First, some background information.
- A regression problem is when your neural network outputs a continuous value. Think housing prices, stock market value, etc.
- A spread is sports is what the sports book think will be the difference in the final score of a game. For example, Team 1 ends with 24 points and Team 2 ends with 21 points the spread is -3 for Team 1
I am assuming that some readers could guess where this is going. After doing the DevPost project on college basketball I tried to mess around with NFL scores. Going in I knew that I wouldn’t actually get anything of value but it would be “fun” to try. Anyway, I started training my model and I was getting amazing results. I was within a quarter of a point. If I actually had a model that would do that I would be a billionaire and pretty much shut down the sports betting market.
Well, since I am still here and not on a personal island you can assume I messed up. It turns out that I had skipped the step where I removed the ACTUAL SCORE OF THE GAME from my training data. The network picked up on this and was ignoring all my other inputs.
Back to work, I guess.