A comprehensive dataset of soccer event images for advancing automatic recognition systemsKaggle
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 c...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | Data in Brief |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340925002501 |
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| author | Jamal Hussain Shah Maira Afzal Samia Riaz Mussarat Yasmin Seifedine Kadry Fahad Ahmed Khokhar |
| author_facet | Jamal Hussain Shah Maira Afzal Samia Riaz Mussarat Yasmin Seifedine Kadry Fahad Ahmed Khokhar |
| author_sort | Jamal Hussain Shah |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9d2ca7676c82474185561eae9b6df4de |
| institution | OA Journals |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-9d2ca7676c82474185561eae9b6df4de2025-08-20T02:05:36ZengElsevierData in Brief2352-34092025-06-016011151810.1016/j.dib.2025.111518A comprehensive dataset of soccer event images for advancing automatic recognition systemsKaggleJamal Hussain Shah0Maira Afzal1Samia Riaz2Mussarat Yasmin3Seifedine Kadry4Fahad Ahmed Khokhar5Department of Computer Science, COMSATS University Islamabad, Wah Campus, PakistanDepartment of Computer Science, COMSATS University Islamabad, Wah Campus, PakistanDepartment of Computer Science, COMSATS University Islamabad, Wah Campus, PakistanDepartment of Computer Science, COMSATS University Islamabad, Wah Campus, PakistanDepartment of Applied Data Science, Noroff University College, Kristiansand, Norway; Artificial Intelligence Research Center (AIRC), Ajman University, Ajman 346, United Arab Emirates; Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon; MEU Research Unit, Middle East University, Amman 11831, JordanDepartment of Computer Science, COMSATS University Islamabad, Wah Campus, Pakistan; Department of Mathematics and Information, University of Florence, Florence 50134, Italy; Corresponding author.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.http://www.sciencedirect.com/science/article/pii/S2352340925002501Event-based datasetSports dataSoccer trendsSoccer visualizationSoccer classificationSoccer events |
| spellingShingle | Jamal Hussain Shah Maira Afzal Samia Riaz Mussarat Yasmin Seifedine Kadry Fahad Ahmed Khokhar A comprehensive dataset of soccer event images for advancing automatic recognition systemsKaggle Data in Brief Event-based dataset Sports data Soccer trends Soccer visualization Soccer classification Soccer events |
| title | A comprehensive dataset of soccer event images for advancing automatic recognition systemsKaggle |
| title_full | A comprehensive dataset of soccer event images for advancing automatic recognition systemsKaggle |
| title_fullStr | A comprehensive dataset of soccer event images for advancing automatic recognition systemsKaggle |
| title_full_unstemmed | A comprehensive dataset of soccer event images for advancing automatic recognition systemsKaggle |
| title_short | A comprehensive dataset of soccer event images for advancing automatic recognition systemsKaggle |
| title_sort | comprehensive dataset of soccer event images for advancing automatic recognition systemskaggle |
| topic | Event-based dataset Sports data Soccer trends Soccer visualization Soccer classification Soccer events |
| url | http://www.sciencedirect.com/science/article/pii/S2352340925002501 |
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