ArticleFrontiers in sports and active living2025
Kernel Density Estimation: a novel tool for visualising training intensity distribution in biathlon.
Article in Frontiers in sports and active living, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Stroke rate-stroke length dynamics in elite freestyle swimming: application of kernel density estimation.Frontiers in sports and active living · 2025Article
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5 authors.
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Abstract
Purpose: This study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how KDE plots, alongside traditional training metrics, might provide a more detailed understanding of heart rate (HR) intensity patterns, aiding in the evaluation of training quality and compliance. Methods: Fifteen elite-level youth biathletes from two national academy programmes were monitored over 5-6 weeks using HR monitors. Training sessions were measured via time-in-zone (TIZ) within a five-zone HR model with any time accumulated below the threshold for Zone 1, considered Zone 0. Sessions were dichotomised into those planned as low-intensity training (LIT) or those planned with high-intensity training (HIT). KDE analyses were conducted in MATLAB (Version R2020b) using the " Results: For LIT sessions, athletes performed less time in Zone 1 than planned, while performed time exceeded planned time in Zone 2. For HIT sessions, performed time in Zone 5 was lower than planned. All sessions contained unplanned time in Zone 0. The 2D KDE plots provided a continuous and detailed representation of HR intensity accumulation throughout training sessions, revealing patterns and intensity fluctuations that complement traditional TIZ analyses. Conclusions: 2D KDE plots might serve as a valuable complementary tool for assessing TID in biathlon, offering a more nuanced and continuous view of HR intensity. By identifying discrepancies between planned and performed training intensity, coaches can refine strategies and provide individualised feedback. Incorporating KDE plots into training monitoring could improve training alignment, helping reduce overtraining or undertraining risks and optimising athlete development.
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