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Purpose: To determine the minimum number of events (training or matches) for producing valid acceleration–speed (AS) profiles from global navigation satellite system (GNSS) data. Methods: Nine elite female soccer players participated in a 4-week training camp consisting of 19 events. AS profile metrics calculated from different combinations of athlete events were compared to force–velocity (FV) profile metrics from 2 × 40-m stand-alone sprint effort trials, using the same GNSS 10-Hz technology. Force–velocity profiles were calculated, from which AS profiles were obtained. AS profiles from training and matches were generated by plotting acceleration and speed points and performing a regression through the maximal points to obtain the AS metrics (theoretical maximal speed, x-intercept [in meters per second], theoretical maximal acceleration, y-intercept [in meters per second squared], and the slope per second). A linear mixed model was performed with the AS metrics as the outcome variables, the number of events as a fixed effect, and the participant identifier as a mixed effect. Dunnett post hoc multiple comparisons were used to compare the means of each number of event grouping (1–19 events) to those estimated from the dedicated sprint test. Results: Theoretical maximal speed and theoretical maximal acceleration means were no longer significantly different from the isolated sprint reference with 9 to 19 (small to trivial differences = −0.31 to −0.04 m·s⁻¹, P = .12–.99) and 6 to 19 (small differences = −0.4 to −0.28 m·s⁻², P = .06–.79) events, and the slopes were no longer different with 1 to 19 events (trivial differences = 0.06–0.03 s⁻¹, P = .35–.99). Conclusions: AS profiles can be estimated from a minimum of 9 days of tracking data. Future research should investigate methodology resulting in AS profiles estimated from fewer events.

Purpose: Ice hockey is a team invasion sport characterized by repeated high-intensity skating efforts, technical and tactical skill, physical contact, and collisions requiring considerable levels of muscular strength. The purpose of this study was to evaluate the relationships between lower-body vertical force–time metrics and skating qualities in subelite female ice hockey players. Methods: A cross-sectional cohort design was employed utilizing 14 athletes (body mass = 66.7 [1.8] kg; height = 171.6 [6.2] cm; age = 21.1 [1.7] y). The relationships between metrics of lower-body strength collected from a drop jump, squat jump, countermovement jump, loaded countermovement jump, and an isometric squat and 4 skating qualities collected from a linear sprint, repeated sprint test, and a multistage aerobic test were evaluated. Results: The regression models revealed a positive relationship between relative peak force in the isometric squat and skating multistage aerobic test performance (r ² = .388; P = .017) and a positive relationship between repeated-sprint ability and eccentric mean force during the loaded countermovement jump (r ² = .595; P = .001). No significant relationships were observed between strength metrics and skating acceleration or maximal velocity. Conclusions: These data suggest that skating ability is most affected by relative isometric strength in female ice hockey players. It is recommended that practitioners focus training on tasks that improve relative force output. It is also recommended that isometric relative peak force be used as a monitoring metric for this cohort.

Purpose: To verify whether training the iron cross (IC) with assistive devices (herdos; H_IC) and added external load (LH_IC) to equate the moments of force developed on the rings could be considered an intermediate step between the nonoverloaded herdos situation (H_IC) and the IC performed on the rings. Methods: Relative levels of surface electromyography (sEMG) activity were normalized with respect to a standing IC before comparing gymnasts who can perform the IC on the rings (achievers) and gymnast who cannot (nonachievers) in the 2 herdos conditions (H_IC and LH_IC). Seven muscles were chosen for sEMG analysis, namely, pectoralis major (PM), latissimus dorsi, teres major, lower trapezius, serratus anterior, biceps brachii (BB), and triceps brachii. Additionally, 3 indices were calculated to measure levels of coactivation: Elbow_idx, Scapula_idx, and Shoulder_idx. Results: The bigger magnitude of differences in sEMG activity among situations was found for the PM and BB (F ≥ 30.7; P < .001). When comparing the global and the PM, teres major, BB, and triceps brachii activity across groups, nonachievers activated their musculature to a greater extent than the achievers independently of the herdos situation (P ≤ .046). Achievers’ Elbow_idx was the only index that was significantly higher (P ≤ .005) in the IC in comparison to LH_IC and H_IC. Conclusion: sEMG activity of PM and BB was particularly sensitive between situations, independently of the level of achievement. We recommend training the IC by adding external load in the herdos situation to increase muscle activity to levels closer to the rings situation but avoiding the potential factor of injuries.

