Multivariate modelling of subjective and objective monitoring data improve the detection of non-contact injury risk in elite Australian footballers

Colby, Marcus J.; Dawson, Brian; Peeling, Peter; Heasman, Jarryd; Rogalski, Brent; Drew, Michael; Stares, Jordan; Zouhal, Hassane; Lester, Leanne

doi:10.1016/j.jsams.2017.05.010

Cited by 63 publications

(88 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both acute:chronic workloads, independently, showed poor predictive power (all AUCs <0.60, Youden Indices close to 0, poor sensitivity, ie, ability to detect when a non-contact injury will occur and low positive predictive values). It should be noted that multivariate approaches to the analysis of workload measures have been shown to improve predictive power36 and should be considered in future workload research in elite football. The current authors have deliberately kept this section of the discussion brief, as the aim of injury risk mitigation is not necessarily about predicting injury, but rather understanding and establishing risk factors to target for risk mitigation strategies 37…”

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

View full text Add to dashboard Cite

show abstract

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

View full text Add to dashboard Cite

show abstract

“…The most common timeframe used was a 1-week acute training load and 4-week chronic training load. [9][10][11]17,18,[20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] Other timeframes included a 3-day acute load and a 21 daychronic load, 19 or varying timeframes. [37][38][39][40] One study examined various timeframes for calculating ACWR, 37 utilizing 2-9 days for acute loads, and chronic loads varying from 14 to 35 days, while the other study ranged from 1 to 2 weeks for acute loads, and 3-8 weeks for chronic loads, but only utilized the 1:4 week ratio for relationship to injury.…”

Section: Study Characteristicsmentioning

confidence: 99%

“…38 Five studies utilized exponentially weighted moving averages (EWMA) for their calculation of ACWR 17,27,29,36,39 and four articles studied a combination of ACWR and chronic workload. 11,30,38,39 Lastly, one study examined ACWR in combination with recent lower limb injuries, 36 while another evaluated the effects of fitness on the relationship between ACWR and injury risk. 23…”

Section: Study Characteristicsmentioning

confidence: 99%

“…Three studies reported the ACWR of total distance and its relation to varying chronic workloads. 11,30,38 Hulin et al 18 found that an ACWR of 1.23-1.61 combined with short recovery (<7 days between matches) increased injury risk compared to an ACWR of 1.02-1.22 (RR=2.88). In addition, it was also found that ACWR ≥1.62 combined with short recovery further increased injury risk relative to ACWR of 1.02-1.22 (RR=5.80) and 0.67-0.86 (RR=3.41).…”

Section: Association Of External Loads and Injury Risks Total Distancementioning

confidence: 99%

“…38 This same study also found an ACWR of 0.00-0.03 for TD combined with low 4-week chronic TD (18,834-20,892m) further increased injury risk 7 days later (RR=8.19) compared to chronic sprint distance, but had no significant impact 14 (RR=5.49), 21 (RR=4.16) or 28 days later (RR=3.16) when compared to an ACWR 0.90-1.20 and a high 4-week chronic TD (20892-22762m). 38 Colby et al 30 reported, compared to ACWR range of 0.99 to 1.08, ranges of <0.88 (IRR=1.17), 1.08-1.21 (IRR=1.37), and >1.21 (IRR=1.53) resulted in higher incidence of injury, while 0.88-0.99 (IRR=0.60) resulted in a lower incidence when using TD. This same study found that when compared to an above average chronic TD load (81694m over 4 weeks) and moderate 27,30,34,[36][37][38][39] Total [9,10,17,20,21,[23][24][25][26][28][29][30][31][32][33][35][36][37][38]40] ACWR [11,[17][18][19][20][21][22][23][25][26][27][28][29]…”

Section: Association Of External Loads and Injury Risks Total Distancementioning

confidence: 99%

See 2 more Smart Citations

<p>The Relationship Between Acute: Chronic Workload Ratios and Injury Risk in Sports: A Systematic Review</p>

