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This study aimed to evaluate the between-session reliability of single-leg performance and asymmetry variables during unilateral and bilateral countermovement jumps (CMJ). Twenty-three basketball players completed two identical sessions which consisted of four unilateral CMJs (two with each leg) and two bilateral CMJs. Mean and peak values of force, velocity and power, impulse, and jump height were obtained separately for each leg using a dual force platform. All performance variables presented an acceptable reliability (CV range = 4.05–9.98%) with the exceptions of jump height for the unilateral CMJs and mean power, peak velocity, peak power, and impulse for the left leg during the bilateral CMJ (CV≥11.0%). Nine out of 14 variables were obtained with higher reliability during the unilateral CMJ (CV ratio ≥1.16), and 4 out of 14 during the bilateral CMJ (CV ratio ≥1.32). Asymmetry variables always showed an unacceptable reliability (ICC range = 0.15–0.64) and poor / slight levels of agreement in direction (Kappa range = -0.10 to 0.15) for the unilateral CMJ, while an acceptable reliability (ICC range = 0.74–0.77) and substantial levels of agreement in direction (Kappa range = 0.65 to 0.74) were generally obtained for the bilateral CMJ. These results suggest that single-leg performance can be obtained with higher reliability during the unilateral CMJ, while the bilateral CMJ provides more consistent measures of inter-limb asymmetries.

This study aims to determine the validity of the linear critical power (CP) and Peronnet models to estimate the power output associated with the second ventilatory threshold (VT2) and the maximal aerobic power (MAP) using two‐time trials. Nineteen recreational runners (10 males and 9 females and maximum oxygen uptake: 53.0 ± 4.7 mL/kg/min) performed a graded exercise test (GXT) to determine the VT2 and MAP. On a second test, athletes performed two‐time trials of 9 and 3 min interspaced by 30 min. The CP was determined from the linear CP model and compared with the power output associated with the VT2. The MAP was determined from the linear Peronnet model, established at 7 min, and compared with the MAP determined in the GXT. The CP model was valid for determining the VT2, regardless of sex (p = 0.130; 9/3 vs. GXT: 3.5 [−1.1 to 8.2] W). The MAP was overestimated (p = 0.015) specifically in males (9/3 vs. GXT: 9.2 [3.3 to 15.1] W) rather than in females (p = 9/3 vs. GXT: 1.7 [−4.4 to 8.0] W). Therefore, MAP estimates were determined introducing the CP and W' parameters to a stepwise multiple linear regression analysis. For females, the CP was the unique significant predictor of MAP (p < 0.001) explaining 96.7% of the variance. In males, both CP and W' were significant predictors of MAP (p < 0.001) explaining 97.7% of the variance. Practitioners can validly estimate the VT2 and MAP through a practical testing protocol in both male and female recreational runners.

Markerless motion capture systems (MCS) have been developed as an alternative solution to overcome the limitations of 3D MCS as they provide a more practical and efficient setup process given, among other factors, the lack of sensors attached to the body. However, this might affect the accuracy of the measures recorded. Thus, this study is aimed at evaluating the level of agreement between a markerless MSC (i.e., MotionMetrix) and an optoelectronic MCS (i.e., Qualisys). For such purpose, 24 healthy young adults were assessed for walking (at 5 km/h) and running (at 10 and 15 km/h) in a single session. The parameters obtained from MotionMetrix and Qualisys were tested in terms of level of agreement. When walking at 5 km/h, the MotionMetrix system significantly underestimated the stance and swing phases, as well as the load and pre-swing phases (p < 0.05) reporting also relatively low systematic bias (i.e., ≤ −0.03 s) and standard error of the estimate (SEE) (i.e., ≤0.02 s). The level of agreement between measurements was perfect (r > 0.9) for step length left and cadence and very large (r > 0.7) for step time left, gait cycle, and stride length. Regarding running at 10 km/h, bias and SEE analysis revealed significant differences for most of the variables except for stride time, rate and length, swing knee flexion for both legs, and thigh flexion left. The level of agreement between measurements was very large (r > 0.7) for stride time and rate, stride length, and vertical displacement. At 15 km/h, bias and SEE revealed significant differences for vertical displacement, landing knee flexion for both legs, stance knee flexion left, thigh flexion, and extension for both legs. The level of agreement between measurements in running at 15 km/h was almost perfect (r > 0.9) when comparing Qualisys and MotionMetrix parameters for stride time and rate, and stride length. The agreement between the two motion capture systems varied for different variables and speeds of locomotion, with some variables demonstrating high agreement while others showed poor agreement. Nonetheless, the findings presented here suggest that the MotionMetrix system is a promising option for sports practitioners and clinicians interested in measuring gait variables, particularly in the contexts examined in the study.

