Evidence map›Paper›PMID 42690493›Full record

SynthesisSports medicine - open2026

Reliability, Device Agreement and Validity of Load-Velocity Profiles: A Systematic Review with Meta-analysis.

Nina Claassen, Stanislav Dimitri Siegel, Mareike Sproll, Niklas Lebelt, Alyssa Virginia Bargende, Anne Marieke Fasold, Konstantin Warneke

Abstract readSystematic Review
In one paragraph

Synthesis in Sports medicine - open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Nina ClaassenInstitute of Human Movement Science and Exercise Physiology, University Osnabrück, Osnabrück, Germany.
Stanislav Dimitri SiegelInstitute of Human Movement Science and Exercise Physiology, Friedrich Schiller University Jena, Jena, Germany.
Mareike SprollInstitute of Human Movement Science and Exercise Physiology, University of Hamburg, Hamburg, Germany.
Niklas LebeltInstitute of Human Movement Science and Exercise Physiology, Friedrich Schiller University Jena, Jena, Germany.
Alyssa Virginia BargendeInstitute of Human Movement Science and Exercise Physiology, Friedrich Schiller University Jena, Jena, Germany.
Anne Marieke FasoldInstitute of Human Movement Science and Exercise Physiology, Friedrich Schiller University Jena, Jena, Germany.
Konstantin WarnekeInstitute of Sustainability Psychology, Leuphana University Lüneburg, Lüneburg, Germany. konstantin.warneke@uni-jena.de.ORCID http://orcid.org/0000-0003-4964-2867

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFor a valid one-repetition maximum (1RM) prediction via load-velocity (LV) relationships, high reliability and accuracy must be assumed.

objectiveSince individual study results indicate ambivalent prediction, this systematic review and meta-analysis was designed to provide a updated and comprehensive overview, extending knowledge about the validity and reliability of commercially available velocity sensors in Part I and the validity and reliability of velocity-based 1RM prediction models in Part II.

methodsA systematic literature search was conducted in PubMed/MEDLINE, Web of Science, and Scopus. Validity and/or reliability studies or velocity-based 1RM prediction evaluations were included. Methodological quality was assessed using adapted COSMIN. The analysis was performed for intraclass correlation coefficient (ICC), Lin's concordance correlation coefficient (CCC), and Pearson's correlation coefficient (r). The review was preregistered in PROSPERO (CRD42025634595).

resultsSixty-three studies were included for sensor validity and reliability and 38 for 1RM prediction models. Part I: Velocity sensors demonstrated good-to-excellent pooled validity and device agreement (ICC = 0.91-0.92 [0.83-0.97]; k = 55 and 439, respectively); intra- and inter-day reliability were classified as good to excellent with ICC = 0.90-0.91 [0.85-0.95] (k = 228 and 608, respectively), with sensor technology moderating the results. However, substantial heterogeneity and wide ranges of study-level estimates indicated considerable variability across moderators, linear position transducer (LPT) generally showing more consistent performance than inertial measurement units (IMU). Part II: Velocity-based 1RM prediction showed ICCs = 0.90 [0.83-0.94] (k = 124) and ICC = 0.91 [0.72-0.98] (k = 9); for reliability and validity, respectively. DISCUSSION: Commercial velocity sensors generally provide high relative validity and reliability. Results varied depending on exercise complexity, intensity, sensor technology, and modeling approach. While velocity-based 1RM prediction demonstrated high average validity, large heterogeneity in lower body exercises significantly biased the results. Furthermore, the dearth of measurement error and agreement analyses prohibits final conclusions.

conclusionTherefore, velocity-based monitoring and 1RM prediction require cautious interpretation, as sensor- and exercise-specific evidence remains limited.

Indexed as

Load–velocity relationshipMeasurement reliabilityMeasurement validityMeta-analysisMovement velocityOne-repetition maximum predictionResistance trainingVelocity-based trainingWearable sensors

Identifiers

PMID42690493
PMCPMC13542044

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.