ABSTRACT
Abstract Aim: The study aimed to investigate the effects of the somatotype components on handball. Methods: The sample consisted of 60 elite junior handball players. Somatotype was evaluated using the Heath & Carter method. The kinetic performance trials of the handball athletes were running speed performance over 5 m 10 m and 20 m sprints, sit and reach, standing long jump (SLJ), ball velocity, and maximum aerobic power. For the data analyses, we used Pearson correlation and multiple linear regression. Results: The endomorphic component correlated positive with all three sprint times (5 m, 10 m και 30 m sprints) (r = 0.315, p = 0.014; r = 0.367, p = 0.004; r = 0.358, p = 0.005 respectively) while negative with SLJ (r = -0.418, p = 0.001) και maximum aerobic power (r = -0.322, p = 0.012). The mesomorphic component had a positive correlation with ball velocity (r = 0.260, p = 0.045) and negative relation with SLJ (r = -0.261, p = 0.044). The ectomorphic component exhibited a negative correlation only with ball velocity (r = -0.260, p = 0.045). The ordinary least square regression models found that endomorphy and ectomorphy were prognostic factors and predicted worse performance in all of the examined motor performance indices except ball velocity and 5 m sprint, while mesomorphy was a predictor of worse performance in SLJ. Conclusions: In conclusion, according to the findings of this study, somatotype components play an important role in performance-related parameters.
ABSTRACT
Abstract Aim: The main purpose of the study was to investigate the height factor and player position concerning final team ranking in the three age categories, youths, juniors, and seniors. Height data were checked. Methods: Data was analyzed from 24 participating teams for seniors (n = 972, age = 27.3 ± 4.5), juniors (n = 622 age = 19.9 ± 1.0), and youths (1035 age = 18.8 ± 0.2) from official data from the selected last male World Handball Championships of 2013-2019. For each participating player, his position was noted too: backs (left and right), pivot (line player), goalkeeper, back (center), and wings (left and right). The final team ranking was recorded and the 24 teams were divided into 3 ranking groups of 8 teams. Results: The ANOVA test proved that mean heights were significantly different between the three age groups (seniors: 190.04 ± 7.33, juniors: 187.28 ± 8.13, youths: 186.84 ± 7.55, F(2,3095) = 61.1 p < 0.001). Effect size 0.039. In all ranked groups and all categories, the heights of the players were significantly different between different player positions. The discrimination ability of height in all three categories and player positions represented an overall percentage of around 70% classifying the three 8-team ranking tiers. Conclusion: Height is a factor that differentiates high-level performance for both players' position and age categories. The practical results can help the national federations and coaches apply more effective strategies for player selection.