Running Variability in Marathon-Evaluation of the Pacing Variables.
Medicina (Kaunas)
; 60(2)2024 Jan 26.
Article
in En
| MEDLINE
| ID: mdl-38399506
ABSTRACT
Background and Objectives:
Pacing analyses for increasingly popular long-distance running disciplines have been in researchers' spotlight for several years. In particular, assessing pacing variability in long-distance running was hardly achievable since runners must repeat long-running trials for several days. Potential solutions for these problems could be multi-stage long-distance running disciplines. Therefore, this study aimed to assess the long-distance running variability as well as the reliability, validity, and sensitivity of the variables often used for pacing analyses. Materials andMethods:
This study collected the split times and finish times for 20 participants (17 men and three women; mean age 55.5 years ± 9.5 years) who completed the multiday marathon running race (five marathons in 5 days), held as part of the Bretzel Ultra Tri in Colmar, France, in 2021. Seven commonly used pacing variables were subsequently calculated Coefficient of variation (CV), Change in mean speed (CS), Change in first lap speed (CSF), Absolute change in mean speed (ACS), Pace range (PR), Mid-race split (MRS), and First 32 km-10 km split (32-10).Results:
Multi-stage marathon running showed low variability between days (Intraclass correlation coefficient (ICC) > 0.920), while only the CV, ACS, and PR variables proved to have moderate to good reliability (0.732 < ICC < 0.785). The same variables were also valid (r > 0.908), and sensitive enough to discern between runners of different performance levels (p < 0.05).Conclusions:
Researchers and practitioners who aim to explore pacing in long-distance running should routinely utilize ACS, CV, and PR variables in their analyses. Other examined variables, CS, CSF, MRS, and 32-10, should be used cautiously. Future studies might try to confirm these results using different multi-stage event's data as well as by expanding sensitivity analysis to age and gender differences.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Running
/
Athletic Performance
Limits:
Female
/
Humans
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Male
/
Middle aged
Language:
En
Journal:
Medicina (Kaunas)
Journal subject:
MEDICINA
Year:
2024
Type:
Article