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Purpose <p>Performance analyses in cross-country skiing often focus on lap or terrain-level splits. However, few studies have explored micro-pacing strategies—particularly in Skiathlon, an Olympic event requiring athletes to complete both classical and freestyle techniques on the same course.</p> Methods <p>Thirteen national-level male skiers were tracked during an International Ski Federation-certified Skiathlon using GNSS and trunk-mounted sensors. Instantaneous speed profiles were analysed using one-dimensional statistical parametric mapping (SPM) to identify “race-critical clusters”: contiguous intervals where speed significantly predicted section time (α = 0.05) across all eight laps (four classical, four freestyle).</p> Results <p>Freestyle laps were 4% faster than classical, with greater terrain-specific speed differences and pacing variability in classical, especially downhills. Seven race-critical clusters were identified: two uphill, four downhill, and one flat. These accounted for 11.3&#xa0;s (classic) and 10.9&#xa0;s (freestyle) of the time gap between the fast and slow group. In these segments, faster skiers used higher-gear sub-techniques and exhibited longer cycle lengths and/or higher frequencies (<i>p</i> &lt; 0.05).</p> Conclusions <p>Within race-critical clusters, the faster skiers gained substantial time advantages. Secondary analyses showed clear differences in sub-technique selection and kinematic profiles, suggesting that technical execution plays a critical role in these performance gains. Athletes and coaches may consider integrating GNSS-based tracking, SPM, and wearable-derived technique analysis into race evaluation to move beyond traditional split times and focus training on the most decisive segments of the course.</p>

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Micro-pacing and performance determinants in skiathlon: linking speed profiles, sub-technique selection, and cycle characteristics

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月22日

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  • Lei Shang,
  • Hongjun Yu,
  • Ruiying Shi,
  • Dong Zhang,
  • Craig A. Staunton

摘要

Purpose

Performance analyses in cross-country skiing often focus on lap or terrain-level splits. However, few studies have explored micro-pacing strategies—particularly in Skiathlon, an Olympic event requiring athletes to complete both classical and freestyle techniques on the same course.

Methods

Thirteen national-level male skiers were tracked during an International Ski Federation-certified Skiathlon using GNSS and trunk-mounted sensors. Instantaneous speed profiles were analysed using one-dimensional statistical parametric mapping (SPM) to identify “race-critical clusters”: contiguous intervals where speed significantly predicted section time (α = 0.05) across all eight laps (four classical, four freestyle).

Results

Freestyle laps were 4% faster than classical, with greater terrain-specific speed differences and pacing variability in classical, especially downhills. Seven race-critical clusters were identified: two uphill, four downhill, and one flat. These accounted for 11.3 s (classic) and 10.9 s (freestyle) of the time gap between the fast and slow group. In these segments, faster skiers used higher-gear sub-techniques and exhibited longer cycle lengths and/or higher frequencies (p < 0.05).

Conclusions

Within race-critical clusters, the faster skiers gained substantial time advantages. Secondary analyses showed clear differences in sub-technique selection and kinematic profiles, suggesting that technical execution plays a critical role in these performance gains. Athletes and coaches may consider integrating GNSS-based tracking, SPM, and wearable-derived technique analysis into race evaluation to move beyond traditional split times and focus training on the most decisive segments of the course.