Today Travis Yost of TSN.ca put up an interesting post where he ranked forwards and defensemen based on their ice time with their team (1-12 for forwards and 1-6 for defensemen) and then looked at each group (1-12) average to see how the forwards performed.
To illustrate this, I took the average Corsi% for every forward who led his team in 5-on-5 ice-time, then repeated the same through the twelfth forward. You’ll notice how the first line looks great, the second and third lines look average, and the fourth line looks poor.
When I do this I get the following chart which is more or less the same for the purposes of the analysis but is different enough that we must have used different methodology (maybe Yost used Score Adjusted Corsi as opposed to straight 5v5).
Regardless of the differences in the charts, the overall trend is the same, first and second line forwards have better CF% than third and fourth line forwards. Yost’s conclusion from this is that coaches are good at handing out ice time to their forwards giving the best forwards the most ice time. While true, I think Yost is missing one key point which can easily be seen by splitting apart CF% into its components – CF/60 and CA/60.
Basically what is happening is coaches are handing out more ice time to players that generate more offense. Shot attempts against are pretty stable from forward 1 to 12.
The next obvious question is, how do the percentages look?
The most ice time is given to the high shooting percentage players and the least to the low shooting percentage players. That said, the significantly higher than normal shooting percentages are mostly just for the top 3 or 4 forwards on a team. Beyond that the drop off is much less significant as you go down the forward ranks. The impact is significant though. The average first line forward has an on-ice shooting percentage 1.6 percentage points above the average 3rd line forward resulting in first liners scoring >23% more goals on an equal number of shots.
Another interesting observation is that save percentage steadily rises as you drop down the line up. The average #8 forward has an on-ice save percentage that is about 0.6% higher than the average #1 forward. That’s a smaller impact than shooting percentage but not completely insignificant either.
I’d probably ignore the spikes seen in the 12th best forward. Sample size might be an issue and it is an interesting combination of players, some high end younger players and some injured players like Brandon Sutter.
Now, combining all this together we can look at goal rates for and against.
As expected, the top line scores far more than lines 2-4 and that is largely due to their significantly better shooting percentage. Defensively there are not significant differences from lines 1 through three with a bit of a tail off at the very bottom of the line up.
The conclusion in all of this is forwards get assigned ice time based significantly on their offensive production which drives their overall goal differential.
Now for defensemen starting with 5v5 CF%.
As with what Yost found there isn’t a consistent trend here where the top ice time defensemen have the best CF% and it slowly drops off as you move down the line up. Instead it is fairly flat. The conclusion here would be that coaches don’t really hand out ice time to defensemen in an efficient way but is this really true once we start looking at the data in more detail?
Let’s look at CF/60 and CA/60 first.
So, here we start to see something. The #1 defenseman is, on average, a very good two-way defenseman generating the most offense and good at defending as well. The #2 and #3 defensemen appear to be the worst offensive defensemen but also give up a fair number of shots as well which is not a good combination. We see this in the previous chart where the #2/#3 defensemen have the worst CF%. Defensemen 4 through six are more balanced defensemen.
And the percentages?
Interesting spike in shooting percentage for the #4 defenseman. It could mean the #4 guys are more offensive specialists that get more ice time with the top lines of teams.
The #2 and #3 defensemen that seemed do poor corsi-wise now appear much better having by far the best on-ice save percentages which are on average about 0.4 percentage points higher than the rest of the defense.
How does this all wash out in terms of goals for and against?
The highest goals against rates are by #1 defensemen with #3 defensemen having the best (lowest) goals against rates. Interestingly the best offensive defensemen are on average #4 defensemen followed by top pairing defensemen.
And GF% overall?
Interesting that the #1 defensemen have pretty much the worst goal differential while defensemen 2 thru 4 are much better all round. It makes you think that maybe the defensemen that teams have identified as #1 guys might be over used. Makes you wonder how many teams would be better off playing their #4 defensemen in a #1 role and vice versa.
Now let’s finish with one final plot for defensemen comparing CF% and GF%.
Wow, do the GF% and CF% lines tell dramatically different stories. Aside from how poor the #1 defensemen appear the GF% is a much more reasonable plot with defensemen 2-4 being quite good with a significant drop off to the 5th/6th guys. That makes more sense than CF% where the 5th and 6th guys are significantly better than #2 and #3.
It is probably worth looking at other years or revisiting this later this season when sample sizes are larger before we draw any significant conclusions but the one thing I want everyone to take away from this post is it that just looking at Corsi% may not be telling the whole story. There may be far more interesting and more important messages to be found looking beyond Corsi%. In this case there is more to the story than what Yost’s posts portrays. For forwards it isn’t so much Corsi% that is driving coaching decisions for forwards but rather the overall offensive ability of the forward with defensive ability having relatively little importance. For defensemen there appears to be some ability for #2 and #3 defensemen to boost save percentage and that appears to be an important reason that they get ice time over those further down the depth charts while the #1 defensemen might be getting mis-used or over-used. Again, this is not necessarily apparent when just looking at Corsi% but is critically important to understand what is really happening from an analytics point of view.
When I first got into hockey analytics I spend a fair bit of my time trying to come up with an all-inclusive player evaluation statistic. The more I dig into the data the more I realize that all-inclusive stats or high level stats often over generalize and miss the point. In hockey players are often given very specialized roles based on their skills and their resulting statistics are a result of a combination of their skills and the roles they have been given. There is a lot of nuance in hockey that we can’t extract from a single high-level stat like Corsi%.