p≤0.05. By using the Bland-Altman method, a plot of the differences between the measured body height and the lowest predicted body height was presented. The obtained results indicate that the predictive values of adult body height in active volleyball players are lower than the actual values, i.e., drop-outs have lower values of deviation from actual adult body height. Significant differences were found between active and inactive volleyball players/drop-outs in the 4 applied variables.