Wage Against the Machine : A Generalized Deep-Learning Market Test of Dataset Value

How can you tell if a particular sports dataset really adds value? The method introduced in this paper provides a way for any analyst in almost any sport to determine the additional value of almost any dataset. Applying the method to NBA betting markets with a standard dataset available publicly as well as an augmented one incorporating data from Vantage Sports, we find that a rolling deep learning model with the augmented data substantially and significantly outperforms a similar machine learning model with the standard data over the 2014-2015 season. Furthermore, the performance with the augmented data is above the betting break even probability.Finally, the same model without modification continues to outperform in subsequent markets and games, yielding a winning probability in excess of 56 percent for bets on games from the start of the season on October 27, 2015 through December 13, 2015