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Introduction
Injury prediction is one of the most challenging issues in sports and a key component for injury prevention, since the successful identification of injury predictors forms the basis for effective preventive measures. 1 Traditionally, scientific investigations have assumed a reductionist view in an attempt to understand sports injuries. According to this approach, the phenomenon (injury) has been reduced into units and explained by rational deduction. 2 3 The sports injury literature has revealed important injury predictors by means of typical statistics tools, such as logistic regression. However, for some injuries (eg, hamstring strain and patellar tendinopathy (PT)), these techniques have not yet yielded consistent identification of risk factors. 4 5 Unfortunately, these inconsistencies show that the majority of the human health conditions are complex. In this sense, we need a broader approach to better understand the complex relationships between risk factors/predictors and injuries. 2-4 6-8
To address this issue, Meeuwisse et al 9 developed a dynamic, recursive model for risk and causes of sports injuries, considering that the injury has a non-linear behavior. This model brought many advances to the understanding of sports injuries aetiology, because it assumes that there may be recurrent changes in susceptibility to injury along the participation in sports, and the primary risk factors exposure can produce adaptations and continuously change the risk. Despite the recognition of the non-linear and recursive characteristics of sports injuries, the model described by Meeuwisse et al 9 was not sufficient to address the complex interactions among several factors.
The multifactorial and complex nature of sports injuries arises not from the linear combination of isolated and predictive factors, but from the interaction among what Philippe and Mansi 8 called 'the web of determinants'. These determinants may be linked to each other in a non-linear manner, in the sense that small changes in a few determinants can lead to large and, sometimes, unexpected consequences. 6 10 We propose that, to fully uncover this complex nature of sports injury aetiology, a complex systems approach is necessary. This approach rests on identifying interactions and clarifying how these interactions contribute to the emergence of sports injuries. 10 11 In addition, it allows seeking regularities (see explanation in the characteristics of a complex system section), by means of pattern recognition...