This study aimed (i) to explore the reliability of the load–velocity relationship variables (load‐axis intercept [L0], velocity‐axis intercept [v0], and the area under the load–velocity relationship line [Aline]) obtained during the countermovement jump exercise in successive sessions and (ii) to examine the feasibility of the load–velocity relationship variables to detect acute changes in the lower‐body maximal mechanical capacities following different velocity‐based training (VBT) protocols. Twenty‐one recreational runners completed four randomized VBT protocols (three back squat sets with three minutes of rest) on separate occasions: (i) VBT with 60% of the one‐repetition maximum (1RM) and 10% velocity loss (VBT60–10); (ii) VBT with 60% 1RM and 30% velocity loss (VBT60–30); (iii) VBT with 80% 1RM and 10% velocity loss (VBT80–10); and (iv) VBT with 80% 1RM and 30% velocity loss (VBT80–30). The load–velocity relationship was determined before and after each VBT protocol using the two‐point method in the countermovement jump with a 0.5 kg load and another matching a mean velocity of 0.55 m·s−1. All load–velocity relationship variables had an acceptable reliability (CV ≤ 5.61% and ICC ≥ 0.83, except for v0 between VBT60–30 and VBT80–10). Both v0 and Aline were reduced after VBT60–30 and VBT80–30 (p ≤ 0.044 and ES ≥ −0.47) but not after VBT60–10 and VBT80–10 (p ≥ 0.066 and ES ≤ −0.37). The post–pre differences were not significantly associated between VBT protocols for any load–velocity relationship variable (r ≤ 0.327 and p ≥ 0.148). Although the load–velocity relationship is reliable and sensitive to high‐repetition VBT protocols, its use to detect acute changes in the lower‐body maximal mechanical capacities is characterized by a high variability in individual responses.

This study aimed to elucidate whether ballistic, maximal strength and strength-endurance performances are affected by the sex of the evaluator. Sixteen young male handball players attended two testing sessions that only differed in the sex of the evaluators (2 women vs . 2 men). The two sessions were performed in a counterbalanced order. Ballistic performance (countermovement jump height and throwing velocity), maximal strength performance (squat and bench press [BP] one-repetition maximum [1RM]), and strength-endurance performance (number of repetitions-to-failure in BP and average velocity of the set in the squat) were assessed in both sessions. BP 1RM was greater in the presence of women evaluators ( p = 0.036, ES = 0.09), whereas no differences were observed for the remaining variables ( p ≥ 0.254, ES ≤ 0.19). Low correlations ( r median [range] = -0.074 [-0.693, 0.326]) were observed between the different performance tests for the percent differences between both testing sessions. The sex of the evaluators has minimal influence on a number of physical traits in young male handball players when they are tested in the presence of other members of the team, while the low correlations indicate that a higher performance in one test under the presence of women does not imply a higher performance under the presence of women in other performance tests.

This study aimed to compare the accuracy of the power output, measured by a power meter, with respect to the speed, measured by an inertial measurement unit (IMU) and a global navigation satellite system (GNSS) sport watch to determine the critical power (CP) and speed (CS), work over CP (W') and CS (D'), and long‐duration performance (i.e., 60 min). Fifteen highly trained athletes randomly performed seven time trials on a 400 m track. The CP/CS and W'/D' were defined through the inverse of time model using the 3, 4, 5, 10, and 20 min trials. The 60 min performance was estimated through the power law model using the 1, 3, and 10 min trials and compared with the actual performance. A lower standard error of the estimate was obtained when using the power meter (CP: 2.7 [2.1–3.3] % and W': 13.8 [10.4–17.3] %) compared to the speed reported by the IMU (CS: 3.4 [2.5–4.3] %) and D': 20.7 [16.6–24.7] %) and GNSS sport watch (CS: 3.4 [2.5–4.3] % and D': 20.6 [16.7–24.7] %). A lower coefficient of variation was also observed for the power meter (4.9 [3.7–6.1] %) Regarding the speed reported by the IMU (10.9 [7.1–14.8] %) and GNSS sport watch (10.9 [7.0–14.7] %) in the 60 min performance estimation, the power meter offered lower errors than the IMU and GNSS sport watch for modelling endurance performance on the track. Highlights Recent advances in wearable technology are creating new opportunities to accurately monitor running intensity in contexts where precision is essential (i.e., track running) for athletes' (e.g., pacing) and coaches' (e.g., performance analysis) tasks. The track mode of recent global navigation satellite system (GNSS) sport watches seems to offer a decent improvement. Alternatively, new inertial measurement units (IMUs) designed specifically for running have emerged offering the capability to monitor distance in specific contexts such as treadmills and indoor tracks. Additionally, these IMUs provide new metrics of the external load. The power meter provided by the Stryd inertial measurement unit (IMU) demonstrated lower estimation errors in modelling endurance running performance on the track compared to speed data reported by the same IMU and a Garmin GNSS sports watch (using the track mode).

