A Look at the New Jersey Devils Passing Stats, 20 Games In

Elsa

"Great pass, Zid. You didn't turn it over that time." The NJ Devils have some great passers and some woeful passers. Good enough passes can become shot attempts. Some Devils are better at this shot-generation. Let's sort out who we'd like to have the puck more often.

Passing Data Season-to-date

This is a look at all New Jersey Devils skaters passing data from Game 1 until this point in the season. 20 games in, I want to try and answer what constitutes a “good” passing game. To do this, I’ll look at average passes in each zone per game as well as average shot attempts generated per game among forwards and defensemen.

You’ll notice these reports look different from the individual game reports. The new columns are for Games Played (B), the Percentage of Shot Attempts Generated as it relates to Total Pass Attempts (M), Total Team Corsi For when that player is on the ice (N), Percentage of Shot Attempts Generated as it relates to Team Corsi For (O), Total Pass Accuracy (Q), and. These are added to illustrate which players have been most consistent and most productive. All other columns are the same.

All Corsi, Quality of Competition, and Quality of Teammates figures were pulled from ExtraSkater.

These summaries break down like this: 1) Analysis of each player’s season to date totals and comparison to the previous summary; 2) Analysis of player’s season-to-date averages; 3) Team season-to-date averages. I’ll include the stats from the previous 10 game summary as well, but going forward, I’m only going to highlight averages. You’ll see.

Terms You May See:

DZ%: Defensive Zone Completion Percentage

NZ%: Neutral Zone Completion Percentage

OZ%: Offensive Zone Completion Percentage

SAG: Shot Attempts Generated

SAG/P%: Percentage of pass attempts that result in shot attempts generated

CF: Total Corsi events for while that player is on the ice

SAG/CF%: Percentage of Corsi events that occur as a result of that player’s SAG

Accuracy: Overall Completion Percentage (total completions/total attempts)

TotTm% QoC: Average Time on Ice of 5-on-5 opponents

TotTm% QoT: Average Time on Ice of 5-on-5 teammates

Let’s get to it. Here's the defensemen's passing stats for the first 10 games. My summary is here if you take a look.

Gr86vew_medium

via i.imgur.com

And now we'll take a look at the defensemen first. These charts are broken into 2 parts because they were too small as one.

Def_20_game_passing_totals_1

Def_20_game_passing_totals_2

Defensemen:

At the 10 game mark, Marek Zidlicky dominated these categories everywhere except for completion percentage. He’s improved his passing in every zone by 4 – 6%, which is a significant jump for only 10 games. He has cooled off in terms of SAG, only generating 10 shot attempts over the last 10 games as opposed to 28 generated during the first 10 games. As noted in the Zone Exit write-up, Zid faces the 2nd highest QoC, but only has the 5th best line mates out of the 8 defensemen the Devils have used this season (discounting Jon Merrill’s brief debut). Nearly 8% of Zid’s passes result in a shot attempt, which is still the highest among the defensemen, but he’s on this team to provide offense, so I’d like to see him get back to providing opportunities for his teammates. His 14.4 SAG/CF% is also the highest among the defense by a good margin.

Adam Larsson began the season tentatively, to say the least. Since being paired with Eric Gelinas, his stats have improved across the board. His completion percentages improved slightly in the defensive zone, quite well in the offensive zone, but nearly 20% in the neutral zone. That’s mostly due to small samples early on for Larsson, but it certainly shows he’s becoming more involved. He had 13 SAG in games 11 – 20 compared to just 3 in games 1 – 10, a huge improvement. Consider it this way: Larsson generated more shooting attempts than Zidlicky over the past 10 games. Zid built a big lead over the first 10 games, but we’ll see if Larsson can continue to gain on him. The young Swede does face a lower QoC, but only marginally better teammates.

