Hi I don't really know what your level is exactly but I would check out the following resources:
https://www.coursera.org/specializations/sports-analytics (course on using sport data)
https://www.kaggle.com/c/nfl-big-data-bowl-2021/data (NFL tracking data - check older data bowls for other types of data)
http://thespread.us/building-a-win-probability-model-part-1.html (building your own model and see how you do vs Vegas)
https://medium.com/@ross.blanchard/machine-learning-for-nfl-analysis-f3b591e571ef (same idea as the previous)
In general I would just follow a specific idea you have, predicting wins, QB metrics, etc. and just go from there. Get your hands dirty with some Pandas, Numpy, and then start training your models using the typical libraries like scikit-learn, XGBoost or PyTorch (Neural Networks). I found that learning by doing is the most effective, because otherwise I just seem to forget a large part of what I have been reading/listening to.
Hope this helps you. Good Luck