Literature DB >> 32412969

The Distribution of Match Activities Relative to the Maximal Mean Intensities in Professional Rugby League and Australian Football.

Rich D Johnston1,2, Heidi R Thornton3, Jarrod A Wade4, Paul Devlin5, Grant M Duthie6.   

Abstract

ABSTRACT: Johnston, RD, Thornton, HR, Wade, JA, Devlin, P, and Duthie, GM. The distribution of match activities relative to the maximal mean intensities in professional rugby league and Australian football. J Strength Cond Res 36(5): 1360-1366, 2022-This study determined the distribution of distance, impulse, and accelerometer load accumulated at intensities relative to the maximal mean 1-minute peak intensity within professional rugby league and Australian football. Within 26 rugby league (n = 24 athletes) and 18 Australian football (n = 38 athletes) games, athletes wore global navigation satellite system devices (n = 608 match files). One-minute maximal mean values were calculated for each athlete per game for speed (m·minP-1P), accelerometer load (AU·minP-1P), and acceleration (m·sP-2P). Volumes for each parameter were calculated by multiplying by time, specifying total distance, accelerometer load, and impulse. The distribution of intensity of which these variables were performed relative to the maximal mean was calculated, with percentages ranging from 0-110%, separated into 10% thresholds. Linear mixed models determined whether the distribution of activities within each threshold varied, and positional differences. Effects were described using standardized effect sizes (ESs), and magnitude-based decisions. Across both sports, the distribution of activity (%) largely reduced the closer to the maximal mean 1-minute peak and was highest at ∼60% of the maximal mean peak. When compared with Australian football, a higher percentage of total distance was accumulated at higher intensities (70-80% and 100-110%) for rugby league (ES range = 0.82-0.87), with similar, yet larger differences for accelerometer load >80% (0.78-1.07) and impulse >60% (1.00-2.26). These findings provide information of the volume of activities performed relative to the mean maximal 1-minute peak period, which may assist in the prescription of training.
Copyright © 2020 National Strength and Conditioning Association.

Entities:  

Mesh:

Year:  2020        PMID: 32412969     DOI: 10.1519/JSC.0000000000003613

Source DB:  PubMed          Journal:  J Strength Cond Res        ISSN: 1064-8011            Impact factor:   3.775


  6 in total

1.  Effect of formation, ball in play and ball possession on peak demands in elite soccer.

Authors:  Andrea Riboli; Marco Semeria; Giuseppe Coratella; Fabio Esposito
Journal:  Biol Sport       Date:  2020-09-01       Impact factor: 2.806

2.  Acceleration and High-Speed Running Profiles of Women's International and Domestic Football Matches.

Authors:  Jesse Griffin; Timothy Newans; Sean Horan; Justin Keogh; Melissa Andreatta; Clare Minahan
Journal:  Front Sports Act Living       Date:  2021-03-25

3.  A GNSS-based method to define athlete manoeuvrability in field-based team sports.

Authors:  Grant Malcolm Duthie; Sam Robertson; Heidi Rose Thornton
Journal:  PLoS One       Date:  2021-11-19       Impact factor: 3.240

4.  Analysis of professional soccer players in competitive match play based on submaximum intensity periods.

Authors:  Eduardo Caro; Miguel Ángel Campos-Vázquez; Manuel Lapuente-Sagarra; Toni Caparrós
Journal:  PeerJ       Date:  2022-04-26       Impact factor: 3.061

5.  The Distribution of Match Physical Activities Relative to the Most Demanding Scenarios in Professional Basketball Players.

Authors:  Franc García; Daniel Fernández; Jordi Illa; Xavier Reche; Jairo Vázquez-Guerrero
Journal:  J Hum Kinet       Date:  2022-09-08       Impact factor: 2.923

Review 6.  The Maximal Intensity Period: Rationalising its Use in Team Sports Practice.

Authors:  Dan Weaving; Damien Young; Andrea Riboli; Ben Jones; Giuseppe Coratella
Journal:  Sports Med Open       Date:  2022-10-12
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.