Does NHL Shot Differential Matter?

If you have been following the evolution of the hockey analytics community, you’ll notice we have come to a place where many of these people strongly believe that shot differential is the most important measure of the value of hockey players. Putting grades on trades and other transactions only requires an examination of Corsi and its derivatives. They’ll say things like this was a terrible trade because the player has a bad Relative Corsi Against.

I’m a hockey stats nerd who wants to see the hockey analytics revolution succeed, but I have always been skeptical of “shots at goal plus minus” (aka Corsi) as a meaningful statistic. They call it a “possession” statistic, but it doesn’t actually count how long a team is in possession of the puck, and it assumes that all shots are created equal.

Placing ultimate importance on shot differential assumes that it actually matters which team gets the most total shots with no measure of quality of shooting location. It begs the question, how often does the team that shoots the most shots win the hockey game? A smart hockey brain might say something like 65%. If it were 50%, then the final shot differential would have no impact on the outcome of the game. I looked at a random sample of 1100 NHL games, and the team with the most shots won 50.9% of the games. In the playoffs it drops to 40%.

Hold on a minute, getting more shots in the regular season only increases the probability of winning by 1%? In the playoffs the losing team tends to get the most shots? In the 2016 NHL playoffs the 5 games with the largest shot differentials saw the losing team get the most shots (top being Washington losing with 44 shots to Philly’s 11). If shot differential is so important, why doesn’t it have a more positive effect on wins and loses?

There are possible theories. Such as, many teams play differently when they are leading or trailing on the scoreboard. They may hold an extra forward back to box out the middle and limit shots from best percentage scoring areas. In doing so they would hinder their own team’s shot production by attempting to limit the opponent’s opportunities. This would hurt the Corsi ratings for the players who are winning, while teams playing from behind take more risks and shoot more shots (though not always from higher value locations), thus giving the perception of greater value. It’s a theory.

Corsi is a flawed rating system that rewards quantity of shots over quality of shots. It gives players greater value to pepper the net with shots from everywhere instead of making extra passes to get the puck into a higher percentage scoring location. Goals are a function of quality scoring chances more so than quantity of shots. A shot from the red line has the same Corsi value as a breakaway. I never understood why Corsi is supposed to be a better judge of value than regular old fashioned plus minus. Perhaps the sample size is smaller for goals, but goals data is far more important than shots data. I would much rather know who was on the ice for every goal rather than who was on the ice for every shot.

If normal plus minus does not provide us with enough information, then Corsi supplies us with too much. Perhaps the optimal statistic is waiting untapped in the middle of these two extremes. Quality Scoring Chance Plus Minus. That would require a precise definition of quality scoring chance and people to count them, but would be a superior measure of value. In the proper context shot differential and Corsi can tell a story, but should not be the primary statistic for assigning value. Because if the Florida Panthers think they got a quality asset in Jakub Kindl, this Red Wings fan will tell you, don’t hold your breath…