Literature DB >> 35073233

Possession chain factors influence movement demands in elite Australian football match-play.

Andrew Vella1,2, Anthea C Clarke1, Thomas Kempton2,3, Samuel Ryan2,3, Jacob Holden, Aaron J Coutts2,3.   

Abstract

Contemporary analysis of physical activity in Australian Football (AF) is typically presented as a total measure and independent of game context, which is not representative of how the game is played and/or assessed by coaches. This study examines the activity profile of individual possession chains and determines the influence that field position, initial chain state, and possession phase have on these activity characteristics in men's AF.Global positioning system data were attained from 35 players in 13 matches across the 2019 Australian Football League season. Matches were coded into different possession phases, initial field location of the ball, and initial chain state. Mixed models were built to observe the influence of field position and initial chain state for each possession phase.Less TD and HSR distance were covered during attacking chains in the forward 50 and attacking midfield, while defensive chains covered less TD and HSR in the defensive 50 and defensive midfield (p < 0.001). Significant main effects for possession phase and initial chain state were observed for TD and HSR. TD and HSR were higher during attacking chains, while chains beginning from a stoppage were lower than intercept and kick-ins (p < 0.001).Overall, the most intense moments of the game appear similar across all possession phases when field location is accounted for and that transitioning the ball quickly from the defensive end of the field results in greater physical activity. These findings can be used for prescription and monitoring of training drills specific to AF requirements.

Entities:  

Keywords:  GPS; tactics; team sport; time-motion analysis

Mesh:

Year:  2020        PMID: 35073233     DOI: 10.1080/24733938.2020.1795235

Source DB:  PubMed          Journal:  Sci Med Footb        ISSN: 2473-3938


  4 in total

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Journal:  Front Neurorobot       Date:  2022-06-29       Impact factor: 3.493

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Authors:  Christopher Wing; Nicolas H Hart; Fadi Ma'ayah; Kazunori Nosaka
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3.  Quantifying congestion with player tracking data in Australian football.

Authors:  Jeremy P Alexander; Karl B Jackson; Timothy Bedin; Matthew A Gloster; Sam Robertson
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4.  Assessment of Physical, Technical, and Tactical Analysis in the Australian Football League: A Systematic Review.

Authors:  Andrew Vella; Anthea C Clarke; Thomas Kempton; Samuel Ryan; Aaron J Coutts
Journal:  Sports Med Open       Date:  2022-10-08
  4 in total

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