The New York Rangers finished the 2020-2021 regular season with a +20 goal differential, yet missed the playoffs in a deep East Division. With a surprise management change at the end of the season following a disappointing result, are the Rangers a threat to make the playoffs next season? I encourage you to check out this post that describes some of the plots we’ll look at in more detail.
Overall Performance
While the Rangers finished in 5th in the East Division, they also put together a solid +20 goal differential on the season. Typically, this would be enough to put them into the playoffs but circumstances conspired against the Rangers this year. Let’s take a look at their results at 5v5 along with our points predictor model.
The Rangers underperformed our model, which uses 5v5 data as input, by a significant margin. As a result, we see the model prediction puts them much closer to the playoffs but still in 5th in the division. Finishing ahead of the Rangers were four good teams and it looks like a case where the Rangers suffered from the re-configured divisions and lack of wild card playoff spots this season.
Let’s take a look at how the Rangers goal rates stack up against the league at 5v5.
The Blueshirts’ offense was solid at 5v5 and they finished the year in the top 10 in GF/60 at 5v5. Team defense has more room for improvement, but they still had respectable numbers. At the team level, they look like they have the makeup of a good team. With the current division alignment and playoff format likely to be a one year phenomenon, the Rangers look primed for a better result in 2021-2022.
Player Performance
Let’s take a look at individual player performance to see where the Rangers should focus their efforts to improve this offseason. We’ll start with a player usage chart. With defensemen’s stats factored for comparison with forwards, we get a visual depth chart on the diagonal starting from the top right.
Artemi Panerin, Pavel Buchnevich and Adam Fox stand out as the best players on the roster. We see the players distributed relatively closely along the diagonal, indicating that the players were utilized effectively. The Rangers’ last two first round picks, Alex Lafreniere (1st overall in 2020) and Kappo Kakko (2nd overall in 2019) are in the middle of the chart, appearing to have put in quality NHL performances this season despite their young age.
By looking at 5v5 on-ice GF/60 vs TOI/GP, we get a visual representation of each players overall impact on team GF/60. Players further to the top right had larger contributions, with more ice time and greater offensive impact.
There aren’t many surprises on this chart. Brendan Smith is one player that stands out, with the highest on-ice GF/60 on the team. However, it appears that he benefitted from a very high on-ice shooting percentage that is unlikely to repeat next season. Generally, we see modestly higher on-ice shooting percentages for the players higher up the depth chart, which we expect.
Switching over to defense, we get a similar visual to the previous chart with on-ice SA/60 vs TOI/GP. This time, we are looking for smaller overall contributions by players located further down and left.
The league average for 5v5 on-ice SA/60 was 30 and the Rangers appear to cluster around this number. While there is room for improvement overall, there aren’t many standouts on the right side of the chart. One player we do notice there is Lafreniere. Likely, this is simply due to him being a young NHLer that needs some time to develop the defensive side of his game. The Rangers should be quite happy with Kakko’s defensive contribution in just his second NHL season, as he appears to have one of the better defensive impacts on the team.
Let’s move on to our on-ice GF/60 models. Here, we are predicting on-ice GF/60 based on each player’s individual stats. Variances between the model and actual are of interest with variance greater than about 0.3 being significant. Negative variance suggests a player carried his line mates offensively.
Panarin stands out with the best predicted on-ice GF/60 by our model, which is not a surprise, and also with the largest variance that suggests he carried his line mates offensively. With a superstar like Panarin and a growing young team, this is probably the best scenario that the Rangers could have hoped for. Julien Gauthier is the other player that stands out with significant negative variance from the model. Looking back at our initial usage chart, he is well below the diagonal line of the depth chart indicating he was underutilized. It looks like the Rangers should give Gauthier a look in a larger role.
On the other side of the equation, veterans Chris Kreider and Ryan Strome overperformed the model, suggesting their line mates carried them. From the usage chart, they both appear to be slightly over-utilized which supports this theory. With a number of talented young forwards on the team, the Rangers will need to shift ice time from these veterans to their developing players for optimal performance.
Looking at how defensemen performed against the model, we see some significant positive variances. This is likely a reflection on the quality of the Rangers forward group relative to the defense overall. Generally, it looks like the Rangers’ forwards carried their offense. With this in mind, we see Adam Fox performed in-line with the model suggesting that he was able to carry play along with the Rangers forwards. The Rangers should look to upgrade on the blueline.
Igor Shesterkin and Alexander Georgiev provided solid goaltending for the Rangers this season. With solid numbers from two young goaltenders, the Rangers look like they are set in the crease for the next few seasons.
Looking Ahead
The Rangers have just under $58M committed to next season’s cap. With a number of key free agents and an end of season management change, it will be an interesting offseason in New York.
Key RFAs:
Pavel Buchnevich is the Rangers’ most important RFA among skaters. As the Rangers’ second best forward behind Panarin, he is in line for a significant raise from his current $3.25M per year deal. Filip Chytil and Julien Gauthier are also key RFAs that the Rangers need to re-sign. From our review, we saw that Gauthier may have some untapped potential and Chytil was a strong offensive presence this season.
Igor Shesterkin is also an RFA this offseason. Following a solid performance this season, he will be looking for a substantial raise coming off his entry level deal.
Key UFAs:
Brendan Smith was a key piece for the Rangers defense corps this season and he heads to the open market as an unrestricted free agent. With the largest variance from our on-ice GF/60 model, it looks like letting him walk may be the best option for the Rangers. His departure would leave an open roster position where the Rangers can target an upgrade.
Key Players Under Contract:
With a number of highly touted prospects now in the NHL lineup, including Lafreniere, Kakko and Fox, the Rangers need to see continued development from these young stars. Strong performances while these players are still on entry level deals is a recipe to make the Rangers a contender.
Tough Questions:
Do the Rangers lack the grit required to be a contender? That certainly seemed to be the message when Jeff Gorton was let go as GM with a few games left in the season. However, we’ve seen a that the Rangers suffered from some unlucky circumstances this year and have a solid group of young players. If the Rangers are determined to add grit to their lineup, they need to do so without compromising the skill they have.
Offseason Priority:
With a number of high profile RFAs, the Rangers most important business this summer will be re-signing their key RFAs. They should also look to free agency or the trade market to upgrade their defense corps. With RFA raises likely to eat up cap space for the next few years, they will have to be careful about adding large cap hits in the process.
Check out my other season reviews that have already been posted, such as the Detroit Red Wings and the Philadelphia Flyers, and subscribe to catch the rest of my season reviews as they come out.
data: Natural Stat Trick
cap data: CapFriendly
