Machine-learning predictions for Draft Kings (NBA) :)
It scraped basically every single player's performance in every single NBA game ever. I tried XGBoost and Keras, and the Keras model outperformed the XGBoost model. Was about to incorporate real-time injury data, so if a player was injured or out that game it would not select them.
In the end it didn't perform too well. I think the limitation was my lack of domain knowledge, and not really knowing what features to select that would predict a players performance. Also data. I hear MLB is more consistent than NBA because there's just more data.
I'm sitting on MLB data (converting it to a BigQuery warehouse), am also interested in this space. The challenge w/ MLB is randomness plays a larger element - most folks in the MLB gambling space prefer other leagues where an information advantage more directly translates to profits.
It scraped basically every single player's performance in every single NBA game ever. I tried XGBoost and Keras, and the Keras model outperformed the XGBoost model. Was about to incorporate real-time injury data, so if a player was injured or out that game it would not select them.
In the end it didn't perform too well. I think the limitation was my lack of domain knowledge, and not really knowing what features to select that would predict a players performance. Also data. I hear MLB is more consistent than NBA because there's just more data.