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Yetsa A. Tuakli-Wosornu, Xiang Li, Kimberly E. Ona Ayala, Yinfei Wu, Michael Amick, and David B. Frumberg

It is known that high-performance sprinters with unilateral and bilateral prosthetic lower limbs run at different speeds using different spatiotemporal strategies. Historically, these athletes still competed together in the same races, but 2018 classification rule revisions saw the separation of these two groups. This study sought to compare Paralympic sprint performance between all-comer (i.e., transfemoral and transtibial) unilateral and bilateral amputee sprinters using a large athlete sample. A retrospective analysis of race speed among Paralympic sprinters between 1996 and 2016 was conducted. In total, 584 published race results from 161 sprinters revealed that unilateral and bilateral lower-extremity amputee sprinters had significantly different race speeds in all three race finals (100 m, p value <.001; 200 m, <.001; 400 m, <.001). All-comer bilateral amputee runners ran faster than their unilateral counterparts; performance differences increased with race distance. These data support current classification criteria in amputee sprinting, which may create more equal competitive fields in the future.

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Joffrey Drigny, Marine Rolland, Robin Pla, Christophe Chesneau, Tess Lebreton, Benjamin Marais, Pierre Outin, Sébastien Moussay, Sébastien Racinais, and Benoit Mauvieux

Purpose: To measure core temperature (T core) in open-water (OW) swimmers during a 25-km competition and identify the predictors of T core drop and hypothermia-related dropouts. Methods: Twenty-four national- and international-level OW swimmers participated in the study. Participants completed a personal questionnaire and a body fat/muscle mass assessment before the race. The average speed was calculated on each lap over a 2500-m course. T core was continuously recorded via an ingestible temperature sensor (e-Celsius, BodyCap). Hypothermia-related dropouts (H group) were compared with finishers (nH group). Results: Average prerace T core was 37.5°C (0.3°C) (N = 21). 7 participants dropped out due to hypothermia (H, n = 7) with a mean T core at dropout of 35.3°C (1.5°C). Multiple logistic regression analysis found that body fat percentage and initial T core were associated with hypothermia (G 2 = 17.26, P < .001). Early T core drop ≤37.1°C at 2500 m was associated with a greater rate of hypothermia-related dropouts (71.4% vs 14.3%, P = .017). Multiple linear regression found that body fat percentage and previous participation were associated with T core drop (F = 4.95, P = .019). There was a positive correlation between the decrease in speed and T core drop (r = .462, P < .001). Conclusions: During an OW 25-km competition at 20°C to 21°C, lower initial T core and lower body fat, as well as premature T core drop, were associated with an increased risk of hypothermia-related dropout. Lower body fat and no previous participation, as well as decrease in swimming speed, were associated with T core drop.

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Paul Ritsche, Thomas Bernhard, Ralf Roth, Eric Lichtenstein, Martin Keller, Sabrina Zingg, Martino V. Franchi, and Oliver Faude

Purpose: Hamstring muscle architecture may be associated with sprint performance and the risk of sustaining a muscle injury, both of which increase during puberty. In this study, we investigated the m. biceps femoris long head (BFlh) cross-sectional area (ACSA), fascicle length (FL) and pennation angle (PA), and sprint performance as well as their relationship in under 13 to 15 youth soccer players. Methods: We measured 85 players in under-13 (n = 29, age = 12.5 [0.1] y, height = 155.3 [6.2] cm, weight = 43.9 [7.6] kg), under-14 (n = 25, age = 13.5 [0.3] y, height = 160.6 [7.7] cm, weight = 47.0 [6.8] kg), and under-15 (n = 31, age = 14.4 [0.3] y, height = 170.0 [7.7] cm, weight = 58.1 [8.8] kg) teams. We used ultrasound to measure BFlh ACSA, FL and PA, and sprint tests to assess 10- and 30-m sprint time, maximal velocity  (v max), and maximal acceleration (α max). We calculated Pearson r to assess the relationship between sprint ability and architectural parameters. Results: All muscle architectural parameters increased from the under-13 to the under-15 age group (BFlh ACSA = 37%, BFlh FL = 11%, BFlh PA = 8%). All sprint performance parameters improved from the under-13 to under-15 age categories (30-m time = 7%, 10-m time = 4%, v max = 9%, α max = 7%). The BFlh ACSA was correlated with 30-m sprint time (r = −.61 (95% compatibility interval [CI] [−.73, −.45]) and v max (r = .61, 95% CI [.45, .72]). A combination of BFlh ACSA and age best predicted 30-m time (R² = .47 [.33, .62]) and 10-m time (R² = .23 [.08, .38]). Conclusions: Muscle architectural as well as sprint performance parameters increase from the under-13 to under-15 age groups. Even though we found correlations for all assessed architectural parameters, BFlh ACSA was best related to the assessed sprint parameters.