Maupin¹,

Schram²,

Canetti³

et al. 2020

OAJSM

View full text Add to dashboard Cite

Purpose: Low injury rates have previously been correlated with sporting team success, highlighting the importance of injury prevention programs. Recent methods, such as acute: chronic workload ratios (ACWR) have been developed in an attempt to predict and manage injury risk; however, the relation between these methods and injury risk is unclear. The aim of this systematic review was to identify and synthesize the key findings of studies that have investigated the relationship between ACWR and injury risk. Methods: Included studies were critically appraised using the Downs and Black checklist, and a level of evidence was determined. Relevant data were extracted, tabulated, and synthesized. Results: Twenty-seven studies were included for review and ranged in percentage quality scores from 48.2% to 64.3%. Almost perfect interrater agreement (κ = 0.885) existed between raters. This review found a high variability between studies with different variables studied (total distance versus high speed running), as well as differences between ratios analyzed (1.50-1.80 versus ≥1.50), and reference groups (a reference group of 0.80-1.20 versus ≤0.85). Conclusion: Considering the high variability, it appears that utilizing ACWR for external (eg, total distance) and internal (eg, heart rate) loads may be related to injury risk. Calculating ACWR using exponentially weighted moving averages may potentially result in a more sensitive measure. There also appears to be a trend towards the ratios of 0.80-1.30 demonstrating the lowest risk of injury. However, there may be issues with the ACWR method that must be addressed before it is confidently used to mitigate injury risk. Utilizing standardized approaches will allow for more objective conclusions to be drawn across multiple populations.

show abstract

Team's average acute:chronic workload ratio correlates with injury risk in NCAA men's soccer team

Bakal

Friedrich

Keane

et al. 2023

PM&R

View full text Add to dashboard Cite

BackgroundResearch in multiple sports has shown that an individual's acute:chronic workload ratio (ACWR) correlates with injury. However, tailoring team trainings to each individual's ACWR is technically challenging and has not been found to decrease injury risk.ObjectiveTo establish a more feasible method of utilizing the ACWR for injury prevention in soccer. In a National Collegiate Athletic Association (NCAA) men's soccer team, we assessed whether the team's average ACWR, as opposed to that of each individual, correlated with injuries sustained throughout the season.DesignInjury and workload data were retrospectively evaluated for all players (n = 23) of an NCAA men's soccer team during one 18‐week season. Workload data for five global positioning system (GPS)‐derived workload variables (total distance, high‐speed distance, accelerations, player load, and average velocity) were used to calculate the team's average daily acute and chronic workloads (accumulated load for each variable during the past 3 and 28 days, respectively), and uncoupled ACWRs (acute workload divided by chronic workload for each variable). A retrospective cohort design was used to compare the team's workloads and ACWRs on days where ≥1 injury occurred versus days where zero injuries occurred using binary logistic regression models.ResultsTrainings/games with injuries had higher acute workloads, lower chronic workloads, and higher ACWRs for all five workload variables. In multivariable analysis, risk factors for injury included a low chronic workload for total distance (odds ratio [OR] 7.23, p = .024) and an ACWR >1.4 for accelerations (OR 4.34, p = .029).ConclusionsThe team's injury risk was greater with low distance accumulation during the chronic period and with an elevated ACWR for accelerations. Future intervention‐based studies aimed at using ACWR load‐management principles as a method of decreasing injury risk in soccer can consider tracking the team's average values with the goal of maintaining a consistent chronic workload for total distance and avoiding elevations in the ACWR for accelerations.

show abstract

Multivariate modelling of subjective and objective monitoring data improve the detection of non-contact injury risk in elite Australian footballers

Abstract: Chronic load is an important moderating factor in the workload-injury relationship. Low chronic loads coupled with low or very high ACWR are associated with increased injury risk.

Cited by 63 publications

References 31 publications

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

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

<p>The Relationship Between Acute: Chronic Workload Ratios and Injury Risk in Sports: A Systematic Review</p>

Team's average acute:chronic workload ratio correlates with injury risk in NCAA men's soccer team

Contact Info

Product

Resources

About