Corpus ID: 211020562

TRAP: A Predictive Framework for Trail Running Assessment of Performance

  title={TRAP: A Predictive Framework for Trail Running Assessment of Performance},
  author={Riccardo Fogliato and N. L. Oliveira and Ronald Yurko},
  journal={arXiv: Applications},
Trail running is an endurance sport in which athletes face severe physical challenges. Due to the growing number of participants, the organization of limited staff, equipment, and medical support in these races now plays a key role. Monitoring runner's performance is a difficult task that requires knowledge of the terrain and of the runner's ability. In the past, choices were solely based on the organizers' experience without reliance on data. However, this approach is neither scalable nor… Expand


Influence of sex and level on marathon pacing strategy. Insights from the New York City race.
Both men and women try to maintain an even pace profile along the marathon course, partly by avoiding an excessively fast start that might result in a pronounced decrease in the speed in the second half of the race. Expand
Effect of age and performance on pacing of marathon runners
The present study is the first one to observe an age × performance interaction on pacing; ie, older runners pace differently (smaller changes) than younger runners with similar race time. Expand
Pacing by winners of a 161-km mountain ultramarathon.
  • M. Hoffman
  • Mathematics, Medicine
  • International journal of sports physiology and performance
  • 2014
Variations in speed increase with high ambient temperatures, and the small decrease in segmental speed variability among top runners across the nearly 30 y of this study suggests that the best runners have improved at pacing this race. Expand
Pacing during an ultramarathon running event in hilly terrain
The absence of a significant correlation between overall performance and descriptors of pacing is novel and indicates that pacing in ultramarathons in trails and hilly terrain differs to other types of running events. Expand
Prediction Equations for Marathon Performance: A Systematic Review.
Heterogeneity of the data precludes the identification of a single "best" equation for marathon prediction equations, and runners should be wary of relying on a single equation to predict their performance. Expand
Predictor variables for a half marathon race time in recreational male runners
Variant variables of both anthropometry and training were related to half marathon race time in recreational male half marathoners and cannot be reduced to one single predictor variable. Expand
Age, Sex, and Finish Time as Determinants of Pacing in the Marathon
It is concluded that older, women, and faster are better pacers than younger, men, and slower marathoners, respectively, and coaches can use these findings to overcome such tendencies and increase the odds of more optimal pacing. Expand
Do non-elite older runners slow down more than younger runners in a 100 km ultra-marathon?
Athletes in age group 18–24 years were slower than athletes in most other age groups and there was no trend of slowing down for older athletes. Expand
Do gender differences in running performance disappear with distance?
There was a significant slope to the speed difference across distances in that longer distances were associated with greater differences, and the proposed metabolic advantage for women because of increased fat metabolism may be masked by regular feeding during endurance races. Expand
Impact of weather on marathon-running performance.
There is a progressive slowing of marathon performance as the WBGT increases from 5 to 25 degrees C, but performance is more negatively affected for slower populations of runners. Expand