Goldman Sachs’ statistical model for the World Cup sounded impressive: The investment bank mined data about the teams and individual players, used artificial intelligence to predict the factors that might affect game scores and simulated 1 million possible evolutions of the tournament. The model was updated as the games unfolded, and it was wrong again and again. It certainly didn’t predict the final opposing France and Croatia on Sunday.
Of course, past data don’t always predict the future; Goldman Sachs never tells clients to make decisions solely on the basis of its models’ findings. And in any case, the model only generated probabilities of winning a game and advancing, and no team was given more than an 18.5 percent chance of winning the World Cup. The moral of the story is probably that buzz-generating technologies such as big data and AI don’t necessarily make statistical forecasting more accurate.