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Step frequency (SF) in running has received substantial interest from researchers, coaches, therapists, and runners. It has been widely studied in controlled settings, but no published study has measured it continuously in elite-level competition. The present study used wrist-based accelerometers in consumer-grade watches to monitor SF and SF variability of competitors in the 2016 100-km World Championship road race. Using linear mixed-model regression, SF and SF variability were assessed across the race. The average SF (steps-per-minute) of competitors ( n = 20) was 182.0 spm (range: 155.4–203.1 spm). Race fluctuations in SF were influenced only by the speed the competitors were running, with faster speeds being associated with greater SF (5.6 spm/m·s−1, P < 0.001). Independently of this speed relation, SF did not significantly change over the course of the race. SF was further linked to the runner's stature (−123.1 spm/m, P = 0.01) but not significantly related to sex, weight, age, or years of experience. The SF coefficient-of-variation was inversely associated with running speed and distance covered, with runners demonstrating decreasing variability both at faster speeds and as the race progressed. Together, these results add ecological evidence to observations of a speed dependency of SF in a highly trained, elite population of runners and suggest that in road race conditions, SF changes only with speed and not fatigue. Furthermore, it presents evidence that the variability of an elite runner's SF is linked to both speed and fatigue but not to any other characteristics of the runner. The current findings are important for runners, clinicians, and coaches as they seek to monitor or manipulate SF. NEW & NOTEWORTHY Stride frequency (SF; or the synonymous “cadence”) has become a popular point of monitoring and manipulation in runners. Advances in wearable technology have enabled continuous monitoring of SF. This study is the first to examine SF and SF variability patterns throughout an entire road race in elite ultramarathon runners. This adds ecological, normative data to the field's understanding of SF and demonstrates how it relates to running speed, fatigue, and individual characteristics.

Elite middle distance runners present as a unique population in which to explore biomechanical phenomena in relation to running speed, as their training and racing spans a broad spectrum of paces. However, there have been no comprehensive investigations of running mechanics across speeds within this population. Here, we used the spring-mass model of running to explore global mechanical behavior across speeds in these runners. Ten elite-level 1500 m and mile runners (mean 1500 m best: 3:37.3 ± 3.6 s; mile: 3:54.6 ± 3.9 s) and ten highly trained 1500 m and mile runners (mean 1500 m best: 4:07.6 ± 3.7 s; mile: 4:27.4 ± 4.1 s) ran on a treadmill at 10 speeds where temporal measures were recorded. Spatiotemporal and spring-mass characteristics and their corresponding variation were calculated within and across speeds. All spatiotemporal measures changed with speed in both groups, but the changes were less substantial in the elites. The elite runners ran with greater approximated vertical forces (+ 0.16 BW) and steeper impact angles (+ 3.1°) across speeds. Moreover, the elites ran with greater leg and vertical stiffnesses (+ 2.1 kN/m and + 3.6 kN/m) across speeds. Neither group changed leg stiffness with increasing speeds, but both groups increased vertical stiffness (1.6 kN/m per km/h), and the elite runners more so (further + 0.4 kN/m per km/h). The elite runners also demonstrated lower variability in their spatiotemporal behavior across speeds. Together, these findings suggested that elite middle distance runners may have distinct global mechanical patterns across running speeds, where they behave as stiffer, less variable spring-mass systems compared to highly trained, but sub-elite counterparts.

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