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Running Variability in Marathon-Evaluation of the Pacing Variables
Ivan Cuk1, Srdjan Markovic2, Katja Weiss3
1Faculty of Sport and Physical Education, University of Belgrade, 11000 Belgrade, Serbia.
Medicina (Kaunas, Lithuania)
|February 24, 2024
Summary
This study found that Absolute Change in Mean Speed (ACS), Coefficient of Variation (CV), and Pace Range (PR) are reliable and valid for analyzing pacing in multi-stage marathons. These variables effectively differentiate runner performance levels.
Area of Science:
- Sports Science
- Exercise Physiology
- Running Biomechanics
Background:
- Pacing analysis is crucial for understanding long-distance running performance.
- Assessing pacing variability traditionally required repetitive long-running trials.
- Multi-stage running events offer a practical alternative for pacing research.
Purpose of the Study:
- To evaluate the variability in multi-stage marathon running.
- To determine the reliability, validity, and sensitivity of common pacing variables.
- To identify optimal pacing metrics for long-distance running research.
Main Methods:
- Collected split and finish times from 20 participants in a 5-day marathon event.
- Calculated seven pacing variables: CV, CS, CSF, ACS, PR, MRS, and 32-10.
- Assessed reliability, validity, and sensitivity using statistical analyses (ICC, correlation, p-values).
Main Results:
- Multi-stage marathons exhibited low day-to-day variability (ICC > 0.920).
- ACS, CV, and PR demonstrated moderate to good reliability (0.732 < ICC < 0.785).
- ACS, CV, and PR were valid (r > 0.908) and sensitive to performance differences (p < 0.05).
Conclusions:
- ACS, CV, and PR are recommended for pacing analysis in long-distance running research.
- Variables CS, CSF, MRS, and 32-10 should be used with caution due to lower reliability.
- Future research should validate these findings across different events and demographics.
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