Hi, I'm Saiem! ML Engineer
I gave a presentation on the projects below at the Carnegie Mellon Sports Analytics Conference. The paper I wrote for the conference was selected as the winner for the Data and Software contribution, Open Track for their reproducible research competition.
The conference materials can be found here:
Honestly, I am working on so many sports data projects that should have only taken me a couple weeks.
- sportsdataverse node.js source (Docs)
- sportsdataverse-py source (Docs, PyPI)
- cfbfastR source (Docs, Data)
- hoopR source (Docs, Data)
- wehoop source (Docs, Data)
- recruitR source (Docs)
- usfootballR source (Docs)
Projects I contribute to:
They generally fall under the umbrella of the concept of the SportsDataverse. The general goal is to make sports data significantly more open and accessible, streamlining the process of gathering public data for research.