Andy Greene’s DZ% has dipped 3%, but his NZ and OZ%s have improved, so it’s a bit of a tradeoff. As the zone exits showed, Greene hasn’t been as great in his own end as we’d hope, but he does play against the highest QoC every night. Greene also has the highest QoT on the ice with him, though, so it’s a mixed bag. His SAG figures were 12 in the first 10 games and now it’s up to 22, so he’s fairly consistent in the opportunities created for teammates. If he’s on the ice with the top lines, the forwards may generate more on their own and have less reliance upon the defensemen, so there’s some hidden knowledge related to production there. Considering his QoC, I’d say Greene has been quite effective.

Since the first 10 games of the season, Harrold has improved his DZ% by 4, and his NZ% improved by 10. His OZ% remained about the same. In the first 10 games, Harrold generated 11 shot attempts; in games 11 – 20, he only added 5 to that total. Among defensemen, Harrold plays against the 4th strongest QoC with the 3rd weakest QoT. Basically, Harrold plays against tougher competition than he has teammates when he’s on the ice. All that considered he’s actually improved his SAG/CF% marginally by a few percentage points. He’s been effective at generating offense, and has improved his completion percentages.

Bryce Salvador hasn’t played since his 9th game, so nothing new to see here. While he was playing, Salvador tied with Greene for highest QoC. He also had the 2nd highest QoT on the ice with him. Salvador’s DZ% is still 2nd highest on the team.

Anton Volchenkov has remained quite consistent regarding his completion percentages. They’ve only changed within 1%. Overall, he’s the defense group’s most accurate passer. Of course, on a per-game basis, he’s also the least frequent passer on the team. At least he’s competent when he’s on the ice. He hasn’t been as much a liability as I remember. His QoC would indicate Deboer’s getting Volchenkov out there against team’s lower lines, which is smart. Volchenkov can remain a solid 3rd pairing defenseman.

Mark Fayne has not been good in these stats. He only had 4 appearances when I wrote up the first 10 games and he’s at 10 games played now. Considering the slow start much of the team got off to, I’ll give Fayne a little leeway and scrutinize him more once the 30 game mark rolls around. Thus far, Fayne has offered the least in terms of SAG, has the third lowest DZ%, and plays against some of the weaker competition (tied with Volchenkov). I think this is a make or break year for Fayne with Merrill likely to debut at some point this season.

Lastly, Eric Gelinas. He’s played in every game since his debut and with good reason. His DZ% is the highest on the team, and he’s completed all 13 passes in the offensive zone. Gelinas’ SAG figure is 8 and his overall accuracy is the highest on the team. Granted, he is playing against the weakest opposition of the defensemen, but he’s doing that with the weakest quality of teammates by far. He generated almost as many shot attempts (8) as Zidlicky did these past 10 games (10).

Here are the forward 10 game totals.

Ogcha6y_medium

via i.imgur.com

And now the forward 20 game totals.

Fwd_20_game_passing_totals_1

Fwd_20_game_passing_totals_2

Mattias Tedenby and Jacob Josefson still haven’t played more than 10 games, so I’m hesitant to read too much into their stats. I’ve included them on the charts, but I’d rather have a larger sample size before assessing their play. Same thing goes for Ryane Clowe and Cam Janssen.

Let’s start with Old Man Jagr. Jaromir Jagr has been fantastic this season, and it really shows through in these stats. His DZ% increased 10%, while his NZ% and OZ% had minor amounts of change. In the first 10 games, Jagr generated 26 shot attempts. In the next 10 games, he generated 35. A larger percentage of his passes are resulting in SAG and his average SAG per game increased from 2.6 to 3.

His current line mates, Travis Zajac and Dainius Zubrus, are also improving. Zajac’s percentages either improved or remained close to his 10-game marks, while his SAG growth was consistent. Zajac’s largest jump was in SAG/CF% where, in the first 10 games, his passing was responsible for 14.7% of the on-ice Corsi; now, that figure has increased to 21.2%. What that means is that of all the shot attempts when Zajac is on the ice, 21.2% of them are coming as a result of his SAG. I truly hope this new-found “playmaking” ability keeps up. Zubrus’ SAG doubled, which it should if he was remaining consistent, and his on-ice CF doubled exactly. Most of his numbers stayed pretty close to his 10-game marks. Let’s hope he keeps it up playing on the top line. Very underrated, Mr. Zubrus is.

