Effect of somatotype on the general physical fitness tests and throwing velocity on handball

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.

The height importance of male athletes for the classification in the world handball championships

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.

Acute Responses to 10×15 m Repeated Sprint Ability Exercise in Adolescent Athletes: the Role of Change of Direction and Sport Specialization.

BACKGROUND: The repeated sprint ability (RSA) has been studied with protocols using distances longer than 20 m per sprint, whereas basketball players cover on average less than 20-meter distance per sprint during match. OBJECTIVES: The aim of the present study was to examine the physiological impact of 10 × 15 m RSA test in straight-line (RSASL) or with change of direction (RSACOD), i.e. 10 × (7.5 + 7.5 m)) in young national level basketball players. PATIENTS AND METHODS: Young basketball players (n = 11, age 17.1 (1.0) years, body mass 76 (6) kg, height 184 (4) cm, body mass index 22.6 (1.8) kgm(-2), sport experience 6.9 (2.7) years, mean (standard deviation)) and a control group consisting of high-school athletes (n = 7, 16.1 (0.7) years, 67 (6) kg, 177 (6) cm, 21.5 (1.0) kgm(-2), 7.7 (1.6) years, respectively) performed RSASL and RSACOD on a counter-balanced order. Sprints started every 30 seconds (active recovery) and there was 30 minutes break between RSA protocols; time variables were total time (TT), best time (BT) and fatigue index (FI). Countermovement jump (CMJ) was tested before and after each RSA protocol. Heart rate (HR) was continuously monitored during testing procedures. RESULTS: Compared with RSASL, TT and BT were worst in RSACOD (38.13 vs. 27.52 s and 3.67 vs. 2.66 s, P < 0.001, respectively), whereas FI did not differ (3.8 vs. 3.5%, P = 0.388). A 2 × 2 repeated measures ANOVA showed main effect of RSA on CMJ (pre-test vs. post-test, increase + 1.8 cm, P = 0.020, η(2) = 0.28); there was neither main effect of RSA protocols (RSASL vs. RSACOD +0.7 cm, P = 0.251, η(2) = 0.08) nor an interaction between pre-post measurements and RSA protocols (P = 0.578, η(2) = 0.02). Compared with RSASL, RSACOD induced higher mean and peak HR responses (175 vs 172 bpm, P < 0.001, and 185 vs 182 bpm, P = 0.002, respectively). No statistical difference was observed between basketball players and control group neither for TT (27.98 vs. 26.80 seconds, + 4.4%, P = 0.149) and BT (2.71 vs. 2.59 seconds, + 4.5%, P = 0.157) in RSASL nor for TT (38.55 vs. 37.47 seconds, + 2.9%, P = 0.169) and BT (3.70 vs. 3.63 seconds, 1.8%, P = 0.414) in RSACOD. CONCLUSIONS: In conclusion, RSASL and RSACOD differed for time variables (TT and BT) and HR responses. Despite being non-significant, the trend that adding COD reduced the percentage differences in TT and BT between the two groups highlighted the role of sport specialization.