Date of Submission

3-1-2018

Abstract

Australian football is a dynamic team sport, which requires players to perform a large number of high-intensity efforts, combined with low-intensity activities throughout a match. Due to the complex and unique demands of the sport, players require an adequate training stimulus to develop and enhance the physical qualities required to succeed at the highest level. The ability to develop physically challenging but appropriate training at an individual level to 1) enhance the technical and physical qualities required, and 2) minimise the negative response to training (i.e. injury, illness, etc.) is a crucial task for practitioners involved in the preparation of elite players.

The cost of injury in elite sport is substantial, with player availability seen as a key factor in the success or failure of any professional sporting organisation. It is typically suggested that teams with higher injury rates are more likely to be negatively impacted through poor team performance, compared with teams with lower injury rates. If injuries (particularly non-contact, soft-tissue injuries) can be considered ‘largely’ avoidable, then the role of workload becomes a key component in any sporting organisation to manage and minimise the risk of injury.

The notion that workload and injury are interrelated is well established, yet the cost of injury remains significant at the professional level of Australian football. The overall aim of this program of research was to use scientific literature to understand the relationship between workload, injury, and performance in elite Australian football players and then improve the understanding of workload management and modelling of workload variables measured using a commercially available microtechnology unit. The program of research in this thesis first produced a comprehensive literature review to identify the current problem (s). The six subsequent chapters of original research built on the literature review to examine, in elite Australian football, (1) a previously suggested fitness-fatigue model on injury risk, (2) the importance of pre-season training on in-season availability, (3) the use of relative speed zones to model workload at an individual level, (4) a newly proposed fitness-fatigue model, (5) the differences between fitness-fatigue models in an applied setting, and finally (6) the application of a training monitoring system on injury rates.

A previously-established monitoring tool, the acute:chronic workload ratio, was used to quantify the relationship between workload and injury in a cohort of professional Australian football players. The size of the acute workload in relation to the size of the chronic workload was calculated as an acute:chronic workload ratio. A very high acute:chronic workload ratio (i.e. > 2.0) for total distance was associated with a 5 to 8- fold increase in injury risk during the season. Similarly, players with a high-speed running acute:chronic workload ratio of > 2.0 were 5-11 times more likely to sustain an injury in both the current and subsequent week. These findings demonstrate that sharp increases in acute workload significantly increase the likelihood of injury in both the current and subsequent week.

Once this relationship was confirmed in this cohort, the second study explored the effect of the amount of pre-season training completed on injury risk during the in-season period. Players who completed greater amounts of pre-season training (> 50% sessions completed) maintained higher workloads throughout the competitive phase of the season, as well as competed in a greater number of competitive matches. Further, injury rates were ~2 times greater in a low training load group (< 50% sessions completed), when compared with a high training load group (> 85% sessions completed). These findings demonstrate that completing a greater proportion of pre-season training resulted in higher training loads and greater participation in training and competition during the subsequent competitive season.

In study 3, a new method of workload and injury modelling was investigated and compared to a previous model. Specifically, the newly proposed model utilised an exponentially weighted moving average to calculate the acute:chronic workload ratio, as opposed to the previously used rolling averages method. There were significant differences in the acute:chronic workload ratio values for moderate, high, and very high ranges. Although both models demonstrated significant associations between a very high acute:chronic workload ratio (i.e. > 2.0) and increased injury likelihood, the exponentially weighted moving averages model was more sensitive for detecting this increased risk. These findings demonstrate that (1) large spikes in workload are associated with increased injury risk, irrespective of model used, and (2) the exponentially weighted moving averages model is more sensitive in detecting increased injury risk with high acute:chronic workload ratios.

The fourth study investigated the use of absolute and relative speed zones to quantify workload and the subsequent risk of injury. Players were divided into three groups based on maximum velocity; (1) faster, (2) moderate, or (3) slower, with individual workloads analysed using a pre-defined absolute speed threshold, or a relative individualised speed threshold. The differences in workload were calculated, along with differences in injury likelihood using both the rolling average and exponentially weighted moving average methods of workload calculation. Faster players demonstrated a significant over-estimation of very high-speed running when absolute thresholds were applied, while slower players demonstrated a significant underestimation of high- and very high-speed running when compared to their relative thresholds. These findings demonstrate that the use of relative thresholds significantly alters the amount of very high-speed running performed and should be considered in the prescription of workload.

Chapter 7 provides a case series of the differences in loading patterns between the rolling averages and exponentially weighted moving averages models of acute:chronic workload ratio to assess how large ‘spikes’ in workload can occur in one or both of the models. While both models are associated with increased injury risk, it is still unclear how these models differ at an individual workload level. This study explored three professional Australian football player’s loading patterns coupled with the proportion of similarities and differences found between the two existing workload model calculations, along with management strategies for different players in different phases of training.

Finally, the application of a training monitoring system to reduce injury rates was investigated in a cohort of professional Australian football players. The relationship between the acute:chronic workload ratio and injury was established over three seasons (2014-2016). In the final season (2017) of the study, an attempt was made to minimise the number of spikes in workload a player experienced. A significant reduction in workload spikes was observed over the entire 2017 season. In addition, a significant reduction in injury rate occurred. These findings demonstrated that the use of a training monitoring system decreased the number of workload spikes a player encountered, subsequently reducing the incidence of non-contact soft-tissue injury. Collectively, this thesis has highlighted the positive and negative effects of workload in relation to injury, and more specifically how workload is related to injury risk in elite Australian footballers. This applied research advances our understanding of workload and injury, and contributes to the body of literature on injury risk in elite Australian footballers.

School/Institute

School of Exercise Science

Document Type

Thesis

Access Rights

Open Access

Extent

249 pages

Degree Name

Doctor of Philosophy (PhD)

Faculty

Faculty of Health Sciences

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