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Sports Injury Forecasting and Complexity: A Synergetic Approach

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Abstract

The understanding that sports injury is the result of the interaction among many factors and that specific profiles could increase the risk of the occurrence of a given injury was a significant step in establishing programs for injury prevention. However, injury forecasting is far from being attained. To be able to estimate future states of a complex system (forecasting), it is necessary to understand its nature and comply with the methods usually used to analyze such a system. In this sense, sports injury forecasting must implement the concepts and tools used to study the behavior of self-organizing systems, since it is by self-organizing that systems (i.e., athletes) evolve and adapt (or not) to a constantly changing environment. Instead of concentrating on the identification of factors related to the injury occurrence (i.e., risk factors), a complex systems approach looks for the high-order variables (order parameters) that describe the macroscopic dynamic behavior of the athlete. The time evolution of this order parameter informs on the state of the athlete and may warn about upcoming events, such as injury. In this article, we describe the fundamental concepts related to complexity based on physical principles of self-organization and the consequence of accepting sports injury as a complex phenomenon. In the end, we will present the four steps necessary to formulate a synergetics approach based on self-organization and phase transition to sports injuries. Future studies based on this experimental paradigm may help sports professionals to forecast sports injuries occurrence.

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Authors and Affiliations

  1. Graduate Program in Rehabilitation Sciences, Physical Therapy Department, and Centro de Treinamento Esportivo, Universidade Federal de Minas Gerais, 6627, Pampulha, 31270-901, Belo Horizonte, MG, Brazil

    Sergio T. Fonseca, Thales R. Souza, Renan A. Resende & Juliana M. Ocarino

  2. Amsterdam Collaboration on Health & Safety in Sports, Department of Public and Occupational Health, Amsterdam Movement Sciences, Amsterdam UMC, Amsterdam, Netherlands

    Evert Verhagen

  3. Graduate Program in Rehabilitation Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Evert Verhagen

  4. Motor Control Laboratory, Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA, 01003, USA

    Richard van Emmerik

  5. Uni-BH University, Belo Horizonte, MG, Brazil

    Natalia F. N. Bittencourt

  6. Physical Therapy Department, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Diamantina, MG, Brazil

    Luciana D. M. Mendonça

  7. Graduate Program in Sports Sciences, Sports Department, and Centro de Treinamento Esportivo, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

    André G. P. Andrade

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  1. Sergio T. Fonseca
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  2. Thales R. Souza
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  3. Evert Verhagen
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  5. Natalia F. N. Bittencourt
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  6. Luciana D. M. Mendonça
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  9. Juliana M. Ocarino
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Correspondence to Sergio T. Fonseca.

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This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES—Finance Code 001), the State of Minas Gerais Funding Agency—FAPEMIG, and the Brazilian Funding Agency—CNPq.

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Sergio Fonseca, Thales Souza, Evert Verhagen, Richard van Emmerik, Natalia Bittencourt, Luciana Mendonça, André Andrade, Renan Resende and Juliana Ocarino declare that they have no conflicts of interest relevant to the content of this review.

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SF proposed and wrote the first draft of the manuscript. TS and JO participated in the conception of the manuscript and provided input to the first draft. EV, RVE, NB, LM, AA and RR revised the original manuscript and provided input to subsequent drafts. All authors read and approved the final manuscript.

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Fonseca, S.T., Souza, T.R., Verhagen, E. et al. Sports Injury Forecasting and Complexity: A Synergetic Approach. Sports Med 50, 1757–1770 (2020). https://doi.org/10.1007/s40279-020-01326-4

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