MVP Predictor

Overview

MVP Predictor is a machine learning project designed to predict the Most Valuable Player (MVP) in the NBA based on various performance metrics and historical data.

Features

• Data collection and preprocessing
• Feature engineering
• Model training and evaluation

Live demo

You can see a live demo of the project here

Installation

1. Clone the repository:

   git clone https://github.com/SamuArg/NBA-MVP-predictor.git

Launch the Backend

1. Navigate to the backend directory:

   cd mvp-predictor/backend

2. Install the required dependencies:

   pip install -r requirements.txt

3. Create a .env with those this key : MONGOURI and write your own MONGO URI.
4. Run the wsgi.py file to start the backend.

   python wsgi.py

Launch the frontend

1. Navigate to the frontend directory:

   cd mvp-predictor/frontend

2. Install the required dependencies:

   npm install

3. If you run your own backend make sure to update the api url.

4. Launch the frontend

   npm run dev

Features to add

• Show shap forces to understand what stats impact the most the prediction
• Update season to season automatically

License

This project is licensed under the MIT License. See the LICENSE file for details.