Smart Football: Object Detection Object Detection Dataset and Pre-Trained Model by Smart Football Object Detection

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Explore Dataset

Here are a few use cases for this project:

Sports Analytics: Use the Smart Football Object Detection model to analyze player performance, team tactics, and real-time statistics by tracking player movements, possession of the ball, passes, and interactions between team members during games.
Live Game Enhancements: Integrate the model into sports broadcasts or live streaming platforms, offering viewers real-time identification and tracking of players, ball, and referee. This can enhance the viewing experience and help viewers keep track of key players' performances.
Video Content Analysis: Automatically analyze and index recorded soccer matches, enabling users to find specific moments in a game (e.g., goals, assists, penalties) by searching for particular player actions, ball possession, or referee decisions.
Training and Coaching: Utilize the model to help coaches and team analysts review player performance during practice sessions or past matches. It facilitates identifying strengths and weaknesses in players and strategizing targeted improvement areas for individual and team development.
Injury Prevention: Use the model to monitor players' fatigue, positioning, and collisions in real-time, enabling medical and coaching staff to identify potential injury risks and take preventive action by adjusting players' training schedules or substituting them during games.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            smart-football-object-detection_dataset,
                            title = { Smart Football: Object Detection Dataset },
                            type = { Open Source Dataset },
                            author = { Smart Football Object Detection },
                            howpublished = { \url{ https://universe.roboflow.com/smart-football-object-detection/smart-football-object-detection } },
                            url = { https://universe.roboflow.com/smart-football-object-detection/smart-football-object-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-06-23 },
                            }