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Kernel Density Estimation: a novel tool for visualising training intensity distribution in biathlon
Craig A Staunton1,2, Andreas Kårström1,3, Hannes Kock1,4
1Department of Health Sciences, Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden.
Frontiers in Sports and Active Living
|July 7, 2025
Summary
Two-dimensional Kernel Density Estimation (KDE) plots offer a detailed view of training intensity distribution in biathlon. These plots help coaches evaluate training quality and athlete responses, improving program effectiveness.
Area of Science:
- Sports Science
- Biathlon Training Monitoring
- Data Visualization Techniques
Background:
- Traditional training metrics like time-in-zone (TIZ) provide a basic overview of training intensity distribution (TID).
- Elite youth biathletes require precise monitoring to optimize performance and prevent over/undertraining.
- A more detailed visualization of heart rate (HR) intensity patterns could enhance the evaluation of training quality and compliance.
Purpose of the Study:
- To introduce two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel method for visualizing TID in biathlon.
- To assess the utility of KDE plots in providing a more detailed understanding of HR intensity patterns compared to traditional metrics.
- To evaluate how KDE plots can aid in assessing training quality and compliance in elite youth biathletes.
Main Methods:
- Fifteen elite youth biathletes were monitored for 5-6 weeks using HR monitors.
- Training sessions were analyzed for time-in-zone (TIZ) within a five-zone HR model, with time below Zone 1 classified as Zone 0.
- 2D KDE plots were generated using MATLAB to visualize HR intensity accumulation, alongside traditional histogram and bar chart analyses.
Main Results:
- Athletes accumulated less time in Zone 1 and more in Zone 2 during planned low-intensity training (LIT) sessions.
- Performed time in Zone 5 was lower than planned during high-intensity training (HIT) sessions.
- All sessions showed unplanned time in Zone 0, with 2D KDE plots revealing continuous HR intensity patterns.
Conclusions:
- 2D KDE plots offer a nuanced, continuous view of HR intensity, complementing TIZ analyses for biathlon training monitoring.
- Identifying discrepancies between planned and actual training intensity allows coaches to refine strategies and provide individualized feedback.
- Integrating KDE plots can improve training alignment, mitigate risks of over/undertraining, and optimize athlete development.
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