Analytical FC Object Detection Dataset and Pre-Trained Model by Toij

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Explore Dataset

Here are a few use cases for this project:

Sports Analysis: The "Analytical FC" model could be used for in-depth match analysis. It could provide data on player performance, including time on the pitch, distance run, or even identifying specific interactions with the ball. Furthermore, tracking referees could ensure fair play by monitoring their position in relation to the play.
Game Highlights Creation: By identifying the key classes- player, referee, ball, and goalkeeper- this model can aid in automated generation of game highlights. The key moments such as goals, fouls, or saves could be pinpointed based on the simultaneous movements of the ball, players, and the referee.
Player Training and Development: Coaches could use this model to review and analyze players' performances during training or matches. It could provide insights like on-field positioning, reaction times and player-ball engagement.
Virtual Reality Gaming: In virtual reality sports games, "Analytical FC" could be used to create more lifelike simulations by modeling the actions of virtual players, referees, and the ball based on the real-world dataset.
Injury Prevention and Rehabilitation: By analyzing the movement and actions of players, the model could help in identifying unnatural movements or situations that typically lead to injuries. This could help in formulating injury prevention strategies and in guiding injured athletes' rehabilitation process.

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{ analytical-fc_dataset,
    title = { Analytical FC  Dataset },
    type = { Open Source Dataset },
    author = { Toij },
    howpublished = { \url{ https://universe.roboflow.com/toij/analytical-fc } },
    url = { https://universe.roboflow.com/toij/analytical-fc },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { aug },
    note = { visited on 2023-12-08 },
}