García-Pinillos, F, Roche-Seruendo, LE, Marcen-Cinca, N, Marco-Contreras, LA, and Latorre-Román, PA. Absolute reliability and concurrent validity of the Stryd system for the assessment of running stride kinematics at different velocities. J Strength Cond Res 35(1): 78–84, 2021—This study aimed to determine the absolute reliability and to evaluate the concurrent validity of the Stryd system for measuring spatiotemporal variables during running at different velocities (8–20 km·h⁻¹) by comparing data with another widely used device (the OptoGait system). Eighteen trained male endurance runners performed an incremental running test (8–20 km·h⁻¹ with 3-minute stages) on a treadmill. Spatiotemporal parameters (contact time [CT], flight time [FT], step length [SL], and step frequency [SF]) were measured using 2 different devices (Stryd and OptoGait systems). The Stryd system showed a coefficient of variation (CV) <3%, except for FT (3.7–11.6%). The OptoGait achieved CV <4%, except for FT (6.0–30.6%). Pearson correlation analysis showed large correlations for CT and FT, and almost perfect for SL and SF over the entire protocol. The intraclass correlation coefficients partially support those results. Paired t-tests showed that CT was underestimated (p < 0.05, effect size [ES] > 0.7; ∼4–8%), FT overestimated (p < 0.05, ES > 0.7; ∼7–65%), whereas SL and SF were very similar between systems (ES < 0.1, with differences <1%). The Stryd is a practical portable device that is reliable for measuring CT, FT, SL, and SF during running. It provides accurate SL and SF measures but underestimates CT (0.5–8%) and overestimates FT (3–67%) compared with a photocell-based system.

Purpose: The aim of this study was to analyze the effects of plyometric training direction on jumping, sprinting, and change-of-direction ability in basketball players. Methods: Forty male basketball players (21.8 [3.8] y), from 4 teams that competed in regional and national championships, were randomly assigned to 1 of 4 groups: (1) vertical jump group, (2) horizontal jump group, (3) vertical and horizontal jump group, and (4) control group. The subjects followed a plyometric training program twice a week for 6 weeks, differing in the execution direction of the jumps. All groups performed the same total training volume of acyclic and cyclic jumps controlled through the number of contacts per session. Pretraining and posttraining measurements included (1) rocket jump, (2) Abalakov jump, (3) horizontal jump, (4) 20-m linear sprint, and (5) V-Cut change-of-direction test. Results: The vertical and horizontal jump group showed significant increases in all performance variables examined, except for linear sprint performance, in which no group improved. The vertical jump group showed significant improvements in rocket jump and Abalakov jump (P < .01), but worsened significantly in terms of sprint performance (P < .05). The horizontal jump group showed significant increases in rocket jump and horizontal jump (P < .001–.01). Furthermore, all experimental groups showed improved V-Cut change-of-direction test performance. Conclusions: These results indicate that combining vertical and horizontal jumps induces improvements in more capabilities than does training only vertical or horizontal jumps with the same training volume. Training only vertical or horizontal jumps will improve performance mainly in vertically or horizontally oriented tasks, respectively.

In athletic training and research, the evaluation of sprint speed is widely used, and its accurate measurement is especially demanding. High-cost photocells are the gold-standard system for sprint time assessment, although low-cost smartphone applications can be a suitable option. This study assesses the validity and reliability of an application to measure sprint time compared to photocells. Five physically active subjects completed six sprints of 10 m and 20 m at maximal speed and a 5 m go and return sprint to evaluate the validity of the Photo Finish^® app (Version 2.30). To assess reliability, six trials of 5 m go and return sprints were measured by two smartphones. The validity results showed a mean bias of 0.012 s (95% CL: 0.000, 0.024) between the application and the photocells for the 10 m sprint, 0.007 s (95% CL: −0.007, 0.022) for the 20 m sprint and 0.005 s (95% CL: −0.005, 0.017) for the 5 m go and return test. The results also found R² between both systems (R²= 0.9863, 0.990 and 0.958) for each distance (10 m, 20 m and 5 m go and return, respectively). As for reliability, the application showed outstanding consistency between two smartphones operating simultaneously (ICC 0.999; R²: 0.999). This study shows that the Photo Finish^® app is an accurate and reliable tool to measure sprint time with an error of 0.09 s.

