2019SUNScholar (Stellenbosch University)Open access

Match-play demands of a Super Rugby team

Shaun Owen

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Abstract

Rugby union is a physically challenging intermittent sport, whose multi-faceted nature provides players with a range of playing positions, each with various physical traits, roles and responsibilities.In addition, following professionalisation, the match-play demands of the game have continued to evolve.There is currently limited literature on the contemporary match-play demands of rugby union, particularly temporal patterns as a match progresses, and peak periods of play.This study aimed to provide an accurate in-depth investigation of position-specific locomotive and contact demands during match-play, which will provide a basis for optimal preparation for competition, thereby potentially improving performance and reducing injury risk.Thirty-four professional male rugby union players (20-32 years old) were assessed during match-play over two Super Rugby seasons (2014 and 2015).Players were grouped into Forwards (n = 83) and Backs (n = 124), as well as Tight Forwards (n = 33), Loose Forwards (n = 50), Inside Backs (n = 60), and Outside Backs (n = 64).GPS and video-based analysis provided locomotive (maximum speed, sprint count, total distance, walking distance, jogging distance, striding distance, and sprint distance) and contact (total contact involvements, rucks, tackles, carries, scrums, and mauls) match-play data that were described through three methods: Full Match Analysis, Temporal Pattern Analysis, and Peak Period Analysis.A mixed model repeated measures ANOVA was utilised to draw comparisons between positional groups.

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Rugby union is a physically challenging intermittent sport, whose multi-faceted nature provides players with a range of playing positions, each with various physical traits, roles and responsibilities.In addition, following professionalisation, the match-play demands of the game have continued to evolve.There is currently limited literature on the contemporary match-play demands of rugby union, particularly temporal patterns as a match progresses, and peak periods of play.This study aimed to provide an accurate in-depth investigation of position-specific locomotive and contact demands during match-play, which will provide a basis for optimal preparation for competition, thereby potentially improving performance and reducing injury risk.Thirty-four professional male rugby union players (20-32 years old) were assessed during match-play over two Super Rugby seasons (2014 and 2015).Players were grouped into Forwards (n = 83) and Backs (n = 124), as well as Tight Forwards (n = 33), Loose Forwards (n = 50), Inside Backs (n = 60), and Outside Backs (n = 64).GPS and video-based analysis provided locomotive (maximum speed, sprint count, total distance, walking distance, jogging distance, striding distance, and sprint distance) and contact (total contact involvements, rucks, tackles, carries, scrums, and mauls) match-play data that were described through three methods: Full Match Analysis, Temporal Pattern Analysis, and Peak Period Analysis.A mixed model repeated measures ANOVA was utilised to draw comparisons between positional groups.

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Available abstract

Rugby union is a physically challenging intermittent sport, whose multi-faceted nature provides players with a range of playing positions, each with various physical traits, roles and responsibilities.In addition, following professionalisation, the match-play demands of the game have continued to evolve.There is currently limited literature on the contemporary match-play demands of rugby union, particularly temporal patterns as a match progresses, and peak periods of play.This study aimed to provide an accurate in-depth investigation of position-specific locomotive and contact demands during match-play, which will provide a basis for optimal preparation for competition, thereby potentially improving performance and reducing injury risk.Thirty-four professional male rugby union players (20-32 years old) were assessed during match-play over two Super Rugby seasons (2014 and 2015).Players were grouped into Forwards (n = 83) and Backs (n = 124), as well as Tight Forwards (n = 33), Loose Forwards (n = 50), Inside Backs (n = 60), and Outside Backs (n = 64).GPS and video-based analysis provided locomotive (maximum speed, sprint count, total distance, walking distance, jogging distance, striding distance, and sprint distance) and contact (total contact involvements, rucks, tackles, carries, scrums, and mauls) match-play data that were described through three methods: Full Match Analysis, Temporal Pattern Analysis, and Peak Period Analysis.A mixed model repeated measures ANOVA was utilised to draw comparisons between positional groups.

Key concepts: Psychology, Engineering, Applied psychology, Aeronautics

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