Ationship between punching impact and selected strength and power variables in 15 amateur boxers from the Brazilian National Team (9 men and 6 women). Punching impact was assessed in the following conditions: 3 jabs starting from the standardized position, 3 crosses starting from the standardized position, 3 jabs starting from a self-selected position, and 3 crosses starting from a self-selected position. For punching tests, a force platform (1.02 × 0.76 m) covered by a body shield was mounted on the wall at a height of 1 m, perpendicular to the floor. The selected strength and power variables were vertical jump height (in squat jump and countermovement jump), mean propulsive power in the jump squat, bench press (BP), and bench throw, maximum isometric force in squat and BP, and rate of force development in the squat and BP. Sex and position main effects were observed, with higher impact for males compared with females (p ≤ 0.05) and the self-selected distance resulting in higher impact in the jab technique compared with the fixed distance (p ≤ 0.05). Finally, the correlations between strength/power variables and punching impact indices ranged between 0.67 and 0.85. Because of the strong associations between punching impact and strength/power variables (e.g., lower limb muscle power), this study provides important information for coaches to specifically design better training strategies to improve punching impact....

Gallardo-Fuentes, F, Gallardo-Fuentes, J, Ramírez-Campillo, R, Balsalobre-Fernández, C, Martínez, C, Caniuqueo, A, Cañas, R, Banzer, W, Loturco, I, Nakamura, FY, and Izquierdo, M. Intersession and intrasession reliability and validity of the My Jump app for measuring different jump actions in trained male and female athletes. J Strength Cond Res 30(7): 2049–2056, 2016—The purpose of this study was to analyze the concurrent validity and reliability of the iPhone app named My Jump for measuring jump height in 40-cm drop jumps (DJs), countermovement jumps (CMJs), and squat jumps (SJs). To do this, 21 male and female athletes (age, 22.1 ± 3.6 years) completed 5 maximal DJs, CMJs, and SJs on 2 separate days, which were evaluated using a contact platform and the app My Jump, developed to calculate jump height from flight time using the high-speed video recording facility on the iPhone. A total of 630 jumps were compared using the intraclass correlation coefficient (ICC), Bland-Altman plots, Pearson's product moment correlation coefficient (r), Cronbach's alpha (α), and coefficient of variation (CV). There was almost perfect agreement between the measurement instruments for all jump height values (ICC = 0.97–0.99), with no differences between the instruments (p > 0.05; mean difference of 0.2 cm). Almost perfect correlation was observed between the measurement instruments for SJs, CMJs, and DJs (r = 0.96–0.99). My Jump showed very good within-subject reliability (α = 0.94–0.99; CV = 3.8–7.6) and interday reliability (r = 0.86–0.95) for SJs, CMJs, and DJs in all subjects. Therefore, the iPhone app named My Jump provides reliable intersession and intrasession data, as well as valid measurements for maximal jump height during fast (i.e., DJs) and slow (i.e., CMJs) stretch-shortening cycle muscle actions, and during concentric-only explosive muscle actions (i.e., SJs), in both male and female athletes in comparison with a professional contact platform.

Med short-distance sprints and jump tests until 18 days before 100-m dash competitions in track and field to determine if these tests are associated with 100-m sprint times. Testing comprised of squat jumps (SJ), countermovement jumps (CMJ), horizontal jumps (HJ), maximum mean propulsive power relative to body mass in loaded jump squats, and a flying start 50-m sprint. Moderate associations were found between speed tests and competitive 100-m times (r = 0.54, r = 0.61, and r = 0.66 for 10-, 30-, and 50-m, respectively, p ≤ 0.05). In addition, the maximum mean propulsive power relative to body mass was very largely correlated with 100-m sprinting performance (r = 0.75, p < 0.01). The correlations of SJ, CMJ, and HJ with actual 100-m sprinting times amounted to −0.82, −0.85, and −0.81, respectively. Because of their practicality, safeness, and relationship with the actual times obtained by top-level athletes in 100-m dash events, it is highly recommended that SJ, CMJ, and HJ be regularly incorporated into elite sprint-testing routines....

