Author(s): DE WAAL, S., JACOBS, S., LAMBERTS, R., Institution: UNIVERSITY OF GLOUCESTERSHIRE, Country: UNITED KINGDOM, Abstract-ID: 1111

INTRODUCTION:
Pacing strategies during endurance efforts are learned behaviours which vary depending on athlete experience, race length, and terrain [1]. Previously, optimal ultra-trail marathon running pacing strategies have been described as ‘steadier’ [2] or by ‘limiting’ fluctuations in speed [3]. These pacing analyses were limited by electronic timing systems which use indiscriminate distances between checkpoints. Therefore, the aim of this study was to determine the pacing strategies and relative importance of uphill, downhill and level running for ultra-trail marathon performance in top 10 (TOP-10) runners and non-top 10 (NOT TOP-10) runners in a 100 km ultra-trail marathon.
METHODS:
Fifty male finishers (TOP-10: n = 6, NOT TOP-10, n = 44) and forty-six individual segments (1.5 ± 1.2 km) were analysed based on 2021 100 km UTCT STRAVA data. Twenty-three uphill (net gradient > 1.0%), 16 downhill (net gradient <-1.0%) and 7 level (net gradient between +1.0% - -1.0%) were analysed. Individual segment speeds, normalised to average race pace (segmentrel), and CV% were used to identify pacing strategies. Mann Whitney-U tests were used to compare TOP-10 and NOT TOP-10 finishers. Spearman Rank correlations were used to measure the association between overall race performance and uphill, downhill, and level running performance. Significance was set at p<0.05 for all tests.
RESULTS:
Uphill running had the strongest relationship with overall performance (r = 0.826, p <0.01). Substantially weaker relationships between overall running performance and level (r = 0.402, p<0.01) and downhill (r = -0.382, p<0.01) running performance were found. The CV% was significantly lower in TOP-10 (32.10 ± 1.81) than NOT TOP-10 (35.39 ± 4.43) (U = 24, r = 0.46, p <0.01), with both groups characterised by a positive pacing strategy. In 12 of the first 17 segments, TOP-10 finishers ran significantly slower (segmentrel) than NOT-TOP 10 finishers (p <0.05). Inversely, TOP-10 finishers ran 7 of the last 11 segments (segmentrel) quicker than NOT-TOP 10 finishers (p < 0.05).
CONCLUSION:
Uphill running performance remains a valuable measure of overall trail running performance as it represents a higher percentage of overall running demand. Sport scientists and laboratory technicians should continue to use uphill exercise tests to determine variation in ultra-trail marathon performance [4]. TOP-10 runners have diminished decay in initial running speed than NOT TOP-10 runners, despite a generally high variation in pace and net positive split in ultra-trail running. Neuromuscular fatigue [5] may contribute to the disparity in segmentrel between TOP-10 and NOT TOP-10 runners during the latter phases of an ultra-trail marathon.