WISD Hackathon

This code in this repository is part of a submission to the WISD Hackacthon. The purpose of this project was to perform analysis on teams transition tendencies by assessing their passing and driving habits.

Setup/Installation Requirements

The only requirements for this code are a computer, internet connection, and Python 3.0 or above To begin, download the repository and create a virtual environment. To install required libraries to virtual environment, run:

python3 -m pip install -r requirements.txt

If on Mac, may need to also install Xcode command line tools to run Streamlit:

xcode-select --install

Download Data

To download the data from AWS:

python3 download_data.py

• saves event and tracking data in data/games/gameId folders
• saves metadata in data/metadata folder
• the AWS credentials are not included in this repo

Preprocess Data

To get transition data and stats:

python3 get_transition_stats.py

• saves transition possession summaries in data/transition/possession_summaries.pkl
• saves transition passing stats in data/transition/pass_stats.pkl
• saves transition drive stats in data/transition/drive_stats.pkl
• saves all transition tracking data in data/transition/possessions_tracking/

To run Streamlit Application in web browser:

streamlit run transition_app/Home.py