The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform
David Drake - One of the best experts on this subject based on the ideXlab platform.
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the use of microtechnology to monitor Collision performance in professional rugby union
International Journal of Sports Physiology and Performance, 2018Co-Authors: Simon Macleod, Chris Hagan, Mikel Egaña, Jonny Davis, David DrakeAbstract:Purpose: To determine if microtechnology-derived Collision loads discriminate between Collision performance and compare the physical and analytical components of Collision performance between positional groups. Methods: Thirty-seven professional male rugby union players participated in this study. Collision events from 11 competitive matches were coded using specific tackle and carry classifications based on the ball-carrier’s Collision outcome. Collisions were automatically detected using 10 Hz microtechnology units. Collision events were identified, coded (as tackle or carry), and timestamped at the Collision contact point using game analysis software. Attacking and defensive performances of 1609 Collision events were analyzed. Results: Collision loads were significantly greater during dominant compared with neutral and passive Collisions (P < .001; effect size [ES] = 0.53 and 0.80, respectively), tackles (P < .0001; ES = 0.60 and 0.56, respectively), and carries (P < .001; ES = 0.48 and 0.79, respectiv...
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The Use of Microtechnology to Monitor Collision Performance in Professional Rugby Union.
International Journal of Sports Physiology and Performance, 2018Co-Authors: Simon Macleod, Chris Hagan, Mikel Egaña, Jonny Davis, David DrakeAbstract:Purpose: To determine if microtechnology-derived Collision loads discriminate between Collision performance and compare the physical and analytical components of Collision performance between positional groups. Methods: Thirty-seven professional male rugby union players participated in this study. Collision events from 11 competitive matches were coded using specific tackle and carry classifications based on the ball-carrier’s Collision outcome. Collisions were automatically detected using 10 Hz microtechnology units. Collision events were identified, coded (as tackle or carry), and timestamped at the Collision contact point using game analysis software. Attacking and defensive performances of 1609 Collision events were analyzed. Results: Collision loads were significantly greater during dominant compared with neutral and passive Collisions (P
Simon Macleod - One of the best experts on this subject based on the ideXlab platform.
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the use of microtechnology to monitor Collision performance in professional rugby union
International Journal of Sports Physiology and Performance, 2018Co-Authors: Simon Macleod, Chris Hagan, Mikel Egaña, Jonny Davis, David DrakeAbstract:Purpose: To determine if microtechnology-derived Collision loads discriminate between Collision performance and compare the physical and analytical components of Collision performance between positional groups. Methods: Thirty-seven professional male rugby union players participated in this study. Collision events from 11 competitive matches were coded using specific tackle and carry classifications based on the ball-carrier’s Collision outcome. Collisions were automatically detected using 10 Hz microtechnology units. Collision events were identified, coded (as tackle or carry), and timestamped at the Collision contact point using game analysis software. Attacking and defensive performances of 1609 Collision events were analyzed. Results: Collision loads were significantly greater during dominant compared with neutral and passive Collisions (P < .001; effect size [ES] = 0.53 and 0.80, respectively), tackles (P < .0001; ES = 0.60 and 0.56, respectively), and carries (P < .001; ES = 0.48 and 0.79, respectiv...
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The Use of Microtechnology to Monitor Collision Performance in Professional Rugby Union.
International Journal of Sports Physiology and Performance, 2018Co-Authors: Simon Macleod, Chris Hagan, Mikel Egaña, Jonny Davis, David DrakeAbstract:Purpose: To determine if microtechnology-derived Collision loads discriminate between Collision performance and compare the physical and analytical components of Collision performance between positional groups. Methods: Thirty-seven professional male rugby union players participated in this study. Collision events from 11 competitive matches were coded using specific tackle and carry classifications based on the ball-carrier’s Collision outcome. Collisions were automatically detected using 10 Hz microtechnology units. Collision events were identified, coded (as tackle or carry), and timestamped at the Collision contact point using game analysis software. Attacking and defensive performances of 1609 Collision events were analyzed. Results: Collision loads were significantly greater during dominant compared with neutral and passive Collisions (P
Eamonn Delahunt - One of the best experts on this subject based on the ideXlab platform.
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The relationship between Collision metrics from micro-sensor technology and video-coded events in rugby union.
