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Related Experiment Video

Updated: Jan 9, 2026

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

AI-Based Performance Analysis for Track and Field Athletes.

Mostafa Habibi, Mehrdad Nourani, Mohammad Mehdi Nourani

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|December 3, 2025

Summary

This summary is machine-generated.

This study introduces an AI-powered system for ranking track and field athletes using historical race data. Coaches can now quantify athlete performance and predict competition readiness with this data-driven tool.

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Last Updated: Jan 9, 2026

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Area of Science:

Sports Science
Artificial Intelligence
Data Analytics

Background:

Traditional performance evaluation in track and field relies on manual analysis.
Lack of objective, data-driven tools hinders accurate athlete assessment and progress tracking.
Predicting athlete consistency and competitive potential remains a challenge for coaches.

Purpose of the Study:

To develop and present an AI-driven methodology for performance analysis and ranking of track and field athletes.
To provide coaches with a tool for quantifying athlete progress during training.
To enable data-driven predictions of athlete competitiveness for future events.

Main Methods:

Utilized historical race data from the TFRRS database.
Curated and extracted key statistical features from athlete records.
Trained a neural network clustering (ART2) technique for performance analysis.

Main Results:

Developed a methodology to map athlete records to performance clusters.
The AI model provides a data-driven approach to ranking athletes.
Enabled quantification of athlete performance and progress.

Conclusions:

The proposed AI methodology offers a novel, data-driven solution for track and field performance analysis and ranking.
Coaches can leverage this tool to objectively assess athletes and predict their competitive performance.
This approach enhances training efficiency and strategic planning for competitions.