This research presents an integrated quantitative framework for evaluating football players’ adherence to tactical roles compared to their assigned positions. By incorporating multimodal data sources, including Full HD video, wearable sensor information, and match context, the system employs deep learning algorithms such as YOLOv12 for player detection and tracking, mapping positional data onto a standardized 2D pitch model. Quantitative metrics, including individual position deviation, formation stability, zone compliance, and team compactness, are computed and joint into an overall tactical score. The results show that the system can detect subtle tactical deviations and offer real-time alerts, enabling coaches to make prompt strategic adjustments.