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Maximal aerobic speed (MAS) and knee extensor strength (KEf) significantly predict mountain ultra-marathon (MUM) performance. Training should focus on these factors, not just running economy, for better race times.

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Area of Science:

  • Sports Science
  • Exercise Physiology
  • Ultra-Endurance Performance

Background:

  • Mountain ultra-marathons (MUMs) present unique physiological demands.
  • Identifying key performance determinants is crucial for optimizing training.
  • Previous research often focused on running economy, with less emphasis on maximal aerobic capacity and muscular strength.

Purpose of the Study:

  • To identify the primary physiological factors influencing performance in male ultra-endurance mountain runners.
  • To investigate the relationship between maximal aerobic speed (MAS), running economy, muscular strength, and MUM performance.
  • To develop a predictive model for MUM performance based on key physiological variables.

Main Methods:

  • Twenty-four male ultra-runners were assessed for maximal aerobic speed (MAS), running economy at various intensities, knee extensor strength (KEf), and countermovement jump (CMJ) height.
  • These measures were taken before and after a 75 km MUM.
  • Performance time was correlated with physiological variables, and a multiple regression model was constructed.

Main Results:

  • Performance time was strongly correlated with MAS (r=-0.74) and the fraction of MAS sustained (FMAS) (r=-0.89).
  • Knee extensor strength (KEf) and its post-race loss also showed significant correlations with performance (r=-0.51).
  • Contrary to hypotheses, running economy (level and uphill) and its post-race changes did not correlate with performance.

Conclusions:

  • Maximal aerobic speed (MAS), fraction of MAS sustained (FMAS), and knee extensor strength (KEf) are critical determinants of MUM performance.
  • Training programs for MUMs should prioritize improvements in aerobic power and muscular strength over solely focusing on running economy.
  • A predictive model incorporating FMAS, MAS, and KEf explained 98% of the variance in performance time.