Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security, IACIDS 2023, 23-25 November 2023, Lavasa, Pune, India

Research Article

Object Detection and Tracking for Football Data Analytics

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  • @INPROCEEDINGS{10.4108/eai.23-11-2023.2343216,
        author={Shankara Narayanan V and Syed Ashfaq Ahmed and Sneha Varsha M and Guruprakash J},
        title={Object Detection and Tracking for Football Data Analytics},
        proceedings={Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security, IACIDS 2023, 23-25 November 2023, Lavasa, Pune, India},
        publisher={EAI},
        proceedings_a={IACIDS},
        year={2024},
        month={3},
        keywords={object detection object tracking ball possession sports analytics yolo models},
        doi={10.4108/eai.23-11-2023.2343216}
    }
    
  • Shankara Narayanan V
    Syed Ashfaq Ahmed
    Sneha Varsha M
    Guruprakash J
    Year: 2024
    Object Detection and Tracking for Football Data Analytics
    IACIDS
    EAI
    DOI: 10.4108/eai.23-11-2023.2343216
Shankara Narayanan V1,*, Syed Ashfaq Ahmed1, Sneha Varsha M1, Guruprakash J1
  • 1: Department of Computer Science and Engineering, Amrita School of Computing, Coimbatore, Amrita Vishwa Vidyapeetham, India
*Contact email: cb.en.u4cse20656@cb.students.amrita.edu

Abstract

This paper presents a method of quantifying ball possession and its usage in foot- ball sports data analytics by using object detection and object tracking. After comparing the performance of YOLOv5 and YOLOv8 which are two state-of-the-art object detection models, the latter was chosen to be used along with BYTETrack for object detection and tracking. The input will be a video stream of a football game taken from a tactical camera which is passed to the object detection module. The detected objects are individually tracked and ball possession is calculated per player by assigning unique track-id for all players. Finally, aggregating player’s individual ball possession into their respective teams provides a way of estimating the team’s ball possession.