Such integrative properties offer exceptional possibilities of subjective monitoring for outperforming any objective monitoring system. CAS contain higher-order perceptual units that provide continuous and multilevel integrated information about performer–environment interactions. The objective of this paper is to reorient the current integrative proposals of sports monitoring by re-conceptualizing athletes as complex adaptive systems (CAS).
However, the application of algorithms, predicated on mechanistic assumptions of how athletes operate, cannot capture, assess and adequately promote athletes’ health and performance. Therefore, this thesis proposes updating, on the basis of a complex systems approach, the current theoretical assumptions and methodological techniques of sports monitoring.Ĭurrent trends in sports monitoring are characterized by the massive collection of tech-based biomechanical, physiological and performance data, integrated through mathematical algorithms.
#Spontaneous processes series
The used time series analysis techniques, taken at individual level, supposed an actionable and effective way to assess athlete’s behaviour and improve the understanding of the studied phenomena. The applied methods and techniques have shown their potential to capture: a) the psychobiological stress and exercise tolerance through the hysteresis area of heart rate and the rate of perceived exertion, b) the fatigue-induced exhaustion and the exercising flow state through the time-variability of acceleration, and c) the multilevel coordination of dyads through the analysis of synergies. Four published research articles are included, studying the properties of hysteresis, variability and synergies in diverse phenomena: workload stress and tolerance, fatigue-induced exhaustion, exercising flow state, and the relation between intra- and interpersonal synergies in a dyadic task. This thesis, conceptualizing athletes as complex adaptive systems (CAS), aims to propose methods and data analysis techniques for assessing CAS’ properties, and approach sport-related phenomena accordingly.
Sports monitoring, based on excessively simplistic theoretical assumptions and methodological techniques, has limitations for capturing and assessing athletes’ behaviour.