Abstract
This article describes a method for predicting the outcome of National Hockey League (NHL) games. We combine a model for goal scoring and yielding, and one for penalty commission, in a Markov-type computation and a simulation model that produce predicted probabilities of victory for each team. Where these differ substantially from the market probabilities, we make “bets” according to a simple strategy. Our return on investment is both positive and statistically significant.
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