It has been said in sports that you play to win the game. But it's easier to win the game if you are playing the Cleveland Browns than the New England Patriots, meaning that who you are playing can have as much to do with winning as how well you are playing. This project uses a Bayesian state-space model framework to measure the impact of the who, the when, and the where on a teams' schedule. We'll touch on the impact of rest, the home advantage, and opponent caliber to create a metric of schedule-strength that can be applied universally across sports. We conclude by estimating schedule strength in the National Hockey League during the 2017-18 season, and by extrapolating the impact of schedule strength on season outcomes.