On Salad and Predicting Hockey Games

Hockey, perhaps more than any other major sport, is difficult to predict. In the NHL, enforced parity and the intrinsic randomness of the game conspire to shorten the gap that exists between the league’s best and worst clubs. Michael Lopez concludes that the better NHL team can expect to win 57% of matches played against an opponent on neutral ice. That number places the league only slightly above the MLB (56%) and well behind the NBA (67%) and NFL (64%).

This video, albeit much less exhaustive than Lopez’s research in methodology, does a good job of summarizing the agents of randomness and their impacts on various sports:

Again, we find that hockey is comparatively prone to variance.

If you’re still not convinced, Josh Weissbock claimed a theoretical upper bound exists for NHL game prediction accuracy of 62% in his 2014 thesis. That means even the best predictive models should expect to be wrong on 4 of 10 picks, on average.

Surprise, surprise. Hockey games are difficult to predict. Continue reading “On Salad and Predicting Hockey Games”