Suchergebnisse - Data

Terada, M., Taniyama, D., Isaka, T. “… Background The retrospective studies have reported altered spinal reflex excitability of the lower leg muscles in patients with acute lateral ankle sprain (LAS); however, these authors relied on data without a pre-injury assessment. Prospective examination of the longitudinal changes in neural excitability from pre-injury characteristics would provide a more comprehensive view of the underlying neuromuscular impairments.  …”

Russell, J. L., McLean, B. D., Stolp, S., Strack, D., Coutts, A. J. “… This study examined the impact of on-court training load and travel demands on AROM responses and individual in-game performance among 14 NBA players. Data included training load, travel-related variables (elevation, time zone changes, nights away), AROMs and game performance metrics.  …”

D. Memmert “… Durch die Integration von Big Data können Spielergebnisse, Fitnessparameter und individuelle Leistungen eingehend analysiert werden, was zu neuen Entwicklungen in der Forschung führt.  …”

Chatham, L. S., Young, T. S., Wojcik, R. M., Bell, L. A., Torbati, A. H., Carpenter, R. D., Jenkins, P. E., Poddar, S. K., Yakacki, C. M. “… Impact tests were performed following the NFL testing protocol on four prominent football helmets. The resulting data was used to determine Head Acceleration Response Metric (HARM), Diffuse Axonal Multi-Axis General Evaluation (DAMAGE), and Head Injury Criterion (HIC).  …”

Howarth, H., Evans, G., Kruger, P., Dilkes, E., Bell, G., Kipps, C. “… The study was cross-sectional in design. Data was collected using a battery of psychometric tests yielding information on distress (The Distress Screener), anxiety and depression (PHQ-9, K10), sleep disturbance (PROMIS scale), alcohol consumption (AUDIT-C), smoking behaviour, adverse nutrition behaviour, career satisfaction (Career Satisfaction Scale) and mental toughness (Mental Toughness Index).  …”

Foster, J. M., Gerardo, R. T., Brennan, S. N., Molnar, T. J., Tran, R., Sottile, C. B., Geppert, K. S., Egiazarian, M., Ballhagen, A. F., Pennell, A., Tan, R. “… Peak and mean power and velocity, and the within- and between-day coefficient of variation (CV%), were measured using a linear transducer during barbell squats and bench press performed at 55% one-repetition maximum (1RM), 60%1RM, and 65%1RM. RESULTS: Pilot data have been collected (n=4). All CV% data for peak power, mean power, peak velocity, and mean velocity were <20% and thus, indicate that our methodology are acceptable to proceed with data collection.  …”

Parmley, J., Weaving, D., Whitehead, S., Tooby, J., Owen, C., Sawczuk, T., Roe, G., Collins, N., Phillips, G., Vishnubala, D., Stokes, K., Hudson, S., Jones, B. “… This study aimed to describe the incidence of head acceleration events (HAEs) during pitch-based in-season training and matches in professional male rugby league. Data were recorded using instrumented mouthguards from 108 players (70 forwards and 38 backs) at nine Super League teams (2024 season), resulting in 468 player-training sessions and 665 player-matches included.  …”

Zhu, H., Wen, Y. “… The data analysis included repeated measures ANOVA, mediation effect testing, and machine learning models.  …”

Haugen, T., Bucher Sandbakk, S., Sandbakk, Ø., Tønnessen, E. “… Methods: An intrinsic case study design was used to capture the quantitative and qualitative aspects related to the training and development process. We used a three-step data collection process and pragmatic analyses of (1) training logs/plans and performance statistics, (2) in-depth semi-structured interviews with three of the player's coaches, and her mother, and (3) systematic quality assurance through interviews to clarify, expand and validate preliminary findings with all informants followed by negotiation among researchers and all key informants, including the player.  …”

Lundstrom, E. A., De Souza, M. J., Conklin, M. E., Williams, N. I. “… In 26 elite male (n = 10) and female (n = 16) collegiate swimmers, we assessed sleep quality (sleep duration (hrs), sleep debt (hrs), slow-wave sleep (SWShrs and SWS%), rapid-eye movement (REMhrs and REM%)), training measures (strain (AU), average heart rate (HR) (ExHRavg) and maximum exercising HR (ExHRmax)), and swimming performance (200yd time trial swim) during heavy training, preceding championship competition. Collection of sleep data was matched to days of training data collection, and also to the day preceding the performance swim.  …”

Flórez-Gil, E., Boullosa, D., Calleja-González, J., Vaquera, A. “… The survey explored various aspects of warm-up routines, including objectives, components, duration, methods, and equipment used. Data were stratified by team gender and competition level.  …”

Karadenizli, Z. I., Ilbak, I., Bartik, P. “… A total of 44 athletes (22 football players and 22 handball players) participated in this cross-sectional comparative study. Anthropometric data included height (cm), body weight (kg), and body mass index (BMI, kg/m²).  …”

Snoussia, H., Dergaaa, I., Ghouilic, H., Ceyland, H. I., Stefanicae, V., Muntean, R.-I., Hawania, A., Abdellaouia, S., Guelmamic, N., Khalifaa, R., Abderrahman, A. B. “… Assessment included validated scales for collaborative learning engagement, self-efficacy, tactical skills acquisition, and perceived training value. Data were analysed using repeated measures ANOVA with effect sizes calculated.  …”

de la Rubia, A., García-Sánchez, C., Marquina, M., Martín-Castellanos, A., Lino-Samaniego, Á., Tannion, K. “… Equipment and methods The sample consisted of 87 handball players (46 boys and 41 girls) aged 13-17 years. Anthropometric data (height, body mass and self-reported biological parent's height) were collected to calculate maturity level using the percentage of predicted adult height (Khamis-Roche equation).  …”

Ren, X., Boisbluche, S., Philippe, K., Demy, M., Äyrämö, S., Rautiainen, I., Ding, S., Prioux, J. “… Although injuries are challenging to predict, new technologies and the application of data science can provide valuable insights. This study aimed to predict injury risk among professional rugby union players using machine learning (ML) models.  …”

Bayrak, A., Enli, M. “… Background This study aims to determine the injury incidence among male and female athletes in the Turkish Handball Super League and to examine the most common types, mechanisms, and risk factors of injuries. Methods Data were collected through medical records and self-reported questionnaires from 160 handball Super League players (82 females, 78 males).  …”

Degenhardt, H., Hinz, M., Rupp, M.-C., Kleim, B. D., Vieider, R. P., Weyer, M., Henze, A.-S., Imhoff, A. B., Siebenlist, S., Ehmann, Y. J. “… Demographics, activity level and data on acute and overuse injuries over the past five years were collected.  …”

Jia, Y., Zhou, X., Tang, Y., Li, Q., Wang, J., Fu, Q. “… Study Sample: A VR system with 100 task scenarios was used to assess decision-making performance and visual behavior. 30 high-level and 30 low-level players participated in two phases. Data Collection and Analysis: In Phase 1, a panel of basketball experts (N = 3) rated the decision-making scenarios.  …”

Stojanovic, E., Scanlan, A. T., Radovanovic, D., Jakovljevic, V., Živkovic, V., Faude, O., Fox, J., Raasch, K., Ferrauti, A. “… Results: Following screening, 22 studies (15 reporting mechanism data, 21 reporting body location data, and 17 reporting type data) were included in the systematic review and meta-analysis.  …”

Badenhorst, M., Romanchuk, J., Salmon, D., Brown, J. C., Hendricks, S., Walters, S. “… Reflexive thematic analysis was used to analyse the data. Results: Three themes were developed from the data.  …”