Low reliability and high redundancy in inter-limb asymmetry: Effects of formula and variable selection

Inter-limb asymmetry monitoring is widely used for athletic performance and injury-risk assessment, yet the longitudinal psychometric impact of formula selection remains poorly understood. This study examined the methodological variability and reliability of ten commonly used inter-limb asymmetry formulas. Using a six-week, weekly repeated-measures design, thirty trained youth soccer players (age: 15.6 ± 1.07 years) completed unilateral countermovement jumps (CMJ) and unilateral flywheel leg press assessments, from which jump height and six concentric and eccentric power metrics were derived. Pearson correlation analysis revealed substantial mathematical redundancy, reducing the ten formulas to 3–4 distinct computational groups. The KOBAYASHI, ROBINSON, and WONG formulas showed the highest relative reliability (ICC: 0.152–0.367), although all formulas remained poor in absolute terms (ICC < 0.40). Mean concentric power emerged as the most reliable variable (ICC: 0.184–0.367). CMJ height asymmetries exhibited the lowest absolute thresholds for change (MDC 95 : 10.08–33.37), indicating comparatively greater sensitivity for detecting longitudinal adaptations than eccentric-phase metrics. Asymmetry magnitude and reliability therefore depend on both the formula and movement phase analyzed. Practitioners should prioritize CMJ height and mean concentric power for stable monitoring, and researchers should explicitly report formulas and their psychometric properties to ensure clarity and comparability across sports science studies.

Authors

Institutions

Publication Details

Journal
Human Movement Science
Published
2026-08-24
DOI
https://doi.org/10.1016/j.humov.2026.103526
Primary Topic
Sports injuries and prevention
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Low reliability and high redundancy in inter-limb asymmetry: Effects of formula and variable selection

David Falcón Miguel, Alejandro Moreno-Azze, Carlos D. Gómez‐Carmona, Daniel López-Plaza
Human Movement Science
Sports injuries and prevention
article

Low reliability and high redundancy in inter-limb asymmetry: Effects of formula and variable selection

David Falcón Miguel, Alejandro Moreno-Azze, Carlos D. Gómez‐Carmona, Daniel López-Plaza
article en

Abstract

Inter-limb asymmetry monitoring is widely used for athletic performance and injury-risk assessment, yet the longitudinal psychometric impact of formula selection remains poorly understood. This study examined the methodological variability and reliability of ten commonly used inter-limb asymmetry formulas. Using a six-week, weekly repeated-measures design, thirty trained youth soccer players (age: 15.6 ± 1.07 years) completed unilateral countermovement jumps (CMJ) and unilateral flywheel leg press assessments, from which jump height and six concentric and eccentric power metrics were derived. Pearson correlation analysis revealed substantial mathematical redundancy, reducing the ten formulas to 3–4 distinct computational groups. The KOBAYASHI, ROBINSON, and WONG formulas showed the highest relative reliability (ICC: 0.152–0.367), although all formulas remained poor in absolute terms (ICC < 0.40). Mean concentric power emerged as the most reliable variable (ICC: 0.184–0.367). CMJ height asymmetries exhibited the lowest absolute thresholds for change (MDC 95 : 10.08–33.37), indicating comparatively greater sensitivity for detecting longitudinal adaptations than eccentric-phase metrics. Asymmetry magnitude and reliability therefore depend on both the formula and movement phase analyzed. Practitioners should prioritize CMJ height and mean concentric power for stable monitoring, and researchers should explicitly report formulas and their psychometric properties to ensure clarity and comparability across sports science studies.

Human Movement ScienceVol. 109
University of Alicante (ES), Universidad de Zaragoza (ES)
No poverty
Openalex Percentile: Top 8%
Sports injuries and prevention
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.