Scandinavian journal of medicine & science in sports, 2020Co-Authors: Peter Tierney, Catherine Blake, Eamonn DelahuntAbstract:This study aimed to determine the relationship between Collision metrics from a commercially available micro-sensor technology unit (MST) and the count of Collisions coded by expert video analysts in professional rugby union. Forty-four professional rugby union players wore MST units during match play. We analyzed 245 combined data files from 11 competitive matches, resulting in the inclusion of a total of 9202 individual Collision events. Collision metrics (the count of Collisions and the Collision Load™) were analyzed via the manufacturer's software. Each match was also video recorded and evaluated by two expert video analysts. Pearson's correlation coefficients were used to determine the relationship between the count of Collisions coded by the expert video analysts, and both MST Collision metrics. One-way ANOVA was used to determine whether differences in the Collision Load™ for individual Collision events existed between different playing positions. Very large-nearly perfect correlations were observed between the count of Collisions coded by the expert video analysts and both MST Collision metrics (the count of Collisions: r = 0.91, 90% CI = 0.89-0.93; the Collision Load™: r = 0.89; 90% CI = 0.87-0.91). Differences in the Collision Load™ for individual Collision events were identified between different playing positions. Collision metrics registered by the MST software relate very strongly with the count of Collisions coded by expert video analysts. The typical Collision LoadTM per individual Collision event varies depending on player position. The application of automated Collision detection for rugby union appears feasible.
H Krugliak - One of the best experts on this subject based on the ideXlab platform.
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Collisions of cloud droplets in a turbulent flow part v application of detailed tables of turbulent Collision rate enhancement to simulation of droplet spectra evolution
Journal of the Atmospheric Sciences, 2008Co-Authors: Mark Pinsky, A Khain, H KrugliakAbstract:The present study is a continuation of the series of studies dedicated to the investigation of cloud droplet Collisions in turbulent flow with characteristics that are typical of real clouds. Detailed tables of Collision kernels and Collision efficiencies calculated in the presence of hydrodynamic interaction of droplets are presented. These tables were calculated for a wide range of turbulent parameters. To illustrate the sensitivity of droplet size distribution (DSD) evolution to the turbulence-induced increase in the Collision rate, simulations of DSD evolution are preformed by solving the stochastic kinetic equation for Collisions. The results can be applied to cloud modeling. The tables of Collision efficiencies and Collision kernels are available upon request. Some unsolved problems related to Collisions of droplets and ice hydrometeors in turbulent clouds are discussed in the conclusion.
Cloe Cummins - One of the best experts on this subject based on the ideXlab platform.
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quantifying the Collision dose in rugby league a systematic review meta analysis and critical analysis
Sports Medicine - Open, 2020Co-Authors: Mitchell Naughton, Ben Jones, Sharief Hendricks, Doug King, Aron J Murphy, Cloe CumminsAbstract:Collisions (i.e. tackles, ball carries, and Collisions) in the rugby league have the potential to increase injury risk, delay recovery, and influence individual and team performance. Understanding the Collision demands of the rugby league may enable practitioners to optimise player health, recovery, and performance. The aim of this review was to (1) characterise the dose of Collisions experienced within senior male rugby league match-play and training, (2) systematically and critically evaluate the methods used to describe the relative and absolute frequency and intensity of Collisions, and (3) provide recommendations on Collision monitoring. A systematic search of electronic databases (PubMed, SPORTDiscus, Scopus, and Web of Science) using keywords was undertaken. A meta-analysis provided a pooled mean of Collision frequency or intensity metrics on comparable data sets from at least two studies. Forty-three articles addressing the absolute (n) or relative Collision frequency (n min−1) or intensity of senior male rugby league Collisions were included. Meta-analysis of video-based studies identified that forwards completed approximately twice the number of tackles per game than backs (n = 24.6 vs 12.8), whilst ball carry frequency remained similar between backs and forwards (n = 11.4 vs 11.2). Variable findings were observed at the subgroup level with a limited number of studies suggesting wide-running forwards, outside backs, and hit-up forwards complete similar ball carries whilst tackling frequency differed. For microtechnology, at the team level, players complete an average of 32.7 Collisions per match. Limited data suggested hit-up and wide-running forwards complete the most Collisions per match, when compared to adjustables and outside backs. Relative to playing time, forwards (n min−1 = 0.44) complete a far greater frequency of Collision than backs (n min−1 = 0.16), with data suggesting hit-up forwards undertake more than adjustables, and outside backs. Studies investigating g force intensity zones utilised five unique intensity schemes with zones ranging from 2–3 g to 13–16 g. Given the disparity between device setups and zone classification systems between studies, further analyses were inappropriate. It is recommended that practitioners independently validate microtechnology against video to establish criterion validity. Video- and microtechnology-based methods have been utilised to quantify Collisions in the rugby league with differential Collision profiles observed between forward and back positional groups, and their distinct subgroups. The ball carry demands of forwards and backs were similar, whilst tackle demands were greater for forwards than backs. Microtechnology has been used inconsistently to quantify Collision frequency and intensity. Despite widespread popularity, a number of the microtechnology devices have yet to be appropriately validated. Limitations exist in using microtechnology to quantify Collision intensity, including the lack of consistency and limited validation. Future directions include application of machine learning approaches to differentiate types of Collisions in microtechnology datasets.