This study explored the goodness-of-fit and the effect of fatigue on the precision of both generalized and individualized relationships between the velocity loss (%VL) magnitude and the percentage of completed repetitions with respect to the maximal that can be performed to failure (%Rep) in the Smith machine parallel back-squat exercise. Twenty-nine resistance-trained males completed four sets to failure, with a rest period of 2 min, against 75% of the one-repetition maximum. Generalized and individualized %Rep-%VL equations determined in the first set were used to estimate %Rep when a 20%VL was achieved during the three successive sets. Individualized %Rep-%VL relationships (R2 = 0.84–0.99) showed a greater goodness-of-fit than the generalized %Rep-%VL relationship (R2 = 0.82). However, the accuracy in the %Rep estimation was always low (absolute errors > 10%) and comparable for both regression models (p = 0.795). %Rep was progressively overestimated when increasing the number of sets using the MVfastest of the first set (from 15% to 45%), but no meaningful overestimations were observed using the MVfastest of each set (~2%). In conclusion, neither the generalized nor the individual %Rep-%VL equations provide accurate estimations of %Rep during the parallel back-squat exercise executed under fatigue.

The aim of the present study was to explore whether military-specific reaction time (RT) test performance is affected by individuals' physical and visual skills. In a single testing session, the military-specific Simple and Go, No-Go RT, aerobic power (20-m Multistage Shuttle Run test), maximal upper- and lower-body mechanical capacities (bench press and squat against different loads), and visual skills (multiple object tracking and dynamic visual acuity) of 30 young men (15 active-duty military personnel and 15 sport science students) were evaluated. The main findings revealed that the Simple RT and Go, No-Go RT presented (1) with aerobic power non-significant small correlations in military personnel = -0.39 and -0.35, respectively) and non-significant negligible correlations in sport science students ( = -0.10 and 0.06, respectively), (2) inconsistent and generally non-significant correlations with the maximal mechanical capacities of the upper- and lower-body muscles ( range = -0.10, 0.67 and -0.27, 0.48, respectively), (3) non-significant correlations with visual skills ( magnitude ≥ 0.58) with the only exception of the Go, No-Go RT that was significantly correlated to all visual variables in the group of students ( ., students who achieved better results during visual tests had shorter RT; magnitude ≥ 0.58), and (4) none of the physical and visual variables significantly predicted the Simple RT or Go, No-Go RT. Altogether, these results indicate that military-specific RT performance is generally independent of physical and visual skills in both military personnel and active university students.

This review aims to synthesize and discuss the potential effects of a stack height modification on the function of the different footwear features and their effects on running performance. Peer-reviewed studies were identified from electronic databases using a structured keyword search and a screening process. Complementary sources were used to illustrate and discuss the current racing footwear constructions. With regard to the shoe mass, it is suggested that a stack height difference of 20 mm could induce a meaningful effect on performance. With respect to the midsole properties, it seems that reducing the stack height does not alter the energy returned, given that the lower midsole deformation is counteracted with an increased stiffness. However, it should be noted that this might affect the timing of the midsole deformation and restitution, which should be matched with the mid and propulsive stance phases. Lastly, the curved geometry of the forefoot sole needed to create the teeter-totter effect could be affected by the stack height reduction. However, current racing footwear designs have counteracted this modification by proximately placing the rocker axis and increasing the toe spring.

Objectives: To evaluate the validity, accuracy, and reliability of the G-Force force platform during isometric tests, through comparison with a gold-standard force platform in physically active young adults. Methods: Nine physically active participants (23.67 ± 4.97 years; body mass index: 25.79 ± 3.02 kg/m2) performed isometric posterior lower limb muscle tests per leg, following a standardized warm-up and familiarization protocol. The G-Force platform and compared against a gold-standard device, the Valkyria Trainer Balance (VTB) force platform. The measured variables included Peak Force and peak rate of force development (RFD) at 50, 100 and 150 ms (RFD50, RFD100 and RFD150). Intra- and inter-platform reliability were assessed using intraclass correlation coefficients (ICC), standard error of measurement (SEM), coefficient of variation (CV%), Bland–Altman analysis and Pearson’s correlation coefficients between both platforms. Results: Peak Force showed excellent intra-platform repeatability (ICC = 0.86–0.91) and moderate-to-good inter-platform reliability (ICC = 0.75–0.77), with the G-Force platform generally reporting slightly lower absolute values than VTB. RFD measures demonstrated moderate reproducibility (ICC = 0.75–0.87) and higher variability (CV = 47–57%). Bland–Altman analyses revealed minimal bias for Peak Force, while regression analyses indicated strong, significant associations between G-Force and VTB measurements (R2 = 0.55–0.77; β = 0.74–0.88; p < 0.05). Conclusions: The G-Force force platform is a valid, reliable, and low-cost tool for assessing isometric strength in physically active young adults.