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. 2023 Dec 21:14:1273451.
doi: 10.3389/fpsyg.2023.1273451. eCollection 2023.

The pacing differences in performance levels of marathon and half-marathon runners

Ljubica Ristanović  1 , Ivan Cuk  1 , Elias Villiger  2 , Stanimir Stojiljković  1 , Pantelis T Nikolaidis  3   4 , Katja Weiss  5 , Beat Knechtle  5   6
Affiliations

The pacing differences in performance levels of marathon and half-marathon runners

Ljubica Ristanović et al. Front Psychol. .

Abstract

Introduction: Many studies indicate a considerable impact of optimal pacing on long-distance running performance. Given that the amount of carbohydrates in metabolic processes increases supralinearly with the running intensity, we may observe differences between the pacing strategies of two long-distance races and different performance levels of runners. Accordingly, the present study aimed to examine the differences in pacing strategies between marathon and half-marathon races regarding the performance levels of runners.

Methods: The official results and split times from a total of 208,760 (marathon, N = 75,492; half-marathon, N = 133,268) finishers in the "Vienna City Marathon" between 2006 and 2018 were analyzed. The percentage of the average change of speed for each of the five segments (CS 1-5), as well as the absolute change of speed (ACS) were calculated. The CS 1-5 for the marathon are as follows: up to the 10th km, 10th - 20th km, 20th - 30th km, 30th - 40th km, and from the 40th km to the 42.195 km. For the half-marathon, the CS 1-5 are half of the marathon values. Four performance groups were created as quartiles of placement separately for sexes and races: high-level (HL), moderate to high-level (MHL), moderate to low-level (MLL), and low-level (LL).

Results: Positive pacing strategies (i.e., decrease of speed) were observed in all performance groups of both sex and race. Across CS 1-5, significant main effects (p < 0.001) were observed for the segment, performance level, and their interaction in both sex and race groups. All LL groups demonstrated higher ACS (men 7.9 and 6.05%, as well as women 5.83 and 5.49%, in marathon and half-marathon, respectively), while the HL performance group showed significantly lower ACS (men 4.14 and 2.97%, as well as women 3.16 and 2.77%, in marathon and half-marathon, respectively). Significant main effects (p < 0.001) for the race were observed but with a low effect size in women (ŋ2 = 0.001).

Discussion: Better runners showed more even pacing than slower runners. The half-marathoners showed more even pacing than the marathoners across all performance groups but with a trivial practical significance in women.

Keywords: endurance; long-distance races; running; speed; strategy; variability.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Average speed change in each race segment of men, calculated as a percent change of the mean race speed in marathon and half-marathon. Performance groups: LL, Low-Level; MLL, Moderate to Low-Level; MHL, Moderate to High-Level; HL, High-Level.
Figure 2
Figure 2
Average change of speed in each race segment of women, calculated as a percent change of the mean race speed in marathon and half-marathon. Performance groups: LL, Low-Level; MLL, Moderate to Low-Level; MHL, Moderate to High-Level; HL, High-Level.
Figure 3
Figure 3
Absolute change of speed in men’s marathon and half-marathon runners. Performance groups: LL, Low-Level; MLL, Moderate to Low-Level; MHL, Moderate to High-Level; HL, High-Level. Error bars represent standard deviation. ** p < 0.001; ## p < 0.001.
Figure 4
Figure 4
Absolute change of speed in women’s marathon and half-marathon runners. Performance groups: LL, Low-Level; MLL, Moderate to Low-Level; MHL, Moderate to High-Level; HL, High-Level. Error bars represent standard deviation. ** p < 0.001; ## p < 0.001.
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