Evidence map›Paper›PMID 42577324›Full record

ArticleFrontiers in sports and active living2026

Nonlinear interaction between stroke length and stroke rate in elite swimming.

Samer Mansoor Jameel

Abstract read
In one paragraph

Article in Frontiers in sports and active living, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 author.

Samer Mansoor JameelCollege of Physical Education and Sport Sciences, University of Baghdad, Baghdad, Iraq.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Competitive freestyle swimming performance depends on the interaction between stroke rate (SR) and stroke length (SL), yet this relationship has generally been examined using linear approaches. This study investigated the nonlinear biomechanical interaction between SR and SL to identify the conditions associated with maximal swimming velocity. Methods: Data were collected from fifty highly trained freestyle swimmers performing maximal-effort 50-m sprint trials. Swimming velocity was analyzed using polynomial regression, response-surface methodology, stationary-point analysis, and Hessian determinant testing to identify and verify optimal biomechanical interaction. Results: The nonlinear interaction model explained 68% of the variance in swimming velocity and improved predictive performance by 20% compared with the linear model. Response-surface optimization identified a constrained biomechanical interaction corridor rather than a single optimal combination of SR and SL. Stationary-point analysis, confirmed by the Hessian determinant, demonstrated that this region represented a statistically significant local maximum, providing evidence that swimming velocity is governed by nonlinear rather than purely additive relationships between SR and SL. Discussion: The findings demonstrate the value of integrating nonlinear regression, response-surface methodology, and mathematical optimization to characterize swimming biomechanics. The proposed analytical framework offers a reproducible approach for optimizing biomechanical performance and has practical applications in training prescription, performance monitoring, and future real-time coaching systems.

Indexed as

biomechanicsnonlinear regressionresponse surface methodologystroke lengthstroke rateswimming performance

Identifiers

PMID42577324
PMCPMC13454069

What Socratic holds

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LicenceCC BY
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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 Socratic graph.