Machine Learning Project using Sk-learn to predict Sports Statistics.
Using raw data from pro-football-focus to predict rushing yards in the NFL. Nick Chubb is the use case, and various factors are used to predict his rushing yards in each of his career games. This data will then be compared to the actual rushing yards.
Methods: A regression model will be used from Sk-learn, and Auto-Gluon, to make predictions. There will be a training and test dataset. Training dataset will be train the model, and the test data will be used to collect the predicted yards.
Link to Data Document https://docs.google.com/spreadsheets/d/1f-0SyOjlpJRm5hSatzzLOE4kuQG1vYxCFgYWPu-3jf0/edit#gid=1757234728
Link to Notes Document https://docs.google.com/document/d/1AXeyPQSjCPXu5Y7xYkUMa7KVhcJBWwAJ0g0w-Bk7FVo/edit
Tools we are using https://scikit-learn.org/stable/index.html https://auto.gluon.ai/dev/tutorials/tabular_prediction/tabular-multilabel.html
NFL Data Sources https://www.pro-football-reference.com/years/2021/opp.htm
https://www.kaggle.com/code/xhlulu/ticket-price-prediction-with-scikit-learn/notebook