Over the past year or two a few different statisticians have been exploring ways to measure a player’s possession skills independent of his team. Team effects on a player’s possession numbers often have a heavy influence on a player’s stats. For example, early in the season, Dan Carcillo had the highest CF% at 5 on 5 of any other forward in the league. It should be obvious to anyone who has ever watched hockey that Carcillo is not the best player in the league and illustrates how important it is to understand that usage and team strength have a lot to do with these measures.
dCorsi, developed by Steve Burtch, and Usage Adjusted Metrics, developed by Domenic Galamini, are two of the main tools that stats analysts have been using to try to evaluate a player’s individual strengths by removing team effects. Removing the team effects allows us to get a clearer picture of which players are driving possession regardless of the way the team uses them.
Galamini released a new visualization tool for Usage Adjusted Metrics at ownthepuck.blogspot.ca that you can use to look up forwards in the league. Below, I have included the visualizations from Galamini’s new tool for Chicago’s forwards. A few of the forwards, Nordstrom and Teravainen most notably, do not yet have enough ice time to be included so we will have to check back later to see their metrics.
You will note that Galamini quantifies the measures in the visualization as 1st, 2nd, 3rd and 4th liners. We’ve discussed before that Chicago has a more progressive way of using their players so these labels may not completely fit, but in a more traditional sense, you can ascribe value to these metrics using these labels. Right now, the Toews line is used against the opponent’s toughest competition frequently. The Richards line is used largely out of the offensive zone (at least for faceoffs) and plays against tough competition. The Shaw line is used against lesser competition whenever possible. The Kruger line takes the majority of the defensive zone starts (i.e. faceoffs) and frequently relieves the Toews line against the opponent’s toughest competition, which makes this line essentially a checking line despite their frequently given label of 4th line.
Galamini breaks the visualization out into 7 main areas. Usage Adjusted Corsi For/60 is the rate of shot attempts for the team with the player on the ice. This measures a player’s value in terms of shot generation. Usage Adjusted Corsi Against/60 is the rate of shot attempts against the team with the player on the ice. This measures a player’s value in terms of shot supperssion. Usage Adjusted Corsi % puts the first two together to measure overall puck possession. Goals/60 is the rate at which the player scores goals. Assists/60 is the rate at which the player assists on goals. Points/60 puts the prior two together. Finally, Scoring Chances/60 measures the rate at which the player is shooting the puck from the most dangerous (highest shooting percentage league wide) areas of the ice.
If a player rates as a first liner, it means his number in that particular metric is very good. So, for example, Jonathan Toews ranks as a first liner in UACF/60, which indicates he has a high shot generation rate and UACA/60, which indicates he has a very low shots against rate considering the quality of the competition he faces, zone starts, etc… (i.e. he is skilled at shot suppression).
With all of this in mind, here are the graphs for Chicago’s forwards.
Patrick Kane is an enigma. For a while now, analysts have been aware that his shot generation metrics showed that he is not individually driving puck possession in a way that is measurable by traditional means (shot attempts). This wouldn’t be a problem if not for the fact that he scores and takes shots from areas considered to be particularly dangerous at very high rates. He is unique in this regard. What does this mean? It means that if you took Patrick Kane away from a strong puck possession team like Chicago, his CF% and underlying possession numbers would likely be fairly poor. His traditional possession numbers are helped by team effects. Despite not being a possession driver, Kane remains one of the most dangerous players in the league through the neutral zone and in the offensive zone because he is simply always a threat to score when he is on the ice.
*all data and visualizations used herein are from ownthepuck.blogspot.ca and were created by Domenic Galamini (@MimicoHero on Twitter). Thanks to Domenic for making this tool available for public use and thereby making this post possible.