Kinesiology, Vol. 58 No. 1, 2026.
Izvorni znanstveni članak
https://doi.org/10.26582/k.58.1.2
Predicting race outcomes in elite swimming: Insights from the critical speed model
Renato Barroso
orcid.org/0000-0001-8112-6622
; University of Campinas, Department of Sport Sciences, School of Physical Education, Brazil
*
Bruna Lindman Bueno
orcid.org/0000-0002-0204-4176
; University of Campinas, Department of Sport Sciences, School of Physical Education, Brazil
Carl Foster
; Department of Exercise and Sport Science, University of Wisconsin-La Crosse, USA
Augusto Carvalho Barbosa
; Meazure Sport Sciences, Brazil
* Dopisni autor.
Sažetak
This study evaluated the Critical Speed (CS) model as a tool to predict performance during major swimming competitions. This is a retrospective observational study that used data publicly available. Data were collected from 40 elite swimmers (21 men, 19 women) across 60 data sets, and their performances in the finals of the 400 m, 800 m, and 1500 m freestyle events were analyzed. The CS model (including CS and D′) was calculated from the first two events and used to predict performance in the third. For men, the model used 400 m and 800 m data to predict 1500 m; for women, it used 400 m and 1500 m to predict 800 m. The model yielded reasonably accurate predictions, with a mean error of 6.3 ± 8.2 seconds (0.7 ± 1.0%) for men and -2.0 ± 3.0 seconds (-0.4 ± 0.6%) for women. Accuracy was higher for women, likely due to the use of interpolation rather than extrapolation. The CS model shows potential for real-time use in multi-event competitions, offering coaches and athletes a practical, low-cost tool for pacing strategies, opponent analysis, and performance forecasting using only in competition data. Despite some limitations, such as selection bias and uncontrolled variables, the CS model is a promising method for elite-level performance management, but its generalization to a broader population of athletes has not yet been attested.
Ključne riječi
performance prediction; critical speed; swimming
Hrčak ID:
348254
URI
Datum izdavanja:
30.6.2026.
Posjeta: 0 *