SportyPredict

Application that uses NBA Player Statistics to predict future outcomes. The user first selects an NBA player from a dropdown menu, then chooses a statistic to predict. Lastly, the user enters the value of the statistic and presses the 'Calculate' button to find out if the prediction could be strong.

Files:
api_documentation.py - Uses API-NBA REST API from RapidAPI and requests API to retrieve data.

mongodb_connect.py - Connects to MongoDB database and creates connection or table and adds records from API.

sportypredictWindow.py - Main application where user can interact with application to set predictions and receive results based on linear regression data.

Tools used for project: Python, MongoDB, TKinter, PyMongo, Numpy, sklearn, REST API, Git