Purpose: Advanced footwear technology is prevalent in distance running, with research focusing on these “super shoes” in competitive athletes, with less understanding of their value for slower runners. The aim of this study was to compare physiological and biomechanical variables between a model of super shoes (Saucony Endorphin Speed 2) and regular running shoes (Saucony Cohesion 13) in recreational athletes. Methods: We measured peak oxygen uptake (VO₂peak) in 10 runners before testing each subject 4 times in a randomly ordered crossover design (ie, Endorphin shoe or Cohesion shoe, running at 65% or 80% of velocity at VO₂peak [vVO₂peak]). We recorded video data using a high-speed camera (300 Hz) to calculate vertical and leg stiffnesses. Results: 65% vVO₂peak was equivalent to a speed of 9.4 km·h⁻¹ (0.4), whereas 80% vVO₂peak was equivalent to 11.5 km·h⁻¹ (0.5). Two-way mixed-design analysis of variance showed that oxygen consumption in the Endorphin shoe was 3.9% lower than in the Cohesion shoe at 65% vVO₂peak, with an interaction between shoes and speed (P = .020) meaning an increased difference of 5.0% at 80% vVO₂peak. There were small increases in vertical and leg stiffnesses in the Endorphin shoes (P < .001); the Endorphin shoe condition also showed trivial to moderate differences in step length, step rate, contact time, and flight time (P < .001). Conclusions: There was a physiological benefit to running in the super shoes even at the slower speed. There were also spatiotemporal and global stiffness improvements indicating that recreational runners benefit from wearing super shoes.

Purpose: The study examined the longitudinal interplay of anthropometric, metabolic, and neuromuscular development related to performance in adolescent national-level swimmers over 12 months. Methods: Seven male and 12 female swimmers (14.8 [1.3] y, FINA [International Swimming Federation] points 716 [51]) were tested before (T0) and after the preparation period (T1), at the season’s peak (T2), and before the next season (T3). Anthropometric (eg, fat percentage) and neuromuscular parameters (squat and bench-press load-velocity profile) were assessed on dry land. Metabolic (cost of swimming [C], maximal oxygen uptake [ $\dot{\mathrm{V}}{\mathrm{O}}_2\text{peak}$ ], and peak blood lactate [bLa_peak]) and performance (sprinting speed [v _sprint] and lactate thresholds [LT1 and 2]) factors were determined using a 500-m submaximal, 200-m all-out, 20-second sprint, and incremental test (+0.03 m·s⁻¹, 3 min), respectively, in front-crawl swimming. Results: v _sprint (+0.6%) and LT1 and 2 (+1.9–2.4%) increased trivially and slightly, respectively, from T0 to T2 following small to moderate strength increases (≥+10.2%) from T0 to T1 and $\dot{\mathrm{V}}{\mathrm{O}}_2\text{peak}$ (+6.0%) from T1 to T2. Bench-press maximal strength and peak power correlated with v _sprint from T0 to T2 (r ≥ .54, P < .05) and LT2 at T1 (r ≥ .47, P < .05). Changes in fat percentage and $\dot{\mathrm{V}}{\mathrm{O}}_2\text{peak}$ (T2–T1 and T3–T2, r ≤ −.67, P < .01) and C and LT2 (T2–T0, r = −.52, P = .047) were also correlated. Conclusions: Increases in strength and $\dot{\mathrm{V}}{\mathrm{O}}_2\text{peak}$ from preparation to the competition period resulted in improved sprint and endurance performance. Across the season, upper-body strength was associated with v _sprint and LT2, although their changes were unrelated.