ArticleSports medicine - open2024
Critical Fluctuations as an Early Warning Signal of Sports Injuries? A Proof of Concept Using Football Monitoring Data.
Article in Sports medicine - open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Examining the use of experience sampling methods in sport psychology research: a scoping review.Frontiers in psychology · 2026Pooled it
- When evidence fails in real life: Rethinking sports injury rehabilitation and prevention.Brazilian journal of physical therapy · 2026Review
- Machine Learning and Non-Invasive Monitoring Technologies for Training Load Management in Women's Volleyball: A Scoping Review.Sports (Basel, Switzerland) · 2026Review
- A causal inference method for athletic injuries based on quantile threshold functions and latent Gaussian DAG models.Frontiers in public health · 2025Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundThere 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).
resultsResults 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 F
conclusionBy 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.
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