Accuribet

A new way to bet on sports. Accuribet utilizes machine learning to predict the outcome of sporting events. We use 42-48 different data points to predict the outcome of a game. In our testing phase we have been able to predict the outcome of games with ~60% accuracy.

<a href="https://accuribet.win">View Live Website</a>
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<a href="https://github.com/day-mon/sports-betting-ai/issues/new">Report Bug</a>
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<a href="https://github.com/day-mon/sports-betting-ai/issues/new">Request Feature</a>

About The Project

This project was a final project for CS 1783 (Artificial Intelligence) at the University of Pittsburgh at Johnstown.

Built With

• Rust
• Postgres
• SolidJS
• TailwindCSS
• Tensorflow
• Redis

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Contributors

• Damon Montague
• Connor Smith
• Alexander Diaz