Applying the acute:chronic workload ratio in elite football: worth the effort?

Buchheit, Martin

doi:10.1136/bjsports-2016-097017

Cited by 46 publications

(46 citation statements)

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“…Lu et al 12 found no excessively inflated acute:chronic workloads prior to injury. The traditional acute:chronic workload at 1:4 may not apply to elite football due to congested fixture scheduling 31. Therefore, the current study investigated three acute:chronic ratios (1:2, 1:3 and 1:4 weeks) and found that the traditional acute:chronic_1:4 between 0.97 to 1.38 and >1.38 increased the risk of non-conact injury (RR=1.68 and 2.13, respectively, when compared with reference acute:chronic workload of 0.60 to 0.97).…”

Section: Discussionmentioning

confidence: 99%

Internal workload and non-contact injury: a one-season study of five teams from the UEFA Elite Club Injury Study

McCall¹,

Dupont²,

Ekstrand

2018

Br J Sports Med

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Section: Discussionmentioning

confidence: 99%

Internal workload and non-contact injury: a one-season study of five teams from the UEFA Elite Club Injury Study

McCall¹,

Dupont²,

Ekstrand

2018

Br J Sports Med

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“…Recent research has demonstrated 70-75% of an endurance athletes training load is undertaken at continuous low training intensities 19,43,44 whereas in non-ESP training, load favours repeated moderate to high training intensities, separated by periods of low intensity training. 20,45,46 This highlights the unique training undertaken by ESPs and the potential barriers to applying findings from non-ESP research to ESPs.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

The associations between training load and baseline characteristics on musculoskeletal injury and pain in endurance sport populations: A systematic review

Johnston¹

2017

Physical Therapy in Sport

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Objective: To determine the associations between training load, baseline characteristics (e.g. age or previous injury) and rate of musculoskeletal injury and/or pain specifically within an Endurance Sporting Population (ESP). Design: Prospectively registered systematic review. 3 Methods: Eight electronic databases were searched by two independent reviewers. Studies were required to prospectively monitor both (i) training loads and (ii) musculoskeletal injury and/or pain for >3 months. Methodological quality and risk of bias were determined utilising the Critical Skills Appraisal Program (CASP). Reported effect sizes were categorised as small, medium or large. Results: Twelve endurance sport studies were eligible (running, triathlon, rowing). Increased injury and/or pain risk was associated with: (i) high total training distances per week/month (medium effect size) (ii) training frequency <2 sessions/week (medium effect size) and (iii) both low weekly (<2 hours/week) and high monthly (large effect size) training durations. None of the studies reported internal training load data or acute:chronic workload ratios. Baseline characteristics found to increase the rate of injury and/or pain included: (i) a history of previous injury (medium effect size), (ii) age >45 years (small effect size), (iii) non-musculoskeletal comorbidities (large effect size), (iv) using older running shoes (small effect size) and (v) non-competitive behaviour. Conclusions: This review identifies a range of external training load factors and baseline characteristics associated with an increased rate of injury and/or pain within ESPs. There is an absence of research relating to internal training loads and acute:chronic workload ratios in relation to rate of injury and/or pain within ESPs.

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“…In fact, over one season, players train and play for about 10 months with their respective clubs, while they may spend only 4 × ̴ 10 days during the year with their national teams (i.e., "international breaks"), before the 3-week pre-WC preparation. In between the end of the 2017 Euro and the 14 th of June, international players would have spent about ̴ 250-270 days with their clubs, and at best, 60-70 days with their national teams (Buchheit 2017a). Finally, players from a single national team often play in more than 10 different clubs and different leagues, which dictates their time of arrival when joining their national team.…”

Section: Introductionmentioning

confidence: 99%

“…What happens often, however, is that while both entities implement some tests and use monitoring technologies, those are different for various reasons (e.g., habits, beliefs, resources): there is therefore a need (i) to use correspondences or create equivalences (e.g., calibrations equations (Buchheit et al 2014)) between the different tests/data/technologies used in each team (= least bad option) or (ii) that one entity convinces the other to change his testing approach/technology (= unlikely). Finally, the worst case scenario is when players are not monitored by one or both structures, or that for various reasons they do not want to share data (Buchheit 2017a). It is also worth noting that staff from both national teams and elite clubs are rarely stable, which complicates further the continuous exchange of information.…”

Section: Introductionmentioning

confidence: 99%