Multifractality of stride-to-stride variations in adolescent runners is sensitive to endurance training

This study investigated the impact of training on stride-to-stride variations in adolescent runners. It was hypothesised that training would significantly affect the magnitude and temporal structure of stride-to-stride variability during running. Twelve competitive adolescent runners (age: 16.3 ± 0.81) performed two 8-minute all-out running tests on a 400-m track, once at the start of the off-season (R<sub>1</sub>) and again after 6 weeks of structured training (R<sub>2</sub>). The study measured stride variability using the coefficient of variation (CV), monofractal analysis (DFA-α), and multifractal spectrum metrics (W and W<sub>Asym</sub>). No significant differences in CV and DFA-α between the two tests, suggesting stable magnitude and temporal structure of stride-to-stride variability in terms of monofractality. However, significant changes were observed in the multifractal spectrum, with a reduction in W and a shift in W<sub>Asym</sub> towards more symmetrical values after training. These results indicate that multifractal dynamics are a more sensitive metric to evaluate the effects of training on stride-to-stride variations in adolescent runners. The reduction of both W and W<sub>Asym</sub> leads to the assumption that alterations in neuromuscular control and adaptability in adolescent runners occurred due to training. Future research should further explore the utility of multifractal metrics in monitoring training progress and optimising performance in young athletes.

Authors

Institutions

Publication Details

Journal
Sports Biomechanics
Published
2025-09-16
DOI
https://doi.org/10.1080/14763141.2025.2552176
Primary Topic
Sports Performance and Training
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multifractality of stride-to-stride variations in adolescent runners is sensitive to endurance training

Christos Chalitsios, Nicholas Stergiou, Thomas Nikodelis
Sports Biomechanics
Sports Performance and Training
article

Multifractality of stride-to-stride variations in adolescent runners is sensitive to endurance training

Christos Chalitsios, Nicholas Stergiou, Thomas Nikodelis
article en

Abstract

This study investigated the impact of training on stride-to-stride variations in adolescent runners. It was hypothesised that training would significantly affect the magnitude and temporal structure of stride-to-stride variability during running. Twelve competitive adolescent runners (age: 16.3 ± 0.81) performed two 8-minute all-out running tests on a 400-m track, once at the start of the off-season (R<sub>1</sub>) and again after 6 weeks of structured training (R<sub>2</sub>). The study measured stride variability using the coefficient of variation (CV), monofractal analysis (DFA-α), and multifractal spectrum metrics (W and W<sub>Asym</sub>). No significant differences in CV and DFA-α between the two tests, suggesting stable magnitude and temporal structure of stride-to-stride variability in terms of monofractality. However, significant changes were observed in the multifractal spectrum, with a reduction in W and a shift in W<sub>Asym</sub> towards more symmetrical values after training. These results indicate that multifractal dynamics are a more sensitive metric to evaluate the effects of training on stride-to-stride variations in adolescent runners. The reduction of both W and W<sub>Asym</sub> leads to the assumption that alterations in neuromuscular control and adaptability in adolescent runners occurred due to training. Future research should further explore the utility of multifractal metrics in monitoring training progress and optimising performance in young athletes.

Sports BiomechanicsVol. 24(12)
University of Nebraska at Omaha (US), Aristotle University of Thessaloniki (GR)
Openalex Percentile: Top 68%
Sports Performance and Training
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.