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Journal Article

Citation

Tierney P, Blake C, Delahunt E. Scand. J. Med. Sci. Sports 2020; ePub(ePub): ePub.

Copyright

(Copyright © 2020, John Wiley and Sons)

DOI

10.1111/sms.13779

PMID

32713044

Abstract

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 analysed 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 analysed via the manufacturer's software. Each match was also video recorded and evaluated by 2 expert video analysts. Pearson 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 expert video analysts and both MST collision metrics (the count of collision: 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.


Language: en

Keywords

injury; contact; contact sports; global positioning system; team sports

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