My infatuation (some say obsession) with hockey began during my undergrad in the city of Chicago. I was fortunate enough to see the Blackhawks win the Stanley Cup when I was in Chicago not once, but TWICE! As I have grown to appreciate and love hockey, I found another outlet to further submerse myself in the sport — statistics! A few ideas I have played around with have been the power play, face-offs, potential trends across time, and seeing if there is anything that can predict the likelihood of a Stanley Cup victory!

Doors closing… Welcome to the Blue Line.


Exploring 11 Years of Chicago Blackhawk’s Data using Principal Components Analysis

March 7, 2019 Academic Hockey Analytics R

In this post we explore 11 seasons (2007 - 2018) of team summary data from the Chicago Blackhawks of the National Hockey League (NHL). Our question was, “Are there any summary measures, such as goals scored or save percentage, that predict playoff performance or championship wins?”…

Multilevel Modeling in R with NHL Power Play Data

February 11, 2018 Academic Hockey Analytics R

This post serves as both a tutorial on how to perform multilevel modeling in R and an analysis that provides insight to how powerplay goals in the NHL have changed across 10 years. Readers will learn how to explore data using plots, use R to fit linear models, and how to extract inferences from the results.

The Last Decade: NHL’s Best and Worst Power Play Teams

May 15, 2017 Hockey Analytics R

So you are watching your favorite NHL team and they finally draw a powerplay. Awesome! The ice opens up with the missing player and it shouldn’t be too hard to score…right? As a previous water polo player, I know what it is like to endure the wrath of a furious coach after a missed man advantage opportunity. In my experience, coaches semed convinced that the man-up should lead to a goal 100% of the time. But how important is this seemingly advantageous situation in the NHL?…