A comprehensive dataset of soccer event images for advancing automatic recognition systems

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-03-22 DOI:10.1016/j.dib.2025.111518

Jamal Hussain Shah , Maira Afzal , Samia Riaz , Mussarat Yasmin , Seifedine Kadry , Fahad Ahmed Khokhar

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引用次数: 0

Abstract

This article presents a detailed overview of a dataset, created for in-depth analysis of soccer events. This dataset will serve as a foundation for researchers and practitioners in the field, providing a perspective on different soccer events under various views. This soccer dataset is designed to categorize soccer matches into various events and contains 187,151 instances divided across 14 groups. To make this dataset simple, it is separated into two main datasets. The first dataset is known as the “View-Based Dataset.” which is divided into four categories: Long view, Medium view, Short view, and Outer view, for a total of 137,196 images. The second dataset is the “Event-Based Dataset,” which has 10 separate classes that highlight multiple soccer events Red card, Spectator, Yellow card, Plenty stock, Player celebration, Offside, Goal attempt, Goal, and Free kick for a total of 38,728 images. Each class in both datasets helps to provide a full understanding of soccer events. This dataset can serve as a foundation for future video analysis studies, promoting progress in soccer analytics and related domains.

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.