Sure, on every goal scored the NHL gives data about who was on the ice at discreet moments in a hockey game, but there is little context to hold these events up against. It would be kind of like judging an MLB batter just based on his hits without having data on any of his unsuccessful at-bats; it’s just not a complete story.
Enter JavaGeek, the king of number crunching, who has concocted a method of extracting such shift data from what really are some pretty challenging sources (I highly recommend reading his Intro to Shift Analysis to better appreciate some of the hurdles). Essentially, JG is able to fill in a missing piece of the puzzle, what percentage of situational ice time an individual shares with a specific teammate. And at my enthusiastic insistence, he was kind enough to run these ice-time scripts for my beloved Ducks.
As an intro to how this concept plays out, let’s consider how Andy McDonald and Teemu Selanne played only at even strength:
T. Selanne | A. McDonald | |
---|---|---|
Pct. of E.S. TOI | 77% |
77% |
Pct. of E.S. ‘Plus’ events | 80% |
93% |
Pct. of E.S. ‘Minus’ events | 78% |
83% |
T. Selanne | A. McDonald | |
---|---|---|
Pct. of E.S. TOI | 23% |
23% |
Pct. of E.S. ‘Plus’ events | 20% |
7% |
Pct. of E.S. ‘Minus’ events | 22% |
17% |