A Kinetic Model Describing Injury-Burden in Team Sports
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ORIGINAL RESEARCH ARTICLE
A Kinetic Model Describing Injury-Burden in Team Sports Colin W. Fuller1
Ó Springer International Publishing Switzerland 2017
Abstract Background Injuries in team sports are normally characterised by the incidence, severity, and location and type of injuries sustained: these measures, however, do not provide an insight into the variable injury-burden experienced during a season. Injury burden varies according to the team’s match and training loads, the rate at which injuries are sustained and the time taken for these injuries to resolve. At the present time, this time-based variation of injury burden has not been modelled. Objectives To develop a kinetic model describing the time-based injury burden experienced by teams in elite team sports and to demonstrate the model’s utility. Methods Rates of injury were quantified using a large eight-season database of rugby injuries (5253) and exposure (60,085 player-match-hours) in English professional rugby. Rates of recovery from injury were quantified using time-to-recovery analysis of the injuries. Results The kinetic model proposed for predicting a team’s time-based injury burden is based on a composite rate equation developed from the incidence of injury, a first-order rate of recovery from injury and the team’s playing load. The utility of the model was demonstrated by examining common scenarios encountered in elite rugby. Conclusions The kinetic model developed describes and predicts the variable injury-burden arising from match play during a season of rugby union based on the incidence of match injuries, the rate of recovery from injury and the
& Colin W. Fuller [email protected] 1
Colin Fuller Consultancy Ltd, Main Street, Sutton Bonington LE12 5PE, UK
playing load. The model is equally applicable to other team sports and other scenarios.
Key Points A novel, kinetic model has been developed for predicting time-based injury-burden in team sports. Combining the onset and recovery of injuries within a single model provides a new perspective on the management of injury risk in team sports.
1 Introduction Many sports governing bodies [1–3] adopt the principles of risk management [4, 5] to guide their governance policies [6]. An essential aspect of this process is monitoring an organisation’s performance [7], which is particularly important for contact team sports, as the risk of injury is usually higher than that observed in non-contact sports [8]. Common measures used to characterise injury-burden in sport include the incidence (injuries/1000 player-hours of exposure), severity (days injured), location (%), type (%) and cause (%) of match and training injuries [9]. These output measures, however, do not provide an insight into the variable injury-burden experienced by teams during a season; therefore to understand and react to this dynamic situation, it is necessary to develop models that describe and predict injury-burden at any point in time. At the present time, there are a few injury causation models that discuss int
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