80 yr). Subjects were separated into symmetrical strength (SS, n = 13) and asymmetrical strength (SA, n = 11) groups using an asymmetry cutoff of 20%. Subjects walked at a standard speed of 0.8 m·s−1 and at maximal speed on an instrumented treadmill while kinetic and spatiotemporal gait variables were measured. Gait and strength asymmetry were calculated as the percentage difference between legs and gait variability as the coefficient of variation over 20 sequential steps. Results SA had greater strength asymmetry (27.4% ± 5.5%) than SS (11.7% ± 5.4%, P < 0.001). Averaged across speeds, SA had greater single- (7.1% vs. 2.5%) and double-limb support time asymmetry (7.0% vs. 4.3%) than SS and greater single-limb support time variability (9.7% vs. 6.6%, all P < 0.05). Group × speed interactions occurred for weight acceptance force variability (P = 0.02) and weight acceptance force asymmetry (P = 0.017) with greater variability at the maximal speed in SA (5.0% ± 2.4% vs. 3.7% ± 1.2%) and greater asymmetry at the maximal speed in SA (6.4% ± 5.3% vs. 2.5% ± 2.3%). Conclusion Gait variability and asymmetry are greater in older women with strength asymmetry and increase when they walk near their maximal capacities. The maintenance of strength symmetry, or development of symmetry through unilateral exercise, may be beneficial in reducing gait asymmetry, gait variability, and fall risk in older adults....

The purpose of this investigation was to compare and determine the relevance of the morphological characteristics and variability of running speed parameters (stride length and stride frequency) between Usain Bolt’s three best 100 m performances. Based on this, an attempt was made to define which factors determine the performance of Usain Bolt's sprint and, therefore, distinguish him from other sprinters. We analyzed the previous world record of 9.69 s set in the 2008 Beijing Olympics, the current record of 9.58 s set in the 2009 Berlin World Championships in Athletics and the O lympic record of 9.63 s set in 2012 London Olympics Games by Usain Bolt. The application of VirtualDub Programme allowed the acquisition of basic kinematical variables such as step length and step frequency parameters of 100 m sprint from video footage provided by NBC TV station, BBC TV station. This data was compared with other data available on the web and data published by the Scientific Research Project Office responsible on behalf of IAAF and the German Athletics Association (DVL). The main hypothesis was that the step length is the main factor that determines running speed in the 10 and 20 m sections of the entire 100 m distance. Bolt’s anthropometric advantage (body height, leg length and liner body) is not questionable and it is one of the factors that makes him faster than the rest of the finalists from each three competitions. Additionally, Bolt’s 20 cm longer stride shows benefit in the latter part of the race. Despite these factors, he is probably able to strike the ground more forcefully than rest of sprinters, relative to their body mass, therefore, he might maximize his time on the ground and to exert the same force over this period of time. This ability, combined with longer stride allows him to create very high running speed - over 12 m/s (12.05 -12.34 m/s) in some 10 m sections of his three 100 m performances. These assumption confirmed the application of Ballerieich's formula for speed development. In most 10 m sections of the 100 m sprint, the step length was the parameter that significantly determined the increase of maximal running speed, therefore, distinguishing Bolt from the other finalists.

The goal of this study was to examine the relationship between kinematics, motor abilities, anthropometric characteristics, and the initial (10 m) and secondary (30 m) acceleration phases of the 100 m sprint among athletes of different sprinting performances. Eleven competitive male sprinters (10.96 s ± 0.36 for 100 with 10.50 s fastest time) and 11 active students (12.20 s ± 0.39 for 100 m with 11.80 s fastest time) volunteered to participate in this study. Sprinting performance (10 m, 30 m, and 100 m from the block start), strength (back squat, back extension), and jumping ability (standing long jump, standing five-jumps, and standing ten-jumps) were tested. An independent t-test for establishing differences between two groups of athletes was used. The Spearman ranking correlation coefficient was computed to verify the association between variables. Additionally, the Ward method of hierarchical cluster analysis was applied. The recorded times of the 10 and 30 m indicated that the strongest correlations were found between a 1- repetition maximum back squat, a standing long jump, standing five jumps, standing ten jumps (r = 0.66, r = 0.72, r = 0.66, and r = 0.72), and speed in the 10 m sprint in competitive athletes. A strong correlation was also found between a 1-repetition maximum back squat and a standing long jump, standing five jumps, and standing ten jumps (r = 0.88, r = 0.87 and r = 0.85), but again only for sprinters. The most important factor for differences in maximum speed development during both the initial and secondary acceleration phase among the two sub-groups was the stride frequency (p<0.01).

