This Python program generates models to predict an NBA player's preformance based on their preformance in previous game/seasons. Perfect for Fantasy Sports.
This project uses Ananconda
conda create -n nbaApp python=3.7
activate nbaApp
Install the necessary packages
pip install tensorflow sklearn numpy keras
Run program
//Navigate to directory with main.py
python main.py
This is used to predict how a player will preform through an entire season. The Model is trained from taking historical data (Can be changed to range up to the 1950s depending on CPU preformance) of all NBA players. Contains an option to filter the training data by model if user believes that it would lead to a more accurate result (Positionless basketball is the currently the META so I decided to leave this optional). This Model currently predicts player stats for the 2020-2021 season.
This is used to predict how a player will preform for their next game. The model is trained from taking data from the static model along with game stats of a certain player for the current season. When indicated to enter a URL, enter the per game stats of given player from ESPN.com.