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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. [ABSTRACT FROM AUTHOR]

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 (r2 =.388; P =.017) and a positive relationship between repeated-sprint ability and eccentric mean force during the loaded countermovement jump (r2 =.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. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this research was to investigate the relationship between horizontal jump distance, 10 m time, and 30–40 m time in multi-sport athletes separated by sex and sprint speed. Methods: A total of 1352 athletes (742 males and 610 females) performed 40 m sprints, standing broad jumps (SBJs), and standing triple jumps (STJs). Data were separated by sex and then grouped as fast, average, and slow using the K-Means algorithm in three conditions (acceleration, max speed, and combined). Results: Regression models explained 84.01% of the variance (F(7,757) = 574.5, p < 0.001) for the 10 m times with mass, speed group, and sex as significant predictors and 88.51% of the variance (F = (7,757 = 841.6, p < 0.001) for the 30–40 m times with SBJ, STJ, speed group, sex, and the interaction of sex and group as significant predictors. Conclusions: These results suggest that when examining general athlete physical performance, horizontal jump tests and max speed sprint times can be used equivalently to stratify athletes. However, it is important to group athletes by speed and sex before being able to predict sprint ability from horizontal jump tests. Further, athlete mass is a significant factor in the prediction of acceleration ability but not maximum speed, and horizontal jumps were significant factors in the prediction of max speed but not acceleration. [ABSTRACT FROM AUTHOR]

Background: The critical power model (CPM) is used extensively in sports to characterize fitness by estimating anaerobic work capacity (W') and critical power (CP). Traditionally, estimates of CP and W' require repeated, time-consuming tests. Alternatively, a 3 min all-out test yields good estimates of W' and CP. However, adoption of the 3 min protocol for regular fitness monitoring is deterred by the mentally/physically strenuous nature of the test. Objective: We propose to examine an alternative single-session testing protocol that can accurately estimate critical power model parameters. Methods: Twenty-eight healthy competitive athletes (cyclists or triathletes) (mean ± SD: age: 38.5 ± 10.4 years, height: 177.9 ± 8.6 cm, mass: 73.4 ± 9.9 kg) participated in 5 sessions on a Lode cycle ergometer in isokinetic mode within a 2-week period. A 3 min all-out test (3MT) was conducted on the first visit to determine CPM parameters from which power outputs for 4 subsequent constant-power plus all-out tests (CPT) were selected to result in exhaustion in 1–10 min. The subjects were to maintain the prescribed power output as consistently as possible at their preferred race cadence. Once the power output could no longer be maintained for more than 10 s, the subjects were instructed to produce an all-out effort. Tests were terminated after power output fell to an asymptote which was sustained for 2 min. Results: The CPM parameters for all of the CPT durations were compared to the traditional CP protocol (significant parameter differences were identified for all CPT durations) and the 3MT (only CPT durations > 3 min were different [3–6 min test, p < 0.01; >6 min test, p < 0.01]). CPT does not estimate traditional CP and W' parameters well. However, the CPT with a duration < 3 min accurately estimates both parameters of a 3MT. Conclusion: Therefore, CPT has the capacity to serve as an alternative tool to assess CP parameters. [ABSTRACT FROM AUTHOR]

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 (Pmax, F0, V0, FVslope, 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. [ABSTRACT FROM AUTHOR]

The Critical Power Model (CPM) is key for assessing athletes' aerobic and anaerobic energy systems but typically involves lengthy, exhausting protocols. The 3 min all-out test (3MT) simplifies CPM assessment, yet its duration remains demanding. Exponential decay models, specifically mono- and bi-exponential functions, offer a more efficient alternative by accurately capturing the nonlinear energy dynamics in high-intensity efforts. This study explores shortening the 3MT using these functions to reduce athlete strain while preserving the accuracy of critical power (CP) and work capacity ( W ′ ) estimates. Seventy-six competitive cyclists and triathletes completed a 3MT on a cycle ergometer, with CP and W ′ calculated at shorter intervals. Results showed that a 90 s test using the bi-exponential model yielded CP and W ′ values similar to those of the full 3MT. Meanwhile, the mono-exponential model required at least 135 s. Bland–Altman and linear regression analyses confirmed that a 120 s test with the mono-exponential model reliably estimated CP and W ′ with minimal physical strain. These findings support a shortened, less-demanding 3MT as a valid alternative for CPM assessment. [ABSTRACT FROM AUTHOR]

To evaluate if takeoff speed can be predicted using peak-speed from a linear position transducer (LPT), 21 rowing athletes performed hexagonal-bar jumps in line with the National Team testing protocol. Predictive validity was assessed by comparing peak-speed from a LPT to the criterion measure takeoff speed collected from force plates. The relationship between peak-speed and takeoff speed was: Takeoff Speed = 1.21[dot]PeakSpeed-0.68, and the correlation was statistically significant (r= 0.990, p < 0.05). The Bland-Altman plot indicated that the 95% limits of agreement ranged from -0.130 m[dot]s[superscript -1] to 0.125 m[dot]s[superscript -1], with points above and below the zero line, suggesting there is no systematic bias. The mean difference in speed was 0.18%. This research shows that takeoff speed can be accurately predicted from peak-speed using a LPT. This allows practitioners to quickly and accurately estimate jump height when accessibility and portability of testing equipment are limiting factors in the field.

The use of session rating of perceived exertion (sRPE) as a measure of workload is a popular athlete load monitoring tool. However, the nature of sRPE means the contribution of salient, sport-specific factors to athlete load in field sports is challenging to isolate and quantify. In rugby sevens, drivers of load include high-speed running and physical contact. In soccer and men's rugby, union acceleration/deceleration also influences load. These metrics are evaluated using data from global navigation satellite system (GNSS) sensors worn by athletes. Research suggests that sensor data methods for identifying load in men's rugby do not accurately quantify female athlete loads. This investigation examined how mass, contact, and accelerations and decelerations at different speeds contribute to load in women's rugby sevens. The study evaluated 99 international matches, using data from 19 full-time athletes. GNSS measures, RPE, athlete mass, and contact count were evaluated using a linear mixed-model regression. The model demonstrated significant effects for low decelerations at low and high speeds, mass, distance, and contact count explaining 48.7% of the global variance of sRPE. The use of acceleration/deceleration and speed from GNSS sensors alongside mass, as well as contact count, presents a novel approach to quantifying load. [ABSTRACT FROM AUTHOR]

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 AdMosTM 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 AdMosTM-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. [ABSTRACT FROM AUTHOR]

The early detection and treatment of Helicobacter pylori infections can help prevent the formation of ulcers and development of gastric cancer in humans. The urea breath test (UBT) is a noninvasive test for diagnosing H. pylori. However, isotopic‐labeled UBT reagents are expensive and require specialized test equipment to detect isotopic CO2. In this study, the development of a user‐friendly, cost‐effective, and alternative method for diagnosing H. pylori infections by detecting NH3 in exhaled breath is reported. A commercial disposable pH strip is modified with sodium carboxymethylcellulose to enhance its performance in gaseous environments. The modified pH strip exhibits compatibility with both acidic (HCl and CH3COOH) and alkaline (NH3) gases. Furthermore, the sensor monitors the production of NH3 resulting from fish spoilage for 72 h, highlighting its real‐time capabilities. The feasibility of employing this simple strip sensor to detect H. pylori infection in patients is investigated through in vitro experiments and preliminary clinical studies. The simple strip sensor is a promising alternative to the C‐13 UBT for detecting H. pylori infection. [ABSTRACT FROM AUTHOR]