Rabal-Pelay, J, Gutiérrez, H, Bascuas, P-J, Pareja-Blanco, F, and Marco-Contreras, LA. Load-velocity relationship in the Bulgarian split-squat exercise. J Strength Cond Res XX(X): 000–000, 2024—The objective of the current research was to analyze the load-velocity relationship in the Bulgarian split-squat (BSS) exercise and to compare these relationships between the dominant and nondominant legs. Twenty-one strength-trained men (age: 27.3 ± 7.3 years) performed a progressive loading test in the BSS exercise using a Smith machine for each leg. The protocol began with a load of 30 kg, incrementally adding 10 kg until the mean propulsive velocity (MPV) fell below 0.4 m·s⁻¹. At that point, 5 kg increments were employed, with a final addition of 2.5 kg for the last estimated attempt one-repetition maximum (1RM). A total of 324 lifts were analyzed. Subjects exhibited a relative strength ratio of 1.23 ± 0.10, a 1RM of 91.3 ± 14.2 kg, and a mean range of motion of 44.7 ± 3.7 cm. Polynomial regression analysis showed a robust relationship with an R ² value of 0.945 (ρ ≤ 0.001) between the relative load (%1RM) and MPV. Despite the differences in 1RM between the dominant and nondominant legs, there were no significant differences in MPV at the %1RM between both legs. These findings suggest that training intensity can be prescribed via the MPV during the BSS exercise. Moreover, the load-velocity relationship is stable between limbs despite the potential differences in absolute strength levels.

The aim of this article was to analyze the step cycle that precedes the throwing action in elite men’s handball and its relationship with different factors, such as throwing distance, throwing technics, throw speed, whether it occurs in jump or standing, the last step, and efficiency. Twenty-four complete matches were analyzed, with a total of 1013 throws in three international elite men’s handball championships. The results show that the most used step cycle is the one performed with two steps. There is a significant relationship between the step cycle and the throw distance, with two-step throws being the most used from outside 9 m (29.8%, p < 0.001), three-step throws at a distance between 6 and 9 m (35.9%, p < 0.001), and zero- and one-step throws from 6 m (30.5%, p < 0.001). Likewise, the last step with natural footing is the most used (93.7%, p < 0.001) with a complete cycle of steps, followed by false foot with more than three steps (27.3%, p < 0.001), and two feet with zero steps (12.6%, p < 0.001). In conclusion, the skill to take advantage of the dynamic improvement offered by the mastery of the step cycle, adapting to the different situations of the game, could be an essential characteristic of the player to effectively complete the throwing action.

Purpose: To analyze the relationships between the evolution of training-load values and countermovement jump (CMJ) as an indicator of stress and fatigue in a high-level 800-m runner during a whole season, including indoor (ID) and outdoor season (OD). Methods: Over 42 weeks, daily training load was quantified as the result of the product of the intensity and volume, and it was termed load index (LI). CMJ was measured in every running session after warm-up and immediately after the last effort of the session. Other jump-related variables such as CMJ height loss, average weekly CMJ, initial CMJ of the next consecutive session, and initial CMJ of the following week were studied. Results: A significant negative relationship was observed between LI and weekly CMJ (ID: r = −.68, P < .001, common variance [CV] = 46%; OD: r = −.73, P < .001, CV = 53%), initial CMJ of the following week (OD: r = −.71, P < .01, CV = 50%), and CMJ height loss (ID: r = −.58, P < .01, CV = 34%; OD: r = −.52, P < .01, CV = 27%). A significant positive relationship was observed between LI and initial CMJ of the next consecutive session when LI values were <8 (OD: r = .72; P < .01, CV = 52%). However, from values ≥8, the relationship turned into a significant negative one (ID: r = −.74; P < .01, CV = 55%; OD: r = −64, P < .01, CV = 41%). Conclusions: CMJ may be a valid indicator of the degree of stress or fatigue generated by specific training sessions of a competitive athlete within a single session, a week, or even the following week. There could be an individual limit LI value from which the training volume does not allow a positive effect on high-speed actions such as a CMJ in the next consecutive session.