Before I get into rush shots of individual players I am going to look at some teams. I am starting with the Columbus Blue Jackets which was suggested for me to look at by Jeff Townsend who was interested to see impact the decline of Steve Mason and then the transition to Bobrovsky had. Before we get to that though, let’s first look at the offensive side of things (and if you haven’t read my introductory pieces on rush shots read them here, here and here).
The League data is league average over the past 7 seasons.
There is a lot of randomness happening here, particularly the rush shot shooting percentages. This could be due to randomness as sample size for single season 5v5 road data is getting pretty small, particularly for rush shot data. Having looked at a number of these charts I think sample size is definitely going to be an issue. They key will be looking for trends above and beyond the variability.
Now for save percentages.
This chart is definitely a little more stable. Steve Mason’s excellent rookie season was 2008-09 where he actually had a below average non-rush 5v5road save percentage but an above average rush save percentage. Columbus never again posted a rush save percentage anywhere close to league average until this past season. Interestingly, despite Bobrovsky’s good season in 2012-13 his 5v5road save percentage that year was somewhat average (at home it was outstanding though which just goes to show you how variable these things can be).
Let’s take a look at the percentage of shots that were rush shots for and against.
Not really sure what to read into that, but I thought I toss it out there for you.
Something that I haven’t looked at before is PDO which is the sum of shooting and save percentages. There is no reason we can’t do this for rush and non-rush shots so here is what it looks like for Columbus.
Again, I am not sure what we can read into this PDO table. PDO is kind of an odd stat in my opinion. PDO typically gets used as a “luck” metric which it can be if it deviates from 100.0% significantly which is certainly the case for a couple of seasons of Rush Shot PDO.
I am still trying to figure out how useful any of this rush/non-rush information is. Certainly I think we hit some serious sample size issues when looking at a single seasons worth of road-only data and I think that puts some of the usefulness in question. I have done some year over year correlations and truthfully they aren’t very good. I think that is largely sample size related but I still think playing style and roster turnover can have significant impacts too. All that said, there is a clear difference between the difficulty of rush and non-rush shots and teams that can maximize the number of rush shots they take and minimize the number of rush shots against will be better off.