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Position-Independent Lactate Kinetic Phenotypes in Professional Soccer Players: A Machine Learning Approach for

Erkan Tortu¹, İzzet İnce², Salih Çabuk³

¹Department of Coaching Education, Faculty of Sport Sciences, Trabzon University, 61335 Trabzon, Türkiye.

Sensors (Basel, Switzerland)

|April 14, 2026

Summary

Professional soccer players exhibit distinct lactate kinetic phenotypes, with the "Economical Aerobic" group showing superior maximal running velocity. These metabolic profiles, identified via machine learning, may inform individualized training strategies beyond playing position.

Keywords:

anaerobic threshold explainable AI lactate kinetics machine learning metabolic phenotyping soccer

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Area of Science:

Sports Science
Exercise Physiology
Biochemistry

Background:

Lactate kinetics are crucial for understanding soccer player performance.
Individual metabolic differences may influence physiological responses during high-intensity exercise.
Current training strategies often overlook distinct metabolic profiles in athletes.

Purpose of the Study:

To identify distinct lactate kinetic phenotypes in professional soccer players using unsupervised machine learning.
To investigate the relationship between these phenotypes and maximal running velocity (Vmax) using explainable AI.
To explore the potential of metabolic phenotyping for individualized training strategies.

Main Methods:

Unsupervised machine learning (clustering) to identify lactate kinetic phenotypes.
Incremental treadmill tests to measure lactate concentrations, VO2max, Vmax, lactate threshold (LT), and anaerobic threshold (AT).
Ridge regression and explainable AI methods to determine predictors of Vmax.

Main Results:

Three distinct lactate kinetic phenotypes were identified: Economical Aerobic (n=216), Balanced Metabolic (n=19), and High Producer (n=126).
The Economical Aerobic phenotype exhibited significantly higher Vmax and VO2max compared to the High Producer phenotype.
Anaerobic threshold velocity (VAT) was the dominant predictor of Vmax, followed by VO2max and specific lactate concentrations.

Conclusions:

Lactate kinetic phenotyping reveals position-independent metabolic profiles associated with performance in professional soccer.
The Economical Aerobic phenotype is linked to superior anaerobic threshold capacity and performance advantages.
Individualized training strategies based on metabolic phenotype, rather than solely playing position, warrant further investigation for talent identification and periodization.