This is the codebase for our final project in DS 502 (Fall 2025).
Our goal is to preemptively predict ACL injury for college athletes.
We are using the following dataset: https://www.kaggle.com/datasets/ziya07/athlete-injury-and-performance-dataset/data
See our final presentation here: https://docs.google.com/presentation/d/1lFzJDqKgKhq0uyFfrejo3gL4j6Si64Tk/edit?usp=sharing&ouid=112144393606313004477&rtpof=true&sd=true
See our final report: Final Report
- Bryan Drozda
- Weaver Goldman
- Hongchao Hu
- Ava Laughlin
- Gage Nagy
We are using uv for managing the Python project.
From inside this folder:
-
If you don't already have Python 3.12, use
uv python install 3.12 -
Build venv (installs packages):
uv sync
To add a package, use uv add <package-name>. DO NOT pip install it!
To activate the environment in VSCode, follow these instructions: astral-sh/uv#9637
Note: I've tried to add a bunch of common packages already. You can see which ones in pyproject.toml
Use uv run python src/acl-injury/main.py, or something equivalent for a different script.
To save the output, use uv run src/acl-injury/main.py > out.txt
I recommend using notebooks through VSCode. With this, you can easily write Python scripts and Jupyter notebooks in the same application.
To activate the environment in VSCode, follow these instructions: astral-sh/uv#9637