Critical Fluctuations as an Early Warning Signal of Sports Injuries? A Proof of Concept Using Football Monitoring Data
Abstract Background There has been an increasing interest in the development and prevention of sports injuries from a complex dynamic systems perspective. From this perspective, injuries may occur following critical fluctuations in the psychophysiological state of an athlete. Our objective was to qu...
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SpringerOpen
2024-12-01
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| Series: | Sports Medicine - Open |
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| Online Access: | https://doi.org/10.1186/s40798-024-00787-5 |
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| author | Niklas D. Neumann Jur J. Brauers Nico W. van Yperen Mees van der Linde Koen A. P. M. Lemmink Michel S. Brink Fred Hasselman Ruud J. R. den Hartigh |
| author_facet | Niklas D. Neumann Jur J. Brauers Nico W. van Yperen Mees van der Linde Koen A. P. M. Lemmink Michel S. Brink Fred Hasselman Ruud J. R. den Hartigh |
| author_sort | Niklas D. Neumann |
| collection | DOAJ |
| description | Abstract Background There has been an increasing interest in the development and prevention of sports injuries from a complex dynamic systems perspective. From this perspective, injuries may occur following critical fluctuations in the psychophysiological state of an athlete. Our objective was to quantify these so-called Early Warning Signals (EWS) as a proof of concept to determine their explanatory performance for injuries. The sample consisted of 23 professional youth football (soccer) players. Self-reports of psychological and physiological factors as well as data from heart rate and GPS sensors were gathered on every training and match day over two competitive seasons, which resulted in an average of 339 observations per player (range = 155–430). We calculated the Dynamic Complexity (DC) index of these data, representing a metric of critical fluctuations. Next, we used this EWS to predict injuries (traumatic and overuse). Results Results showed a significant peak of DC in 30% of the incurred injuries, in the six data points (roughly one and a half weeks) before the injury. The warning signal exhibited a specificity of 95%, that is, correctly classifying non-injury instances. We followed up on this promising result with additional calculations to account for the naturally imbalanced data (fewer injuries than non-injuries). The relatively low F1 we obtained (0.08) suggests that the model's overall ability to discriminate between injuries and non-injuries is rather poor, due to the high false positive rate. Conclusion By detecting critical fluctuations preceding one-third of the injuries, this study provided support for the complex systems theory of injuries. Furthermore, it suggests that increasing critical fluctuations may be seen as an EWS on which practitioners can intervene. Yet, the relatively high false positive rate on the entire data set, including periods without injuries, suggests critical fluctuations may also precede transitions to other (e.g., stronger) states. Future research should therefore dig deeper into the meaning of critical fluctuations in the psychophysiological states of athletes. Key Points Complex Systems Theory suggests that sports injuries may be preceded by a warning signal characterized by a short window of increased critical fluctuations. Results of the current study showed such increased critical fluctuations before 30% of the injuries. Across the entire data set, we also found a considerable number of critical fluctuations that were not followed by an injury, suggesting that the warning signal may also precede transitions to other (e.g., healthier) states. Increased critical fluctuations may be interpreted as a window of opportunity for the practitioner to launch timely and targeted interventions, and researchers should dig deeper into the meaning of such fluctuations. |
| format | Article |
| id | doaj-art-37990be6bfbb4b52a45bae3c93bc3513 |
| institution | OA Journals |
| issn | 2198-9761 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | SpringerOpen |
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| series | Sports Medicine - Open |
