MODELING STABLE SPECIFIC WORK CAPACITY IN ACADEMIC ROWING UNDER PHASE-BASED LOAD CONDITIONS
DOI:
https://doi.org/10.31891/pcs.2025.2.25Keywords:
academic rowing, specific work capacity, stability of functional state, phase structure of distance, ergometric monitoring, individualization of training, programmatic-analytical approach, fatigue compensationAbstract
The article presents the rationale and practical implementation of a programmatic-analytical approach to the individualization of the training process in academic rowing, taking into account the phase-based dynamics of competitive load. Special attention is paid to analyzing the stability of specific work capacity in the context of maintaining a stable functional state during the execution of the 2000-meter race distance. The relevance of the issue lies in the necessity of accurate control over power output dynamics under increased physiological load, which is a key factor in the effective preparation of highly qualified athletes. The aim of the study was to determine individual profiles of functional stability based on phased ergometric analysis (0–2, 2–4, 4–6 minutes) and to apply these data in programming adaptive training loads. This objective was achieved through the use of a set of methods: theoretical analysis, pedagogical observation, functional testing, physiological monitoring (heart rate, blood lactate), ergometric measurements, and mathematical-statistical data processing using variation coefficients and interquartile distribution analysis. The results showed that athletes with high stability of work capacity exhibit lower variability in power output and more stable responses during loading phases, while less stable athletes demonstrate significant fluctuations in functional indicators. This made it possible to identify typical performance profiles and to develop a conceptual model of training adaptation based on the “control–modeling–programming” scheme. The data obtained can be used in practical coaching to improve individualized training programs, as well as in further research aimed at developing digital platforms for real-time assessment of functional state stability in athletes engaged in cyclic sports.
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