So far in this article we’ve explored the history of hockey statistics as well as a crash course in how to properly use analytics to evaluate a particular situation. While correlations don’t equal causation, this month we’ll be exploring the current trends as the 2017-18 draws to a close. At time of writing, 1174 games have been played league-wide across all 31 teams, which is a decent sample size to look at some high level correlations.
I’ve pulled the current NHL standings as well as Corsica.Hockey’s 5v5 Team Stats splash page to run some correlations between a team’s analytical measures as a whole and more common measures of success such as even strength goals for, goals against and regulation/overtime wins. The metrics that will be used in the correlation will be outlined in a glossary at the end of this piece. The point is to illustrate at a very basic level how certain metrics may point to certain advantages, and how players who excel in a given metric may affect a team’s offense, defense, or overall winning ability. Recall that correlation measures are between 1 and -1, with numbers closest to either end bearing perfect positive or negative correlations.
To start, here is the full set of correlates between all metrics for you to explore: