In a constant effort to provide as much context as possible to my data-generated player tracking system, I've looked into more traditional "advanced-stats" metrics.
Fenwick and Corsi numbers take a global picture of what occurs when a player is on the ice (shots attempted for and against), and uses those numbers to rate individual players. My system tracks individual player's puck-possession successes and failures (passes, dekes, puck-battles, etc) with a similar goal in mind.
Habs Eye on the Prize's Andrew Berkshire explains Corsi as follows:
Corsi - is a +/- statistic for a player/team that measures all shot attempts, including misses and blocked shots, directed for and against the team/player being measured per 60 minutes.
Andrew explains Corsi Relative Quality of Competition as follows:
Relative Corsi quality of competition - a measure of the average relative Corsi score of the opponents a player faces, weighted against the ice time played against each player
Silversevens.com explains the calculation for Corsi Relative Quality of Competition as follows:
Corsi Rel QoC is the weighted Relative Corsi Number of a player's opponents.For example, if a player plays 30% of the time against five players with a relative corsi of +1.5, 35% of the time against five players with a relative corsi number of +0.2, and 35% of the time against five players with a relative corsi number of -2.1 then:
Corsi Rel QoC = (0.3 * 5 * 1.5) + (0.35 * 5 * 0.2) + (0.35 * (5 * (-2.1)) = -1.075
The graph is a visual representation of each Montreal Canadiens player's even-strength risk/reward rating as calculated using my system, while the other bar is a visual representation of each player's ES risk/reward rating after including Corsi relative quality of competition into the calculation.
Even-strength risk/reward is a rating that determines how many more positive events than negative events a player produces per-minute of even-strength ice-time. Events used within this system include; puck-battles, loose-puck recoveries, passes, dekes, shots, blocked passes, blocked shots, dump-ins, dump-outs, and deflections. Each event is tracked as a success or failure.
In order for the calculation to work, and for the numbers to make sense, I've divided each Canadiens player's Corsi Rel QoC number by 5. Not only does this help minimize the impact on the original number, it also relates better to the reality of my system; Corsi uses team numbers while a player is on the ice. In order to accomplish this it multiplies the value by 5 to represent the five skaters on the ice. My system tracks individual events taking place against individual players. As such, it does not need to by multiplied by 5.
The quality of competition numbers used in this calculation can be found here. Numbers from earlier this season can be found here.
Alexei Emelin, Tomas Plekanec, and Brian Gionta have faced the highest relative quality of competition. As such, their even-strength risk/reward ratings improved the most with the qualcomp adjustment. Other defensemen with improved risk/reward ratings include PK Subban, Andrei Markov, and Raphael Diaz. Granted, Emelin has been responsible for too many scoring chances against since his return. But, both his pre-adjusted and post-qualcomp risk/reward point to him as a much-needed addition to the Habs top-4. Tomas Plekanec and Lars Eller have faced the toughest competition among Montreal centres. This is apparent in their adjusted risk/reward. Plekanec's adjusted rating is particularly impressive, and does a great job of relating the high quality of competition number 14 faces each game. Among wingers, Michael Bournival and Max Pacioretty have the highest adjusted risk/reward ratings.That said, it is actually Gionta's rating that improves the most when quality of competition is taken into account.
Rene Bourque has the lowest even-strength risk/reward rating both before and after the quality of competition adjustment. That said, Daniel Briere's risk/reward rating improves dramatically when qualcomp is incorporated into his rating. Context is an important aspect of player evaluation. The inclusion of quality of competition numbers into the calculation of a player's risk/reward rating helps produce just that context.
