On uneven ground: embracing the challenges of inter-limb asymmetries and their assessment

Inter-limb asymmetry is often misinterpreted in sports and healthcare, with natural differences wrongly seen as problems requiring correction. Evidence linking asymmetries to injury is weak, and typical asymmetries of 5–15% are not usually harmful. Assessing asymmetries is complex; tests should align with sport-specific demands and be repeated over time to detect meaningful trends beyond normal variation. Practitioners should account for measurement error to ensure observed changes are significant. Individual analysis is more informative than group averages, which can mask important differences. Relying on arbitrary thresholds oversimplifies a continuous variable, so using ranges and interpreting raw limb data is vital. Similar asymmetry values may reflect different strength profiles, so tracking raw data helps ensure performance improvements. A decision-making framework is provided, emphasizing task specificity, data quality, temporal trends, and context. Practitioners should carefully evaluate whether correcting asymmetry is necessary, based on relevance, evidence, and practical outcomes.

Inter-limb asymmetry is often misinterpreted as a problem, though perfect symmetry is rare and not inherently ideal due to natural anatomical differences. Despite this, both social media and professionals often promote correcting asymmetries. Evidence linking asymmetries to injury or performance issues is weak and inconsistent. Many studies rely on indirect metrics rather than actual injury data, and reviews show no clear association between asymmetry and injury risk, especially under 15%. Similarly, performance outcomes like jumping or sprinting show mixed results.

Definition and Measurement. Inter-limb asymmetry refers to strength or performance differences between limbs, often measured using the Limb Symmetry Index (LSI) or asymmetry ratios. However, inconsistent formulas and terminology across studies complicate comparisons, highlighting the need for caution when interpreting findings.

Test Selection. Asymmetry is task- and metric-specific. Different tests (e.g., one- vs. two-legged CMJs) and metrics (e.g., jump height, impulse) yield different asymmetry results. Relevance should guide test selection, not availability. Multiple, sport-specific tests improve reliability.

Longitudinal Monitoring. Single-point assessments are unreliable due to natural variability. Repeated measurements over time help distinguish true changes from noise. Direction and magnitude of asymmetry can fluctuate, reinforcing the importance of ongoing monitoring.

Meaningful Change and Error. Changes must exceed measurement error to be meaningful. Even then, clinical relevance isn’t guaranteed. Concepts like the smallest worthwhile change (SWC) or minimal clinically important difference (MCID) can guide interpretation but require judgment and context-specific understanding.

Intra-individual Focus. Group averages often mask individual differences due to high variability in asymmetry metrics. Tracking within-athlete trends over time is more informative than comparing to population means, especially in small-sample research typical in sports science.

Avoid Arbitrary Thresholds. Dichotomizing continuous variables (e.g., classifying asymmetry as “high” or “low”) oversimplifies complex phenomena, reduces statistical power, and may misguide decisions. Thresholds often lack strong biological or empirical justification.

Use Ranges Over Point Values. Interpreting asymmetry data using confidence intervals or normal ranges is more accurate than relying on single values. This approach accounts for variability and enhances decision-making.

Include Raw Data. Asymmetry metrics alone can be misleading. Raw limb data reveal whether performance improvements are driven by actual gains or just changes in balance. Symmetry without strength is not necessarily beneficial.

Our framework offers a four-part lens—task specificity, temporal stability, measurement quality, and raw performance context—to guide practitioners in interpreting asymmetries effectively. Each athlete’s unique sport, role, and physiological profile must shape how asymmetries are assessed, ensuring a holistic, evidence-based strategy.

Practitioners must prioritize relevant, sport-specific assessments over indiscriminate data collection to avoid acting on irrelevant findings. A systematic evaluation process helps decide when intervention is warranted, considering factors like task relevance, evidence linking asymmetries to injury or performance, meaningful change thresholds, and raw performance levels. Tracking raw limb data over time, using multiple tests, accounting for measurement error, and interpreting asymmetries in context ensures more accurate, practical decisions. Practitioners should resist the urge to “correct” asymmetries or to infer they are automatically prejudicial to performance or injury risk.

This paper “On uneven ground: embracing the challenges of inter-limb asymmetries and their assessment” was published in Asymmetry.

Afonso J, Virgile A, Peña J, Jordan M, García-de-Alcaraz A, et al. On uneven ground: embracing the challenges of inter-limb asymmetries and their assessment. Asymmetry 2025(1):0004, https://doi.org/10.55092/asymmetry20250004.