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Iván Peña-González, José M. Sarabia, Alba Roldan, Agustín Manresa-Rocamora, and Manuel Moya-Ramón

In regular football, the players’ selection process involves an objective assessment based on their anthropometric and physical performance. However, available literature focused on players’ selection process in cerebral palsy (CP) football is scarce. Purpose: To describe the anthropometrical and physical performance profiles of the International Spanish CP footballers and to compare them with the remaining CP football players from the national competition. Method: A total of 75 CP football players from the Spanish CP Football National Competition (classified into the 3 existing classes: football class [FT] 1 = 38; FT2 = 29; FT3 = 8) participated in the study. Participants were divided into 2 groups: selected players (n = 15) and nonselected players (n = 60) for the national team. Anthropometrical data and physical performance (countermovement jump, 20-m sprint, modified agility T-test [MAT], and dribbling test) were collected. Results: There were significant differences in the 20-m sprint, MAT, and dribbling for the total sample and in MAT and dribbling for FT2 and FT3 classes between selected players and nonselected players (P < .05), but there were no differences for FT1. The MAT and dribbling showed a positive correlation and a high percentage of player selection prediction. Conclusion: Change-of-direction ability (ie, MAT) and dribbling skills are important when performing the selection process, as they allow the evaluation of important aspects of the game, but they may also provide the technical staff with an idea of the functionality and the physical performance of the players in each sport class.

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José María González-Ravé, Francisco Hermosilla, Fernando González-Mohíno, Arturo Casado, and David B. Pyne

A well-planned periodized approach allows swimmers to achieve peak performance at the major national and international competitions. Purpose: To identify the main characteristics of endurance training for highly trained swimmers described by the training intensity distribution (TID), volume, and periodization models. Methods: The electronic databases Scopus, PubMed, and Web of Science were searched using a comprehensive list of relevant terms. Studies that investigated the effect of the periodization of training in swimming, with the training load (volume, TID) and periodization reported, were included in the systematic review. Results: A total of 3487 studies were identified, and after removal of duplicates and elimination of papers based on title and abstract screening, 17 articles remained.  A further 8 articles were excluded after full text review, leaving a final total of 9 studies in the systematic review. The evidence levels were 1b for intervention studies (n = 3) and 2b for (observational) retrospective studies (n = 6). The sprint swimmers typically followed a polarized and threshold TID, the middle-distance swimmers followed a threshold and pyramidal TID, and the long-distance swimmers primarily followed a pyramidal TID. The periodization model identified in the majority of studies selected is characterized by wave-like cycles in units like mesocycles to promote physiological adaptations and skill acquisition. Conclusions: Highly trained swimmers follow a training volume and TID based on their primary event. There is a need for further experimental studies on the effects of block and reverse periodization models on swimming performance. Although observational studies of training have limited evidence, it is unclear whether a different training/periodization approach would yield better results.

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S. Sofie Lövdal, Ruud J.R. Den Hartigh, and George Azzopardi

Purpose: Staying injury free is a major factor for success in sports. Although injuries are difficult to forecast, novel technologies and data-science applications could provide important insights. Our purpose was to use machine learning for the prediction of injuries in runners, based on detailed training logs. Methods: Prediction of injuries was evaluated on a new data set of 74 high-level middle- and long-distance runners, over a period of 7 years. Two analytic approaches were applied. First, the training load from the previous 7 days was expressed as a time series, with each day’s training being described by 10 features. These features were a combination of objective data from a global positioning system watch (eg, duration, distance), together with subjective data about the exertion and success of the training. Second, a training week was summarized by 22 aggregate features, and a time window of 3 weeks before the injury was considered. Results: A predictive system based on bagged XGBoost machine-learning models resulted in receiver operating characteristic curves with average areas under the curves of 0.724 and 0.678 for the day and week approaches, respectively. The results of the day approach especially reflect a reasonably high probability that our system makes correct injury predictions. Conclusions: Our machine-learning-based approach predicts a sizable portion of the injuries, in particular when the model is based on training-load data in the days preceding an injury. Overall, these results demonstrate the possible merits of using machine learning to predict injuries and tailor training programs for athletes.

Open access

Stephen S. Cheung