The neuromechanical determinants of sprint running performance have been investigated in team sports athletes and non-elite sprinters. The aim of this study was to quantify the relationships between kinetic and performance parameters, obtained in loaded and unloaded vertical and horizontal jumps, and sprinting in elite athletes. Twenty-two sprinters performed squat jumps, countermovement jumps, horizontal jumps, and jump squats with different loads on a force platform, in addition to a 50-m sprint. Results indicated that jumping height and distance in vertical and horizontal jumps are more strongly correlated (R ≈ 0.81) to sprinting speed than the respective peak forces (R ≈ 0.36). Furthermore, the optimum load generating the maximum power in the jump squat is also highly correlated to sprint performance (R ≈ 0.72). These results reveal that vertical and horizontal jump tests may be used by coaches for assessing and monitoring qualities related to sprinting performance in elite sprinters.

The aim of this study was to investigate the effects of adding vertical/horizontal plyometrics to the soccer training routine on jumping and sprinting performance in U-20 soccer players. The vertical jumping group (VJG) performed countermovement jumps (CMJ), while the horizontal jumping group (HJG) executed horizontal jumps (HJ). Training interventions comprised 11 sessions, with volume varying between 32 and 60 jumps per session. The analysis of covariance revealed that CMJ height and peak force improved only in the VJG, and that HJ distance and peak force improved in both groups. Velocity in 20 m (VEL 20 m) did not improve in either group; however, velocity in 10 m (VEL 10 m) presented a moderate positive effect size (ES = 0.66) in the HJG, while the ES was large (1.63) for improvement in the 10–20 m acceleration in the VJG, and it was largely negative (−1.09) in the HJG. The transference effect coefficients (calculated by the equation: TEC = result gain (ES) in untrained exercise/result gain (ES) in trained exercise) between CMJ and VEL 20 m and ACC 10–20 m were 1.31 and 2.75, respectively. The TEC between HJ and VEL 10 m, VEL 20 m and ACC 0–10 m were 0.44, 0.17 and 0.44, respectively. The results presented herein indicate that the plyometric training-axis is decisive in determining neuromechanical training responses in high-level soccer players.

Pereira, LA, Nimphius, S, Kobal, R, Kitamura, K, Turisco, LAL, Orsi, RC, Cal Abad, CC, and Loturco, I. Relationship between change of direction, speed, and power in male and female National Olympic Team handball athletes. J Strength Cond Res 32(10): 2987–2994, 2018—The aims of this study were to (a) assess the relationship between selected speed- and power-related abilities (determined by 20-m sprint, unloaded countermovement jump [CMJ] and squat jump [SJ], and loaded jump squat [JS]) and performance in 2 distinct change of direction (COD) protocols (Zigzag test and T-test) and (b) determine the magnitude of difference between female and male Brazilian National Olympic Team handball athletes. Fifteen male and 23 female elite handball athletes volunteered to perform the following assessments: SJ and CMJ; Zigzag test and T-test; 20-m sprint with 5-, 10-, and 20-m splits; and mean propulsive power in JS. Pearson's product-moment correlation (p ≤ 0.05) was performed to determine the relationship between the COD tests (Zigzag test and T-test) and speed-power measures (sprint, SJ, CMJ, and JS). The differences between male and female performances were determined using the magnitude-based inference. Moderate to very large significant correlations were observed between both COD tests and the speed-power abilities. Furthermore, male athletes demonstrated likely to almost certainly higher performances than female athletes in all assessed variables. The results of the current study suggest that different speed-power qualities are strongly correlated to the performance obtained in various COD assessments (r values varying from 0.38 to 0.84 and from 0.34 to 0.84 for correlations between speed and power tests with Zigzag test and T-test, respectively). However, the level of these associations can vary greatly, according to the mechanical demands of each respective COD task. Although COD tests may be difficult to implement during competitive seasons, because of the strong correlations presented herein, the regular use of vertical jump tests with these athletes seems to be an effective and applied alternative. Furthermore, it might be inferred that the proper development of loaded and unloaded jump abilities has potential for improving the physical qualities related to COD performance in handball athletes.