The first significant breakthrough in hockey analytics occurred in the mid-2000’s when analysts discovered the importance of Corsi in describing and predicting future success. Since that time, we’ve seen the creation of expected goals, WAR models, and more. Many have cited that the next big breakthrough in hockey analytics will come once the NHL is able to provide tracking data. We’ve already seen some of the incredible applications of the MLB’s Statcast data and the NBA’s SportVu data. Unfortunately, the NHL has no immediate plans to publicly provide this data and as such, many analysts have decided to manually obtain the data.
On Saturday, November 4th, we hosted the first ever Hockey Graphs Analytics Data Sprint. The idea was teams had 6 hours to take raw data and do something interesting with it as a trial for the Vancouver Hockey Analytics Conference. Local teams met up at La Casita here in Vancouver, but we also had online participants as well.
Thanks to all of the people who helped put it together, and thank you to all those who participated, especially those who travelled from as far away as New York.
In this post we link to the finished results and you can see the winners. Their work is in a github repo which you can use for your own data analysis!