Čoh, M, Vodičar, J, Žvan, M, Šimenko, J, Stodolka, J, Rauter, S, and Maćkala, K. Are change-of-direction speed and reactive agility independent skills even when using the same movement pattern? J Strength Cond Res 32(7): 1929–1936, 2018—The purpose of this investigation was to determine whether there are differences between the 2 approaches to quantifying agility (preplanned vs. unplanned response) when reacting to a stimulus in an identical spatial scenarios. The study involved 45 male and 31 female trained athletes (age 21.2 ± 1.78 and 20.6 ± 1.27 years, body height 181.6 ± 8.31 and 167.7 ± 5.03 cm, and body mass 78.9 ± 11.33 and 63.3 ± 8.65 kg, respectively). A light-based reactive training system was used to measure the time to completion in a task that assessed agility by change-of-direction speed (CODS) in a preplanned condition and reactive agility (RA) in an unplanned condition across 4 spatial configurations. Sprint performance in a 30-m sprint and lower limb reactive power in a 10-m single leg jump test was also measured. Significant differences (p ≤ 0.05) were found between men and women in all tests and between performance in the CODS and RA condition for each spatial configuration. Significant correlations were observed between 30-m starting sprint speed and CODS and RA performance measured in a semicircle (r = 0.62, r = 0.60) and lateral (r = 0.54, r = 0.58) configuration in male athletes. The present findings suggest that CODS and RA are 2 different and independent skill domains that define agility. These qualities should be diagnosed by discrete assessments and enhanced by different training methodologies.

The initiation of the take-off on performance in vertical jumps. The additional area of interest in this experiment was whether technique of the take-off phase might be an exploratory factor that has different electromyogram (EMG) muscle activity during squat jump (SJ) and countermovement jump (CMJ) performed starting from the standard position, with parallel foot placement, and from the experimental one, with straddle foot placement. Six well-experienced male 100–400 m sprinters, who were members of the Polish youth and senior national team (mean values: age 21.6 years, best performance: 100 m in 10.54 seconds and 400 m in 45.54 seconds), performed vertical SJ and vertical CMJ from 2 initial positions with different foot placement. To collect all selected kinematic and kinetic data, the video recording system BTS Vixta was used in conjunction with force platforms (Kistler model 9286B). The latest system for 3D motion analysis, BTS SMART, based on the passive IR reflective markers was also applied. Electromyograms of 6 lower limb muscles were collected using a Noraxon EMG device. The CMJ was on average 7 cm higher than the SJ (CMJ, 85 cm and SJ, 78 cm), which amounts to 8.97%. This was not because of the increase of center of gravity (COG) velocity at take-off because velocities of center of gravity (COG) projection were almost equal (SJ, 2.93 m·s−1compared with CMJ, 2.99 m·s−1). No significant differences of both magnitude and rate of development of the muscle torques and powers between jumps were found, but when we analyzed the problem with division into single legs (right and left) and with division into different jumps (SJ and CMJ), the differences were evident. The profiles of EMG activity of selected muscles showed some differences between SJ and CMJ. The vertical SJ and CMJ performance measurement may be of value to coaches and conditioning specialists who wish to develop or assess the power ability of lower extremities either unilaterally (single leg) or bilaterally (sum of both legs)....

This study investigated whether the addition of eight weeks of inspiratory muscle training (IMT) to a regular preseason soccer training program, including incremental endurance training (IET), would change pulmonary function, lung ventilation, and aerobic performance in young soccer players. Sixteen club-level competitive junior soccer players (mean age 17.63 ± 0.48 years, height 182 ± 0.05 cm, body mass 68.88 ± 4.48 kg) participated in the study. Participants were randomly assigned into two groups: experimental (n = 8) and control (n = 8). Both groups performed regular preseason soccer training, including endurance workouts as IET. In addition to this training, the experimental group performed additional IMT for eigght weeks with a commercially available respiratory muscle trainer (Threshold IMT), with a total of 80 inhalations (twice per day, five days per week). Pre- and post-intervention tests of pulmonary function, maximal inspiratory pressure, and the Cooper test were implemented. Eight weeks of IMT had a positive impact on expiratory muscle strength (p = 0.001); however, there was no significant effect on respiratory function parameters. The results also indicate increased efficiency of the inspiratory muscles, contributing to an improvement in aerobic endurance, measured by VO₂max estimated from running distance in the cardiorespiratory Cooper test (p < 0.005).