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A New Passing Data Viz to Analyze John Moore

In this article, I go over a new passing data visualization created by Spencer Mann that provides insight into the newest New Jersey Devil: John Moore. Read on for the details.

Like I was really going to use a picture of Moore as a Ranger on this blog
Like I was really going to use a picture of Moore as a Ranger on this blog
Kirby Lee-USA TODAY Sports

A common theme permeating social media, and even on this blog, is that the New Jersey Devils should trade one of their young defensemen (namely Eric Gelinas or Jon Merrill) for a young forward since the organization is depleted at that position. I'm here to tell you that that idea is complete nonsense and anyone suggesting it can meet me at the flagpole at three o'clock.

I'll be unveiling a new passing data viz that Spencer Mann (@SpenceIce on Twitter) created. If you just want to see that, scroll down to absolute bottom of this post. Devils fans might want to read up on John Moore, however. Also, give Spencer a follow on Twitter and check out his site.

Do the Devils lack high-end forwards? Yes. However, it's not as bleak as it was a few months ago. Adding Pavel Zacha immediately helps the situation. Trading for Kyle Palmierishort while later helps it even more. Also, Ray Shero likely wants to see young players earn places in the lineup. What better way to help out young forwards than by giving them a defensive unit that can transition well, make good passes, and play steady defense?

With Adam Larsson, Andy Greene, Damon Severson, John Moore, Gelinas, and Merrill, the Devils have the opportunity to ice three pairings that are both defensively responsible and can push the pace, exit the zone, and transition well into the offensive zone. As I highlighted on Monday, Merrill is the best defensemen at transitioning from defense to offense with his secondary passes. He's also on the ice for one of the higher expected goals for and lowest against based on passing sequences. There's value to his game. He also does well with a partner that likes to get forward as he played with Severson over the second half of the Devils season.

Gelinas has been talked up based on his offensive prowess and with good reason. After all, he led the Devils blue line in total Corsi Contributions (all individual shot attempts, primary, and secondary passes leading to shot attempts) per sixty minutes with 19.26. Severson was second at 19.10. The two of them like to get involved in the offense. They need a partner that can provide steady defense and transition the puck from defense to offense, not to mention be in good defensive position when either one of them, Gelinas or Severson, activates and joins the offense.

Well, step right up Mr. Merrill and Mr. Moore.

I'm not going to rehash what I think of Merrill since I wrote over 4,000 words on him two days ago. I want to talk about the impact that Moore has on his partner. So, we'll start with looking at his WOWY figures while on the Rangers, passing and overall. All non-passing WOWY figures come from Daviid Johnson's excellent stats.hockeyanalsis site.

Now, one thing to get out of the way is that Moore is not involved in shot attempts as often as Gelinas, Severson, or Zidlicky. He would have been fourth on the Devils blue, but still ahead of Merrill by a good margin (16.77 to 13.04 CC/60). However, Moore has a positive impact on possession in general. In fact, if we look at just the on-ice passing data we collected, we see that out of the Rangers and Devils, he had the highest SAG% Rel figures.


Now, personally, I don't like to use Rel stats when comparing players on different teams. There's a lot of team effects that go into those numbers that make for comparing with opposing teams ineffective, in my opinion. However, if someone, Moore in this instance, is the best on his team, then it stands to reason he'll have a positive impact on the Devils. It also confirms that letting Peter Harrold and Mark Fraser leave the team was the right move by Ray Shero.

So, Moore had a significant impact on passing possession, both for the Rangers and limiting the opposition. He also had the highest Corsi (all shooting attempts) Percentage Rel via War.on.Ice, so he's a solid possession player. This is a great move for the Devils. Here it is in plain sight.


So, each of his four most common defense partners saw better possession numbers with him as opposed to away from him. It's obvious that Moore impacts possession in a way that passing and shot attempts don't quite measure. All this would suggest is he's a solid defensive player.


Not only did his most common linemates have better possession numbers with Moore, but all saw a lower number of shot attempts against with Moore on the ice. Moore's impact is directly tied to playing strong defensive hockey. However, with Moore on the ice, the Rangers were not only better defensively, but had quality going forward. This can be explained  in the interactive chart below.

So, you can filter and get a sense that the Rangers were able to generate more attempts from sustained possession and passing and limit these opportunities for the opposition with great success while Moore was on the ice. The Rangers deployed Moore in favorable situations and he was quite effective in that role. I imagine that the Larsson - Greene pairing will see more defensive zone starts, so Moore could see slightly tougher deployment, but wouldn't be asked to handle all the tough assignments either. Furthermore, he needs to play alongside a Severson or a Merrill to be truly effective. Let's turn to our new data visualization for this.

Passing Data Visualization

So, what Spencer has done is taken the player data I released here and used Tableau to visualize it. There are three parts to it. First, there's a glossary tab to remind you of what each metric means, a player table tab if you just wanted to sort through each player's numbers, and, finally, a chart for each player that shows which percentile (20, 40, 60, or 80) he falls in relative to the rest of his position.

Unfortunately, the Tableau links are not cooperating and won't embed properly, so they may not be working. You can click on the positions at the end of the post and they will take you straight to Spencer's tableau page with the visualizations. I've included some screenshots of certain players to help explain them.

To recap some of the metrics: CC% and CC/60 are for Corsi Contribution (individual shot attempts, primary passes leading to shot attempts, and secondary passes leading to shot attempts) percentage and per sixty minutes. These tell you how much offense goes through that player while on the ice and also how often they contribute.

Composite SAG and SG represent the total number of shot attempts and shots a player generated from both primary and secondary passes per sixty minutes. SAG/60 is solely for the player's primary passing contributions.

Entry Assists represent the number of controlled entries a player assisted on. This is determined by the number of passes in transition (prior to entering the offensive zone) we recorded for each player.

SC Contribution % and SCC/60 are the exact same thing as CC% and CC/60, but represent only the scoring chances a player was involved in. I combined our passing data for scoring chances with War-on-Ice's scoring chance data to arrive at the total number of scoring chances a player contributed to. SC SAG/60 represents the number of scoring chances set up from a player's primary passes.


So, we see Moore does better than most defensemen at generating scoring chances, but doesn't advance play very much in transition or contribute via passes elsewhere. Now, let's look at Merrill's.


We quickly see Merrill jump significantly in his entry assists/60, as well as his composite shot attempts generated. He maintains a high level of scoring chance setups, similar to Moore. Merrill sees a drop in total scoring chance contributions despite his high number of passes leading to scoring chances. Why? Well, this would likely explain that Merrill does not attempt scoring chances himself, but merely acts as a provider, which shows up in his passing numbers and explains his lower overall rank for scoring chances.

If you look at the data for Merrill and Moore, and then compare it to Gelinas and Severson, you come away with two different types of players. One that can impact the team by getting involved and another that either facilitates transition play (Merrill) or another that offers impact through defensive means (Moore). Putting them together would result in not enough offense from the back end to support the forwards. Put Gelinas and Severson together and you risk giving up too many chances the other way and not being sound defensively. I'd suggest keeping Merrill with Severson and pair Gelinas with Moore to maximize the skill sets for both pairs. This provides the Devils with an effective, balanced, and young defensive unit. They could very well grow into an elite unit if given a chance. Let's not break them up just yet.

Feel free to check out both visuals and thank Spencer for putting this together. Sound off below if you have questions or comments!

Passing Data Viz Links: