Title

The relationship between training load and incidence of injury and illness over a pre-season at an Australian Football League Club

Document Type

Journal Article

Publisher

Australian Strength and Conditioning Association

Faculty

Computing, Health and Science

School

Exercise, Biomedical and Health Science, Centre for Exercise and Sports Science Research

RAS ID

9315

Comments

This article was originally published as: Piggott, B., Newton, M. J., & McGuigan, M. R. (2009). The relationship between training load and incidence of injury and illness over a pre-season at an Australian football league club. Journal of Australian Strength and Conditioning, 17(3). Original available here

Abstract

In any competitive sporting environment, it is crucial to a team’s success to have the maximum number of their players free from injury and illness and available for selection in as many games as possible throughout the season. The training programme of the club, and therefore training load, can have an impact on the incidence of injury and illness amongst the players. The purpose of this study was to investigate the relationship between the training load and the incidence of injury and illness over an entire pre-season at an Australian Football League (AFL) club. Sixteen players were subjects; all full time professional male AFL players (mean ± standard deviation; age 23.8 ± 5.1 years; height 188.9 ± 7.4 m; weight 90.9 ± 9.2 kg). A longitudinal research design was employed, where training load, injury and illness were monitored over a 15 week pre-season and Pearson Correlation Coefficients were used to examine relationships. Training load was measured in four different ways; Rating of Perceived Exertion (RPE) × time, mins > 80% max HR, total distance run and total distance run > 12 km/h. Strain and monotony were also determined. The study provided valuable insight into the training demands of an AFL club. There were few in stances of injury (n = 5) and illness (n =12) over the pre-season. There was a significant relationship between total distance run and incidence of injury (r = -0.52, p = 0.048). It was found that 42% of illnesses could be explained by a preceding spike in training load, whilst 40% of injuries could be explained by a preceding spike in training load. The findings of this study show that accurately monitoring training load can help predict where illnesses and injuries may occur. More research is warranted on the monitoring of training load and its relationship with injury and illness in team sports.

Access Rights

Not open access