Extracted Study-Level Metadata for Machine Learning in Football Performance Analysis: A Systematic Review

This dataset contains extracted study-level metadata for 64 studies included in the systematic review Machine Learning in Football Performance Analysis. The dataset includes study identifiers, reference numbers, authors, year, title, sample size, sample unit, data modality, machine-learning family, measure/output, reported metric or value where available, data provider, region, risk-of-bias rating, and DOI/URL. It was prepared from the review’s supplementary material to support transparency, reproducibility, and future updating of the review.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-18
DOI
https://doi.org/10.5281/zenodo.20740519
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
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article

Extracted Study-Level Metadata for Machine Learning in Football Performance Analysis: A Systematic Review

Abdul Hadi Mohamad, David Asirvatham, Chun Hang Lee
Zenodo (CERN European Organization for Nuclear Research)
Sports Analytics and Performance
article

Extracted Study-Level Metadata for Machine Learning in Football Performance Analysis: A Systematic Review

Abdul Hadi Mohamad, David Asirvatham, Chun Hang Lee
article en

Abstract

This dataset contains extracted study-level metadata for 64 studies included in the systematic review Machine Learning in Football Performance Analysis. The dataset includes study identifiers, reference numbers, authors, year, title, sample size, sample unit, data modality, machine-learning family, measure/output, reported metric or value where available, data provider, region, risk-of-bias rating, and DOI/URL. It was prepared from the review’s supplementary material to support transparency, reproducibility, and future updating of the review.

Zenodo (CERN European Organization for Nuclear Research)
Asia School of Business (MY), Taylor's University (MY)
Gender equality
Openalex Percentile: Top 2%
Sports Analytics and Performance
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