@misc{10481/107538,
year = {2025},
month = {10},
url = {https://hdl.handle.net/10481/107538},
abstract = {Objectives: To analyse stroke rate (SR) and stroke length (SL) combinations
among elite swimmers to better understand stroke strategies across all race
distances of freestyle events.
Design: We analysed SR and SL data from 324 male and female swimmers
competing in all individual freestyle events (50 m to 1,500 m) at the 2019
European Short-Course Championships using video-based kinematic analysis.
Methods: Two-dimensional kernel density estimation (2D KDE) was applied to
visualise SR–SL combinations. Spearman correlations quantified relationships
between stroke parameters and speed by sex and race distance.
Results: In the 50 m sprint, SL showed the strongest positive correlation with
speed (men: ρ = 0.57; women: ρ = 0.50), while SR correlations were trivial. As
race distance increased, SR correlations with speed strengthened, reaching
moderate levels in long-distance events (men’s 1,500 m: ρ = 0.37; women’s
800 m: ρ = 0.45), whereas SL correlations weakened. The 2D KDE heatmaps
revealed an inverse SR–SL relationship, with medallists often employing
stroke strategies distinct from finalists and the broader field. Gold medallists
in sprint events favoured above-average SR without compromising SL, while
in middle- and long-distance races, a shift toward higher SR and reduced SL
was observed, particularly among women.
Conclusions: These findings highlight the complexity and individuality of stroke
mechanics at elite levels and suggest that superior conditioning and technique
enable medallists to sustain elevated SR without compromising SL. The
application of 2D KDE provides a novel, intuitive method to capture nuanced
biomechanical strategies, offering valuable insights for coaching and
performance optimisation.},
publisher = {Frontiers Media},
keywords = {biomechanical analysis},
keywords = {elite athletes},
keywords = {Kernel density estimation},
title = {Stroke rate–stroke length dynamics in elite freestyle swimming: application of kernel density estimation},
doi = {10.3389/fspor.2025.1656633},
author = {Staunton, Craig A. and Ruiz Navarro, Jesús Juan and Born, Dennis-Peter},
}