Research Article
Object Detection and Tracking for Football Data Analytics
@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
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.
