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Cloe Cummins, Blake McLean, Mark Halaki and Rhonda Orr

Purpose:

To quantify the external training loads of positional groups in preseason training drills.

Methods:

Thirty-three elite rugby league players were categorized into 1 of 4 positional groups: outside backs (n = 9), adjustables (n = 9), wide-running forwards (n = 9), and hit-up forwards (n = 6). Data for 8 preseason weeks were collected using microtechnology devices. Training drills were classified based on drill focus: speed and agility, conditioning, and generic and positional skills.

Results:

Total, high-speed, and very-high-speed distance decreased across the preseason in speed and agility (moderate, small, and small, respectively), conditioning (large, large, and small) and generic skills (large, large, and large). The duration of speed and generic skills also decreased (77% and 48%, respectively). This was matched by a concomitant increase in total distance (small), high-speed running (small), very-high-speed running (moderate), and 2-dimensional (2D) BodyLoad (small) demands in positional skills. In positional skills, hit-up forwards (1240 ± 386 m) completed less very-high-speed running than outside backs (2570 ± 1331 m) and adjustables (2121 ± 1163 m). Hit-up forwards (674 ± 253 AU) experienced greater 2D BodyLoad demands than outside backs (432 ± 230 AU, P = .034). In positional drills, hit-up forwards experienced greater relative 2D BodyLoad demands than outside backs (P = .015). Conversely, outside backs experienced greater relative high- (P = .007) and very-high-speed-running (P < .001) demands than hit-up forwards.

Conclusion:

Significant differences were observed in training loads between positional groups during positional skills but not in speed and agility, conditioning, and generic skills. This work also highlights the importance of different external-load parameters to adequately quantify workload across different positional groups.

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Ricardo Pires, Thays Falcari, Alexandre B. Campo, Bárbara C. Pulcineli, Joseph Hamill and Ulysses Fernandes Ervilha

signals in the different conditions. A machine-learning algorithm may be able to relate EMG signals to running conditions using a known set of EMG data (training phase) and to deduce what is the running condition when a new set of EMG data is presented to the machine (classification phase). A support

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Robyn Lubisco, Genevieve F.E. Birren and Ryan Vooris

updated them for the 2017–2018 academic year. The purpose of this study was to examine sport management faculty job postings to determine the type of positions available, the qualities of those positions such as tenure and title, and the Carnegie classification of the institution advertising the

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Anna Bjerkefors, Johanna S. Rosén, Olga Tarassova and Anton Arndt

different classification groups depending on the sport-specific activity limitation caused by their physical impairment. Athletes with impaired muscle power, impaired passive range of motion (RM), and limb deficiency that affects the lower limbs and trunk are eligible to compete in para-kayak ( www.canoeicf.com/classification

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Jeremy A. Steeves, Scott A. Conger, Joe R. Mitrzyk, Trevor A. Perry, Elise Flanagan, Alecia K. Fox, Trystan Weisinger and Alexander H.K. Montoye

the 12 upper- and lower-body exercises roughly 78% of the time; however, some resistance training exercises were harder to discern from others (bench press/shoulder press and squats/forward walking lunges) which resulted in lower classification accuracy. Over 90% of all repetitions were successfully

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Andrew Hammond, Ruth Jeanes, Dawn Penney and Deana Leahy

 al., 2013 ; Wedgwood, 2014 ). In the next section we provide essential background about Australian swimming before using the critical disability studies concept of neoliberal-ableism to critique the schema of classification . As we explain, through our theorization of neoliberal-ableism, classification is

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K. Andrew R. Richards and Kim C. Graber

regard to engaging in retention initiatives? and (c) How do perceptions of strategies and barriers vary across institution Carnegie Classification? Method Data for this study were drawn from the PETE student retention questions included in the survey questionnaire described in Chapter 4 ( Richards

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Bethany Forseth and Stacy D. Hunter

. Classification of Intensity The intensity of each physiologic marker within each study was classified into light, moderate, or vigorous intensities. Classifications were based on previously established standards. Oxygen consumption intensity classifications were based on percentages of maximal oxygen consumption

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Luke Hogarth, Brendan Burkett, Peter Van de Vliet and Carl Payton

In Para swimming, a functional classification system has been used to structure competition since the 1992 Barcelona Paralympics. 1 Swimmers with physical, visual, and intellectual impairments compete in separate classes based on the estimated impact of their impairment on swim performance

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Derek M.D. Silva, Roy Bower and William Cipolli III

. Spectators, fans, media, and even athletes themselves often evoke the language used by scouts and so-called experts when evaluating athletic potential. The adoption of scouting discourses is particularly evident in the context of sports media, who increasingly evoke the language to produce classification