Literature DB >> 28872423

The Use of Relative Speed Zones in Australian Football: Are We Really Measuring What We Think We Are?

Nick B Murray, Tim J Gabbett, Andrew D Townshend.   

Abstract

OBJECTIVES: To examine the difference between absolute and relative workloads, injury likelihood, and the acute:chronic workload ratio (ACWR) in elite Australian football.
DESIGN: Single-cohort, observational study.
METHODS: Forty-five elite Australian football players from 1 club participated. Running workloads of players were tracked using Global Positioning System technology and were categorized using either (1) absolute, predefined speed thresholds or (2) relative, individualized speed thresholds. Players were divided into 3 equal groups based on maximum velocity: (1) faster, (2) moderate, or (3) slower. One- and 4-wk workloads were calculated, along with the ACWR. Injuries were recorded if they were noncontact in nature and resulted in "time loss."
RESULTS: Faster players demonstrated a significant overestimation of very high-speed running (HSR) when compared with their relative thresholds (P = .01; effect size = -0.73). Similarly, slower players demonstrated an underestimation of high-(P = .06; effect size = 0.55) and very-high-speed (P = .01; effect size = 1.16) running when compared with their relative thresholds. For slower players, (1) greater amounts of relative very HSR had a greater risk of injury than less (relative risk [RR] = 8.30; P = .04) and (2) greater absolute high-speed chronic workloads demonstrated an increase in injury likelihood (RR = 2.28; P = .16), whereas greater relative high-speed chronic workloads offered a decrease in injury likelihood (RR = 0.33; P = .11). Faster players with a very-high-speed ACWR of >2.0 had a greater risk of injury than those between 0.49 and 0.99 for both absolute (RR = 10.31; P = .09) and relative (RR = 4.28; P = .13) workloads.
CONCLUSIONS: The individualization of velocity thresholds significantly alters the amount of very HSR performed and should be considered in the prescription of training load.

Entities:  

Keywords:  GPS; physical performance; sport; training

Mesh:

Year:  2018        PMID: 28872423     DOI: 10.1123/ijspp.2017-0148

Source DB:  PubMed          Journal:  Int J Sports Physiol Perform        ISSN: 1555-0265            Impact factor:   4.010


  6 in total

1.  The Use of Generic and Individual Speed Thresholds for Assessing the Competitive Demands of Field Hockey.

Authors:  David Casamichana; Esther Morencos; Blanca Romero-Moraleda; Tim J Gabbett
Journal:  J Sports Sci Med       Date:  2018-08-14       Impact factor: 2.988

2.  The Training-Performance Puzzle: How Can the Past Inform Future Training Directions?

Authors:  Tim J Gabbett
Journal:  J Athl Train       Date:  2020-09-01       Impact factor: 2.860

3.  Training Load and Its Role in Injury Prevention, Part 2: Conceptual and Methodologic Pitfalls.

Authors:  Franco M Impellizzeri; Alan McCall; Patrick Ward; Luke Bornn; Aaron J Coutts
Journal:  J Athl Train       Date:  2020-09-01       Impact factor: 2.860

Review 4.  The Association Between the Acute:Chronic Workload Ratio and Injury and its Application in Team Sports: A Systematic Review.

Authors:  Alan Griffin; Ian C Kenny; Thomas M Comyns; Mark Lyons
Journal:  Sports Med       Date:  2020-03       Impact factor: 11.136

5.  Is the Acute: Chronic Workload Ratio (ACWR) Associated with Risk of Time-Loss Injury in Professional Team Sports? A Systematic Review of Methodology, Variables and Injury Risk in Practical Situations.

Authors:  Renato Andrade; Eirik Halvorsen Wik; Alexandre Rebelo-Marques; Peter Blanch; Rodney Whiteley; João Espregueira-Mendes; Tim J Gabbett
Journal:  Sports Med       Date:  2020-09       Impact factor: 11.136

6.  Evolution of Physical Demands of Australian Football League Matches from 2005 to 2017: A Systematic Review and Meta-Regression.

Authors:  Samuel J Janetzki; Pitre C Bourdon; Kevin I Norton; Jackson C Lane; Clint R Bellenger
Journal:  Sports Med Open       Date:  2021-04-28
  6 in total

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