I’m a bit of a sports nut and completing my final year in a computer science degree. I have a small project around machine learning and, while I understand some of the concepts, I struggle with implementation.
- All NBA Basketball games for the last 3 years
- Results, etc
- Player statistics - height, etc
- Statistics per game
- Speciality stats
- Was travel involved between games (Distance)
What I don’t understand is how to structure this. I want to build a model that can give the team and available players to and it be able to gauge the outcome. I have been looking into linear regression for this.
How do I uniquely identify a team? At the moment I have coded them by a unique identifier (eg. LAL = Lakers). Does the model learn that the statistics for LAL are unique for their own performances? How do I structure the data / model so the model know “When LAL plays it is informed by LAL historic performances”.
Also - how does a model go about weighting performances … for example, a teams result in the last 5 games is more important than what happened 4 months ago. ?
Fascinating concepts. Loving it and really appreciative of anyone who is prepared to give me a bit of their time to help understand this. Any notebooks with similar concepts would be greatly appreciated.