| spelling | doaj-art-37990be6bfbb4b52a45bae3c93bc35132025-08-20T01:59:44ZengSpringerOpenSports Medicine - Open2198-97612024-12-0110111410.1186/s40798-024-00787-5Critical Fluctuations as an Early Warning Signal of Sports Injuries? A Proof of Concept Using Football Monitoring DataNiklas D. Neumann0Jur J. Brauers1Nico W. van Yperen2Mees van der Linde3Koen A. P. M. Lemmink4Michel S. Brink5Fred Hasselman6Ruud J. R. den Hartigh7Department of Psychology, Faculty of Behavioral and Social Sciences, University of GroningenDepartment of Human Movement Sciences, Faculty of Medical Sciences, University of Groningen, University Medical Center GroningenDepartment of Psychology, Faculty of Behavioral and Social Sciences, University of GroningenFootball Club GroningenDepartment of Human Movement Sciences, Faculty of Medical Sciences, University of Groningen, University Medical Center GroningenDepartment of Human Movement Sciences, Faculty of Medical Sciences, University of Groningen, University Medical Center GroningenBehavioral Science Institute, Radboud UniversityDepartment of Psychology, Faculty of Behavioral and Social Sciences, University of GroningenAbstract Background There has been an increasing interest in the development and prevention of sports injuries from a complex dynamic systems perspective. From this perspective, injuries may occur following critical fluctuations in the psychophysiological state of an athlete. Our objective was to quantify these so-called Early Warning Signals (EWS) as a proof of concept to determine their explanatory performance for injuries. The sample consisted of 23 professional youth football (soccer) players. Self-reports of psychological and physiological factors as well as data from heart rate and GPS sensors were gathered on every training and match day over two competitive seasons, which resulted in an average of 339 observations per player (range = 155–430). We calculated the Dynamic Complexity (DC) index of these data, representing a metric of critical fluctuations. Next, we used this EWS to predict injuries (traumatic and overuse). Results Results showed a significant peak of DC in 30% of the incurred injuries, in the six data points (roughly one and a half weeks) before the injury. The warning signal exhibited a specificity of 95%, that is, correctly classifying non-injury instances. We followed up on this promising result with additional calculations to account for the naturally imbalanced data (fewer injuries than non-injuries). The relatively low F1 we obtained (0.08) suggests that the model's overall ability to discriminate between injuries and non-injuries is rather poor, due to the high false positive rate. Conclusion By detecting critical fluctuations preceding one-third of the injuries, this study provided support for the complex systems theory of injuries. Furthermore, it suggests that increasing critical fluctuations may be seen as an EWS on which practitioners can intervene. Yet, the relatively high false positive rate on the entire data set, including periods without injuries, suggests critical fluctuations may also precede transitions to other (e.g., stronger) states. Future research should therefore dig deeper into the meaning of critical fluctuations in the psychophysiological states of athletes. Key Points Complex Systems Theory suggests that sports injuries may be preceded by a warning signal characterized by a short window of increased critical fluctuations. Results of the current study showed such increased critical fluctuations before 30% of the injuries. Across the entire data set, we also found a considerable number of critical fluctuations that were not followed by an injury, suggesting that the warning signal may also precede transitions to other (e.g., healthier) states. Increased critical fluctuations may be interpreted as a window of opportunity for the practitioner to launch timely and targeted interventions, and researchers should dig deeper into the meaning of such fluctuations.https://doi.org/10.1186/s40798-024-00787-5FootballComplex dynamic systemsNonlinear time series analysisInjury predictionDynamic complexityProcess monitoring |
| spellingShingle | Niklas D. Neumann Jur J. Brauers Nico W. van Yperen Mees van der Linde Koen A. P. M. Lemmink Michel S. Brink Fred Hasselman Ruud J. R. den Hartigh Critical Fluctuations as an Early Warning Signal of Sports Injuries? A Proof of Concept Using Football Monitoring Data Sports Medicine - Open Football Complex dynamic systems Nonlinear time series analysis Injury prediction Dynamic complexity Process monitoring |
| title | Critical Fluctuations as an Early Warning Signal of Sports Injuries? A Proof of Concept Using Football Monitoring Data |
| title_full | Critical Fluctuations as an Early Warning Signal of Sports Injuries? A Proof of Concept Using Football Monitoring Data |
| title_fullStr | Critical Fluctuations as an Early Warning Signal of Sports Injuries? A Proof of Concept Using Football Monitoring Data |
| title_full_unstemmed | Critical Fluctuations as an Early Warning Signal of Sports Injuries? A Proof of Concept Using Football Monitoring Data |
| title_short | Critical Fluctuations as an Early Warning Signal of Sports Injuries? A Proof of Concept Using Football Monitoring Data |
| title_sort | critical fluctuations as an early warning signal of sports injuries a proof of concept using football monitoring data |
| topic | Football Complex dynamic systems Nonlinear time series analysis Injury prediction Dynamic complexity Process monitoring |
| url | https://doi.org/10.1186/s40798-024-00787-5 |
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