Machine Learning-Guided Training for Elite Athletes (MLGT) (MLGT)

June 27, 2026 updated by: Dr. Arefayne Mesfen Dessye, Debre Berhan University

A Machine Learning-Guided Training Approach to Reduce Injuries and Enhance Performance in Elite Athletes: A Prospective Cohort Evaluation

Plaintext The purpose of this study is to evaluate whether a personalized training protocol driven by machine learning can successfully reduce time-loss sports injuries and enhance athletic performance in elite athletes.

During a 9-month competitive sports season, a group of elite athletes was divided into two training

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

This study evaluated the efficacy of an adaptive, machine learning-driven training protocol compared to traditional athletic preparation over a full 9-month competitive sports season. The primary objective was to determine if a dynamic, technology-led approach to training load management could minimize time-loss injuries while concurrently optimizing athletic performance markers.

Participants were elite athletes randomly allocated into two parallel groups:

  1. The Experimental Group, which underwent training regimens dynamically adjusted using a machine learning algorithm that analyzed individual biomechanical data and historical workload parameters to optimize training volume and intensity.
  2. The Control Group, which followed standard, predetermined high-performance athletic training protocols typical for competitive season preparation.

Throughout the 9-month intervention period, daily tracking was maintained by technical and coaching staff. Data collection focused on the incidence, severity, and duration of all time-loss sports injuries. Concurrently, sport-specific performance parameters were periodically assessed to evaluate physical conditioning and competitive readiness. Statistical analyses were subsequently conducted to compare cumulative injury rates, total days lost to injury, and net performance adaptations between the two cohorts.

Study Type

Interventional

Enrollment (Actual)

120

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Ethiopia
    • Shewa
      • Debre Berhan, Shewa, Ethiopia, 445
        • Dr. Arefayne
      • Debre Berhan, Shewa, Ethiopia, 445
        • M Dessye

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  1. Must be a competitive, elite-level or sub-elite track and field athlete specializing in short-to-mid distance running events.
  2. Aged between 18 and 35 years old.
  3. Actively participating in structured athletic training programs for at least 2 years prior to enrollment.
  4. Free from any acute musculoskeletal injuries or medical conditions that prevent full participation in high-intensity training protocols.
  5. Capable and willing to provide written informed consent to participate in the study.

Exclusion Criteria: 1. Current or recent (within the past 3 months) major lower-limb injury or surgery that restricts maximal sprint or aerobic performance.

2. Concurrent use of performance-enhancing drugs or medications that influence metabolic or cardiovascular responses.

3. Inability to maintain consistent participation in the designated training protocols due to scheduling conflicts or travel.

4. Any underlying cardiovascular, respiratory, or systemic condition that creates a health risk during exhaustive exercise testing.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Prevention
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Active Comparator: Control Cohort
Elite adolescent sprinters who followed standard, predetermined high-performance athletic training protocols typical for competitive season preparation. This group received structured training volume and intensity matching standard athletic coaching guidelines, without any machine learning interventions or adaptive workload adjustments.
Behavioral: Adaptive Machine Learning Workload Optimization
A personalized, data-driven training intervention where athletic workloads are dynamically adjusted based on predictive modeling. The protocol continuously tracks individual physiological markers, biomechanical data, and workload history to optimize training volume and intensity. This adaptive approach aims to maximize performance gains while minimizing the risk of overtraining and injury during the competitive season.
Experimental: Algorithmic Cohort
Elite adolescent sprinters who received a personalized training protocol dynamically optimized by a machine learning algorithm. The framework evaluated individual biomechanical variables, morning heart rate variability (HRV), sleep quality, and physiological fatigue metrics to adjust training volume and intensity.
Behavioral: Adaptive Machine Learning Workload Optimization
A personalized, data-driven training intervention where athletic workloads are dynamically adjusted based on predictive modeling. The protocol continuously tracks individual physiological markers, biomechanical data, and workload history to optimize training volume and intensity. This adaptive approach aims to maximize performance gains while minimizing the risk of overtraining and injury during the competitive season.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Changes in Sprint Performance Time
Time Frame: 12 weeks
Sprint performance will be assessed using electronic timing gates to record running times over a specific distance from a stationary start. Lower times indicate improved sprint performance. Measurements will be taken at baseline and at the conclusion of the training intervention period to evaluate the impact of the workload protocols.
12 weeks

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Debre Berhan University

Investigators

  • Principal Investigator: Dr. Arefayne M Dessye, PhD, Debre Berhan Univeristy

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2023

Primary Completion (Actual)

September 30, 2023

Study Completion (Actual)

September 30, 2023

Study Registration Dates

First Submitted

June 27, 2026

First Submitted That Met QC Criteria

June 27, 2026

First Posted (Actual)

July 6, 2026

Study Record Updates

Last Update Posted (Actual)

July 6, 2026

Last Update Submitted That Met QC Criteria

June 27, 2026

Last Verified

June 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • DBU-SS-2023-008
  • IRB#DBU-SS-2023-008 (Registry Identifier: ClinicalTrials.gov)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

Individual participant data (IPD) will not be shared publicly to maintain the confidentiality of the elite athletes involved and to protect proprietary training protocols. Aggregated study results and statistical analyses will be available through academic publication.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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