The researchers’ system is based on an artificial-intelligence method called “deep learning.” The system analyzed the performances of 36 basketball players and 5,226 pairs of interviews and games. Based on pregame interviews, it had a 60 percent success rate in predicting when a player would deviate from his average on parameters such as three-point shots and points scored. Predicting players’ actions based on past performance has just a 53 percent success rate, much closer to random odds.