Evidence map›Paper›PMID 41978037›Full record

ArticleSensors (Basel, Switzerland)2026

Position-Independent Lactate Kinetic Phenotypes in Professional Soccer Players: A Machine Learning Approach for Maximal Running Velocity Prediction.

Erkan Tortu, İzzet İnce, Salih Çabuk, Süleyman Ulupınar, Cebrail Gençoğlu, Serhat Özbay, Kaan Kaya

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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
–field-weighted citation impact
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

7 authors.

Erkan TortuDepartment of Coaching Education, Faculty of Sport Sciences, Trabzon University, 61335 Trabzon, Türkiye.ORCID 0000-0003-2816-9994
İzzet İnceDepartment of Coaching Education, Faculty of Sport Sciences, Ankara Yildirim Beyazit University, 06010 Ankara, Türkiye.ORCID 0000-0002-6566-5201
Salih ÇabukDepartment of Coaching Education, Faculty of Sport Sciences, Erzurum Technical University, 25050 Erzurum, Türkiye.ORCID 0000-0003-4148-9781
Süleyman UlupınarDepartment of Coaching Education, Faculty of Sport Sciences, Erzurum Technical University, 25050 Erzurum, Türkiye.ORCID 0000-0002-9466-5278
Cebrail GençoğluDepartment of Coaching Education, Faculty of Sport Sciences, Erzurum Technical University, 25050 Erzurum, Türkiye.ORCID 0000-0002-0990-9224
Serhat ÖzbayDepartment of Physical Education and Sports, Faculty of Sport Sciences, Erzurum Technical University, 25050 Erzurum, Türkiye.ORCID 0000-0001-6424-8871
Kaan KayaDepartment of Coaching Education, Faculty of Sport Sciences, Istanbul Yeni Yuzyil University, 34010 Istanbul, Türkiye.ORCID 0000-0003-0892-645X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to identify distinct lactate kinetic phenotypes in professional soccer players using unsupervised machine learning and determine their relationship with maximal running velocity (V

Indexed as

Lactic AcidMachine LearningRunningSoccerAnaerobic ThresholdExercise TestHumansKineticsMaleOxygen ConsumptionPhenotypePredictive Learning ModelsLactic Acidanaerobic thresholdexplainable AIlactate kineticsmachine learningmetabolic phenotypingsoccer

Identifiers

PMID41978037
PMCPMC13075250

What OpenQuestion holds

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Registered trials

None linked

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.