Hockey analytics is well behind analytics in other sports, particularly baseball, but we are now several years into what I will call modern (or current) hockey analytics which has largely focused on possession statistics such as Corsi and Fenwick. Last summer we even saw a number of teams publicly adopt analytics by picking up some prominent people from the public domain. Toronto, Edmonton, Carolina, Florida, and New Jersey to name a few. Results for those teams have clearly been mixed thus far but the greater question is whether hockey analytics, and possession analytics in particular, has had a greater impact on the game than just those few teams. I hope to answer some of those questions today.
One of the reasons why possession statistics such as Corsi became so popular is that it has shown that good possession teams often do well and it has also been identified as an undervalued skill as Eric Tulsky wrote about a couple of years ago. Contracts and salaries were generally given by teams to reward skills such as shooting percentage more than possession skills and thus possession skills were an undervalued talent. Teams could tap into this undervalued talent by getting good possession players at a fraction of the cost of good shooting percentage players. I warned that focusing too much on possession statistics is potentially harmful in the long run as it could result in players altering their playing style at the expense of what really matters, out scoring the opposition. I have shown that there is likely at least a loose inverse relationship between Corsi and shooting percentage implying that boosting one Corsi often has the negative consequences of reducing ones shooting percentage. I did this by looking at the impacts of coaching changes on Corsi and Shooting percentage and looking at the relationship between team CF% and Sh% when extreme outliers are removed.
So, the question is, have we started to see this shift where more teams are focused on possession and less so on shooting (and save) percentage? Has this shift altered team statistics and what leads to success in the NHL? Has the spread in talent across teams for the various metrics increased or decreased? To do this I am going to start off by investigating if there are any differences in statistics for the average team that makes the playoffs (or misses) compared to the average team that makes (or misses) the playoffs several years ago. Let’s start by comparing average playoff team GF% vs average non-playoff team GF% over the past 8 seasons (note that all statistics discussed here are 5v5close statistics unless otherwise specified).
Can’t really say too much has changed here. If anything the spread between good and bad teams has increased a bit but it could just be randomness too. The other observation is that 2012-13 is a bit of an anomaly where the non-playoff teams actually had a higher average GF% than the playoff teams did. This makes no sense other than in a shorter season strange things happened. We’ll get into this more but in a bit. For now, lets have a look at CF%.
Outside of 2012-13 that is about as stable of a chart as you could possible find. There was a slight increase in spread in 2008-09 but otherwise in full seasons the spread in CF% between playoff and non-playoff teams has been very persistent.
Now let’s take a look at shooting percentage.
For shooting percentage, not only is the short 2012-13 season an anomaly but so is 2011-12. In both of these seasons non-playoff teams posted a shooting percentage higher than playoff teams did which I guess puts some water on the argument that lucky teams make the playoffs if one defines luck as posting an elevated shooting percentage. What is also interesting to note though that outside of these two seasons there appears to be a trend towards an increasing disparity between good and bad team shooting percentage. Let’s look at this difference more closely by plotting Average Playoff Team Sh% – Average Non-Playoff Team Sh%.
The trend line does not include 2011-12 and 2012-13 which I’ll admit could be interpreted as a bit of selection bias (though those are clear anomalies in this chart) but when one does ignore those two seasons the trend is pretty clear. The disparity in shooting percentage between playoff and non-playoff teams is growing.
This is really kind of counter-intuitive. In a hockey world where there is a hard salary cap and where shooting percentage is an expensive talent to acquire one would actually expect teams would have a difficult time keeping all of their high-shooting percentage players. This does not appear to be the case though.
What about save percentage?
Again, 2012-13 is an anomaly season but otherwise it is difficult to identify a trend in save percentage aside from playoff teams always tending to have a better save percentage than non-playoff teams which makes perfect sense.
And just to complete the charts, here is PDO.
Not much new here. The short 2012-13 again appears to be an anomaly and 2011-12 driven by Sh% is a bit of an anomaly as well. Also driven by Sh% is what appears to be a slight increase in disparity between playoff team PDO and non-playoff team PDO.
The other thing we can do is look at the spread of these statistics by season by looking at the standard deviation across all teams to see if the spread is increasing, decreasing or staying more or less the same.
Aside from the 2011-12 seasons there might be an upward trend in the size of the spread in team GF% which is kind of interesting and counter to the popular belief that parity is increasing in the NHL. It is possible that there is increased parity in the middle and what we are seeing above is driven by the extremes (a few extremely good or extremely bad teams).
The spread in CF% appears to have increased the past three seasons. Could this be due to some teams jumping on board with possession statistics while others are not resulting in the increased disparity? Difficult to say but certainly possible. It could also be that more teams are going the tank and rebuild through high draft pick route (I am looking at you Edmonton and Buffalo).
As one would expect, the short season of 2012-13 produced the greatest spread in team shooting percentages but otherwise the spread in shooting percentage talent across teams has been pretty stable.
Pretty much the same for save percentage – a bump in the short 2012-13 seasons but otherwise pretty stable.
And we finish it off with the standard deviations of PDO which is surprisingly variable considering how relatively stable both shooting percentage and save percentage were aside from 2012-13. Not quite sure what to make of that variability but there doesn’t seem to be any upward/downward trend otherwise.
From the above charts I think it is very difficult to suggest that there has been much change in outcomes thus far in the NHL’s adoption of analytics. There are some potentially interesting things surrounding shooting percentage and possibly the increased the variability in CF% the past couple seasons but overall we can’t say with any certainty that anything significant has changed thus far. It is still early though and it can take a number of seasons to change a teams focus so we’ll have to keep an eye on it but so far we aren’t seeing much impact.