Background: Para-sports such as wheelchair rugby have seen increased use of inertial measurement units (IMU) to measure wheelchair mobility. The accessibility and accuracy of IMUs have enabled the quantification of many wheelchair metrics and the ability to further advance analyses such as force-velocity (FV) profiling. However, the FV modeling approach has not been refined to include wheelchair specific parameters. Purpose: The purpose of this study was to compare wheelchair rugby sprint FV profiles, developed from a wheel-mounted IMU, using current mono-exponential modeling techniques against a dynamic resistive force model with wheelchair specific resistance coefficients. Methods: Eighteen athletes from a national wheelchair rugby program performed 2 × 45 m all-out sprints on an indoor hardwood court surface. Results: Velocity modelling displayed high agreeability, with an average RMSE of 0.235 ± 0.07 m/s⁻¹ and r² of 0.946 ± 0.02. Further, the wheelchair specific resistive force model resulted in greater force and power outcomes, better aligning with previously collected measures. Conclusions: The present study highlights the proof of concept that a wheel-mounted IMU combined with wheelchair-specific FV modelling provided estimates of force and power that better account for the resistive forces encountered by wheelchair rugby athletes.

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.

Boat acceleration profiles can provide valuable information for coaches and practitioners to make meaningful technical interventions and monitor the determinants of success in rowing. Previous studies have used simple feature detection methods to identify key phases within individual strokes, such as drive onset, drive time, drive offset and stroke time. However, based on skill level, technique or boat class, the hull acceleration profile can differ, making robust feature detection more challenging. The current study’s purpose is to employ the undecimated wavelet transform (UWT) technique to detect individual features in the stroke acceleration profile from a single rowing hull-mounted accelerometer. In this investigation, the temporal and kinematic values obtained using the AdMos^TM sensor in conjunction with the UWT processing approach were strongly correlated with the comparative measures of the Peach™ instrumented oarlock system. The measures for stroke time displayed very strong agreeability between the systems for all boat classes, with ICC values of 0.993, 0.963 and 0.954 for the W8+, W4− and W1x boats, respectively. Similarly, the drive time was also very consistent, with strong to very strong agreeability, producing ICC values of 0.937, 0.901 and 0.881 for the W8+, W4− and W1x boat classes. Further, a Bland–Altman analysis displayed little to no bias between the AdMos^TM-derived and Peach™ measures, indicating that there were no systematic discrepancies between signals. This single-sensor solution could form the basis for a simple, cost-effective and accessible alternative to multi-sensor instrumented systems for the determination of sub-stroke kinematic phases.

Background: Accurate linear sprint modelling is essential for evaluating athletes’ performance, particularly in terms of force, power, and velocity capabilities. Radar sensors have emerged as a critical tool in capturing precise velocity data, which is fundamental for generating reliable force-velocity (FV) profiles. This study focuses on the fitting of radar sensor data to various sprint modelling techniques to enhance the accuracy of these profiles. Forty-seven university-level athletes (M = 23, F = 24; 1.75 ± 0.1 m; 79.55 ± 12.64 kg) participated in two 40 m sprint trials, with radar sensors collecting detailed velocity measurements. This study evaluated five different modelling approaches, including three established methods, a third-degree polynomial, and a sigmoid function, assessing their goodness-of-fit through the root mean square error (RMSE) and coefficient of determination (r²). Additionally, FV metrics (P_max, F₀, V₀, FV_slope, and DRF) were calculated and compared using ANOVA. Results: Significant differences (p < 0.001) were identified across the models in terms of goodness-of-fit and most FV metrics, with the sigmoid and polynomial functions demonstrating superior fit to the radar-collected velocity data. Conclusions: The results suggest that radar sensors, combined with appropriate modelling techniques, can significantly improve the accuracy of sprint performance analysis, offering valuable insights for both researchers and coaches. Care should be taken when comparing results across studies employing different modelling approaches, as variations in model fitting can impact the derived metrics.

Horizontal force–velocity profiling (FV) has become a prominent approach to evaluate sprinting performance and force/power characteristics in athletes. As optical timing gates (TGs) are the most prevalent and accessible athlete sprint testing measurement devices, initial FV applications involved measuring sprint performance using TGs placed at the 0.75, 10, 15, 20, 30, and 40 m marks during all-out sprint testing sessions. However, there was uncertainty as to the standardization in the number, placement, and total distance of TG measurements to determine FV outputs. While original investigations have attempted to determine optimal TG measurement configurations, they have not been compared to continuous velocity measurements, nor have they been subject to a statistical optimization approach. Therefore, the objective of this study is to use simulated TG locations, derived from continuous GNSS velocity measurements, to identify the shortest distance with the minimum number of optimal timing-gate locations to obtain accurate estimates of FV metrics. A total of 49 elite women’s rugby sevens athletes performed 40 m sprint tests between 2015 and 2020. Data were collected using GNSS units (STATSports, Ireland), with athlete split times extracted every 2.5 m interval for the first 10 m, and every 5 m for the remainder of the sprint to simulate timing gates. FV metrics and times generated for all the combinations were compared to the standard model and GNSS models, respectively, using a one-way repeated measures analysis of variance (ANOVA) model. The shortest distance with an average percentage difference 0.27% (RMSE 1.43) for the standard model and 0.43% (RMSE 0.08) for the GNSS models were [0.75, 10-15-25] and [0.75, 5-10-30] combinations, respectively, across all FV measures. For individual FV metrics, different combinations can provide better estimations, indicating that certain regions of the sprint are required for the determination of specific metrics. Within this cohort, the best TG combinations for linear sprint testing are 10 to 15 m shorter than the current suggested combination, using three fewer gates. Further, alternative combinations may offer greater accuracy for specific FV metrics. This work provides an approach for the determination of the most accurate TG locations for teams with constraints on time, money, and equipment.

Cormier, P, Mavignier, B, Geneau, D, and Werle, C. The physical match running demands of Canadian international women’s soccer. J Strength Cond Res XX(X): 000–000, 2026—This study examined position-specific match running demands across youth to senior Canadian female national team soccer players to establish normative data to inform physical performance preparation. External load match running data were collected via Catapult global navigation satellite sensors from 88 outfield players participating in the women's national team pathway (under 17, under 20, and senior levels [WNTU17, WNTU20, and WNT, respectively]). Linear mixed models (level × position) were performed to investigate position-specific differences between international pathway levels. Concerning center backs, WNT players covered greater total distance and distance·min ⁻¹ than WNTU20 and greater distance·min ⁻¹ than WNTU17 players, and greater high deceleration efforts than WNTU17 and WNTU20 levels (effect size [ES] = 1.12–1.90, p ≤ 0.02). Regarding fullbacks, WNTU17 players performed fewer high accelerations and decelerations (total efforts and efforts·min ⁻¹ ) than WNT players (ES = 1.03–2.59, p ≤ 0.04). For forwards, WNTU17 players displayed lower maximum velocity expression (ES = 1.00, p = 0.04) than WNT. Concerning, midfielders, both WNTU17 and WNTU20 players performed lower distance·min ⁻¹ , high-intensity running distance and m·min ⁻¹ , high-speed running distance and m·min ⁻¹ , and maximum velocity than WNT players. In addition, WNTU20 had lower sprint distance and m·min ⁻¹ , high-intensity acceleration·min ⁻¹ , and deceleration efforts (ES = 0.76–2.44, p ≤ 0.03) than WNT players. These results highlight key differences between national team pathway levels. Finally, these data highlight areas to target in the physical preparation of youth international players for the demands of top-level soccer.