A Beginner’s Guide to Understanding Advanced Statistics: Quality of Competition

Shot metrics have taken the NHL by storm this season. It’s about time All About The Habs provided a simplified version of the most predominant statistics. This will serve as a reference point for those looking to begin utilizing these metrics.

What is Quality of Competition?

Quality of competition is a versatile tool used to measure the average strength of an opponent. This is exclusively used at an individual level. The metric is very diverse as it can be portrayed in numerous ways using an abundance of different statistics. You’ll see it primarily based on Relative Corsi (a player’s on-ice average Corsi +/- relative to his team’s average Corsi +/- while he is off-ice) either in the plus/minus form (which behindthenet uses) or percentage form (which war-on-ice uses) and weighted by time-on-ice. In general, RelCorsi corrects for the Corsi boost players get from playing on a great offensive team and vice-versa. It creates a Corsi% or +/- in comparison to his team’s production only, as opposed to the entire league.

If Plekanec plays 20 minutes in a game, and 5 of those minutes are against the same line, 25% of his quality of competition rating/percentage comes from those opponents’ Relative Corsi statistics (if that’s the metric being used). Since this statistic encompasses every opponent a single player is matched against and there being a number of ways to get the resulting QoC, not to mention being weighted by TOI, it would be far too complex and monotonous to give a practical example of how to calculate it. However, if for instance in some sort of parallel universe Player A only ever sees TOI against Montreal’s top line, calculating his QoC would be simple. For example:

The Quality of Competition would be the average of 3.8, 3.9, 4.3, 5.2 and 3.1 which is 20.3 / 5 = 4.06%. In other words, Player A is matched against opponents whose Corsi% is on average 4.06% higher than their teammates. Remember, this is a very watered down example.

Generally, 1st line players will have the better RelCorsi ratings, so players who are primarily matched against those 1st line players should see the highest QoC rating.

What does Quality of Competition reveal?

Quality of competition can uncover a multitude of things depending on which statistic it is largely based on. For the example above, QoC tell us the strength of Player A’s opponents from a purely possession perspective. Looking at the bigger picture, it reveals how a certain player is used by his coaching staff and to a somewhat lesser extent, how the opposing coaching staff views that player.

It arguably helps explain why a player’s 5v5 Corsi% or Fenwick% is what it is, too. If Tomas Plekanec is consistently seeing the opposition’s best, that may have an adverse affect on the amount of shot attempts he generates. How much it affects Corsi% (if at all) is largely still unresolved. Basically, Quality of Competition tells us if players were used overwhelmingly against top competition, and potentially gives us another data point we can use to adjust a player’s inflated Corsi% or vice-versa.

Any QoC No-Nos?

QoC limitations mainly correlate with the limitations of the statistic you’re using to derive the QoC.

For instance, using just regular old Corsi% without weighing it by TOI to determine a player’s QoC would result in very poor possession teams having an unusually high quality of competition simply because they aren’t playing against themselves, whereas every other team is. The adverse affect is also true; top possession teams would have much lower QoC ratings. This best example of this would be this season’s Buffalo Sabres:

They currently have 15 players in the top 20 in quality of competition ratings. This is because they don’t play against the worst possession team in the NHL – themselves.

Final Thoughts

On most teams, the method using RelCorsi to determine QoC works out very well, though it’s reflective of how the coach sees the player and not necessarily of what the player’s abilities actually are. It does add some always important context to player evaluation, though.