Although I haven’t had the opportunity to catch much of the games lately (to be rectified now that the Western Canada road trip is over, of course), my understanding is that things are still going well for the Rangers, and in particular, they’re still getting solid scoring chances night in, night out. We talked a bit about this on the most recent podcast – how even though the Rangers’ CF% isn’t looking so hot and there may be some drop off in wins as a result, their SCF% (scoring chances for) is pretty good, and this is indicative of the team being more than just a flash in the pan a la last season’s hot start.

As some of you may know, I also write occasionally for, where a recent article by the esteemed Loserpoints explored the concept of scoring chances and how to best statistically encapsulate who is in fact getting the most high-end chances. I highly recommend this article, as it does a really great job of explaining what’s pushing the envelope in statistical analysis these days, in particular expected goals (or xG), in an intuitive and easy to understand way. I’m not really a math guy, although I do like statistics, and even I found it easy to understand.

The long short of it is this: scoring chances is a good, but not great stat to go by because it “bins” the numbers by arbitrarily deciding what is or is not a scoring chance. On for example, a shot that has a 9% or greater probability of going in the net (based on factors like wrist shot v. slap shot, where the shot was taken from, etc) counts as a scoring chance, but what about shots that have an 8% chance of going in? Those shots count too (exactly 8% of the time, and so on) and so we want to find a way to weight all scoring chances.

That’s where expected goals comes in. Manny over at has made public his model for calculating expected goals, which takes into account things like whether a shot was a wrister or a slap shot, the angle of the shot, whether it was a rebound, and so on. All of this stuff goes into an equation that then calculates for teams and players how many goals they’re expected to score. It’s interesting stuff that I encourage you to look into, both in Manny’s blog post on, and in the previously linked NHLNumbers article.

As the NHLNumbers article explains however, because the data used in the calculations is taken from the NHL, and because the NHL tells us where a shot was blocked, and not where the shot blocked was taken from, it’s better to use expected unblocked shot shooting percentage, or expected Fenwick shooting percentage (xFSh%) to gauge how a team or player is doing at generating scoring chances. This stat tells you what the likelihood of an unblocked shot going in the net is. Given the way the Rangers are playing, with any layman being able to tell that they’re generating scoring chances, I decided to take a deep dive into the Rangers’ xFSh% on both a team and player-by-player level.

What’s not going to come as a surprise to you, if you’ve made it this far, is that as a team the Rangers have a very high xFSh%. In fact it’s first in the league at 7.26% – meaning that we can expect unblocked shots of theirs to go in 7.26% of the time. Coming in second is the Toronto Maple Leafs, chock full of high-skilled youth, and in third are the reigning Stanley Cup Champion Pittsburgh Penguins. Not such bad company for a team that many (myself included) feared would barely make the playoffs this year. Still though, knowing that the Rangers as a team produce the highest danger scoring chances in the league isn’t enough – we want to know who specifically is leading the way.

Some of these numbers may come as a surprise and some of them may not, but it’s worth noting at the outset that every Rangers forward has an xFSh% above 6%. That’s pretty impressive when you consider that 15 teams in the NHL have a xFSh% of 6 or below. In other words, every Rangers forward is shooting above the bottom half of the league. Leading the way on the Rangers are Derek Stepan at 8.46%, Jimmy Vesey at 7.97 and Rick Nash at 7.93. Next are Hayes, Grabner, Miller and Buchnevich at 7.79, 7.71, 7.61, and 7.20. Zuc, Kreider, and Zibanejad come in at 7.06, 6.91, and 6.61 and lastly the fourth line guys have put up xFSh%s of 6.47, 6.23, and 6.04 for Lindberg, Fast, and Pirri respectively.

What you might notice about these numbers is that guys who play on the same line together are around the same xFSh% – Chris Kreider and Mika Zibanejad come to mind, as do Stepan and Nash. What’s particularly interesting I think is that while guys like Hayes, Vesey, and Grabner have had different linemates in different games so far they’ve all been putting up exceptionally high numbers. This seems to indicate that the three of them are capable of getting high danger chances no matter what, which corroborates what we can see on the ice – those three players are scoring threats constantly, putting in exceptional individual efforts and getting superb chances as a result.

An important caveat is that I have no idea how long this will continue for, but it is encouraging to know that not only are the Rangers scoring tons of goals, but they really truly are producing high-quality offense at a rate that outstrips everyone else in the league. They’re not simply a product of puck luck – they really are playing great hockey. Another caveat is that this metric helps indicate the likelihood of a player’s unblocked shot to go in, but it doesn’t tell you how essential a guy is at setting up the play or contributing on the forecheck for example. While positive play in those last two areas would certainly show up in terms of results, just because a guy like Chris Kreider doesn’t have the highest xFSh% doesn’t mean he isn’t an integral part of this team’s offense in terms of his skill set and how he plays the game. All in all its just one more tool we can use to evaluate team and player performance, but so far the results are overwhelmingly positive for the New York Rangers. Here’s to hoping they can keep it up.


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