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Class-specific time factors (TFs) are applied across para-biathlon race formats and course profiles, but their evaluation requires an understanding of the competitions in which they are used. We examined race-score variability, skiing contribution and lap-speed profiles across Sprint, Middle and Long events at the relatively flatter 2022 (WC22) and hillier 2023 (WC23) world championships. Analyses included all 147 starts from 42 sitting-class athletes (16 women, 26 men). Mixed-effects models accounted for repeated starts and sex; paired athlete-level resampling quantified uncertainty in raw-to-adjusted coefficients of variation (CVs). TF adjustment reduced CV in nine of twelve sex-by-format-by-championship comparisons by 1.61–3.62% points. Mean adjusted CV was higher at WC23 (9.57%) than WC22 (8.52%), although the observed pattern depended on format: adjusted CV was higher at WC23 in Sprint and Middle but lower in Long for both sexes. Skiing contribution was 2.31% points greater at WC23 (95% CI 0.96 to 3.65), and the model-estimated average first-to-final lap-speed increase was 4.84 points greater (2.97 to 6.71). NoTF and ModTF had similar estimated championship differences in pacing; LargeTF estimates were smaller and less precise. Interactions did not establish different championship or format responses between TF groups. Complete lap profiles differed between championships in all three formats. These findings show that race demands and the dispersion of adjusted results vary across the competition contexts in which common TFs are applied. These findings support evaluating TFs against race format, course demands and penalty conventions. The apparently smaller difference between championships in LargeTF athletes’ first-to-final lap-speed change also warrants further investigation.
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Rispal et al. (2026) studied this question.
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