Hammami, R, Sekulic, D, Selmi, MA, Fadhloun, M, Spasic, M, Uljevic, O, and Chaouachi, A. Maturity status as a determinant of the relationships between conditioning qualities and preplanned agility in young handball athletes. J Strength Cond Res 32(8): 2302–2313, 2018—Studies performed thus far have not accounted for the potential influence of maturity on determinants of preplanned agility. This study aimed to examine how determinants of preplanned agility are affected by the period of peak height velocity (PHV) regarding the anthropometrics and conditioning qualities in young handball players. The sample comprised 56 handball players (male; 12–14 years of age), allocated into 2 groups according to their biological age of maturity: Pre-PHV (N = 34) and Post-PHV (N = 22). Players were evaluated on handball-specific tests of preplanned agility (CODAT and T-HALF). Predictors included anthropometrics, sprinting, horizontal and vertical jumps, and reactive strength index (RSI). The reliability of the tests was appropriate (intraclass correlation coefficient: 0.87–0.95; coefficient of variation: 4.4–5.8%). In the Pre-PHV group, 67% variance of the T-HALF accounted for horizontal countermovement jump (β: −0.83, p < 0.01), 20-m sprint (β: 0.91, p < 0.01), and body mass (β: 0.19, p = 0.02). In the Post-PHV group, 80% of the T-HALF variance was explained, with a significant influence of 20-m sprint (β: 0.52, p < 0.01), RSI (β: −0.24, p = 0.04), and standing long jump (β: −0.57, p = 0.03). In the Pre-PHV group, 45% of the CODAT variance accounted for the partial influence of body fat percentage (β: 0.44, p = 0.04) and a 20-m sprint (β: 0.74, p < 0.01). In the Post-PHV group, the predictors accounted for 79% of the CODAT variance, with a significant influence of the RSI (β: −0.26, p = 0.04) and a 10-m sprint (β: 0.87, p = 0.03). Our results reinforce the need for differential strength and conditioning programs aimed at improving the preplanned agility of young athletes who differ in maturity status.
1Tunisian Research Laboratory “Sports Performance Optimization”, National Center of Medicine and Science in Sports (CNMSS), Tunis, Tunisia;
2Faculty of Kinesiology, University of Split, Split, Croatia;
3Research Unit (UR17JS01), Sport Performance, Health and Society, Higher Institute of Sport and Physical Education of Ksar Saîd, University of Manouba, Tunis, Tunisia; and
4Sports Performance Research Institute, AUT University, Auckland, New Zealand
Address correspondence to Dr. Damir Sekulic, firstname.lastname@example.org.