Newcomers Damien Brunner and Michael Ryder have had mixed reactions from Devils fan, I would assume. Well, in Brunner’s case, he’s become slightly better in the passing game. His completion percentage has increased in each zone and 3% overall. He had 9 SAG in both season splits thus far, bringing him to 18 on the season, and his passing percentages related to SAG and CF have increased. Perhaps Brunner realizes that he has to pass sometimes and not just shoot, especially when he’s not scoring.

Ryder also increased his zone percentages across the board and 4% overall. His SAG dropped from 17 in the first 10 games to 12 in the next 10. His SAG/P% remained the same, so Ryder’s attempted fewer passes over the last 10 games than he did to start the season; his SAG/CF% rose almost 6%, so he’s attempting fewer passes, but the passes he completes are contributing to a greater share of the team’s CF when Ryder’s on the ice. Ryder’s been doing this against the 5th strongest QoC, which is consistent for a 2nd line forward, and alongside the 4th strongest QoT among forwards.

Adam Henrique’s Accuracy changed about as slightly as it can, but he’s remained consistent. His SAG dropped from 25 to 19, but, similar to Ryder, his SAG/CF% rose about 6%. The team’s CF only increased by 47, suggesting he and his on-ice teammates are having a harder time generating shot attempts these past 10 games. Henrique’s QoC and QoT are comparable to 2nd line players. You’d like to see the offense come back a little bit for Henrique in the next 10 games.

Andrei Loktionov was a machine the first 10 games, so I didn’t think he could keep it up, but he’s come pretty close. His accuracy dropped 4%, but still remains high at 84%. He’s added 21 SAG compared to the 25 he racked up earlier this year. His passing still creates opportunities for teammates at a high rate. Loki’s QoC is 8th strongest of the forwards, consistent with his usage as a 3rd line player. His QoT is 9th strongest among forwards, so that’s consistent with usage as well.

Patrik Elias has only played in 12 games out of the first 20 this year and 8 of those were in the first 10, so his sample size is smaller than many of the forwards on the team. Surprisingly, Elias’ Accuracy is much lower than what you’d expect (72.4%). He still remains one of the team’s key contributors with 35 SAG in 12 games, 13 more than the first 10 games, and typically plays against top QoC with top Qot. Going forward, Elias may be on a second line with Zubrus, Zajac, and Jagr playing so well lately, so I expect him to assert himself more and dominate like we know he’s capable of.

While they’ve been broken up at times since the arrival of Cam Janssen, the fourth line of Ryan Carter, Stephen Gionta, and Steve Bernier has had its ups and downs. Gionta’s Accuracy remained about the same overall. His SAG dropped from 8 in the first 10 games, to 4 in the next 10. He doesn’t add to much going forward and both he and Carter’s QoC and QoT are virtually identical, good for the 3rd and 2nd lowest totals on the team. In his limited action, Jacob Josefson played against lower competition, but performed significantly better. Josefson generated the same amount of shot attempts in 6 games as Gionta has in 18. His passing rates are all much better. Hopefully, Josefson can get in some games over the next 10 and I can bang the drum harder for him, because he’d be a better option than Gionta for certain. Perhaps Carter, but I’m not sure.

He most certainly wouldn’t be better than Bernier right now. Bernier’s DZ and NZ%s have increased dramatically (23% and 11% respectively), while his OZ% dropped about 7%, but still is at 82.4%. Over the first 10 games, Bernier’s SAG was 15; over the last 10 games he generated 22. His SAG/P% rose slightly to 24% (one in roughly every 4 passes, Bernier is creating a shot attempt for someone), and he had a 7% increase in his SAG/CF%. Bernier’s done this while playing against the 10th strongest QoC, and the only Josefson, Gionta, Carter, and Janssen play with weaker QoT than Bernier.

I think there’s some type of stat that could involve the difference between your QoC and QoT related to production, but I can’t articulate it yet. For example, if your QoC is higher than your QoT by, in Bernier’s case, 0.7%, does that correlate to anything else Bernier does on the ice? Could it mean anything at all? This is just me thinking out loud here, which I’ll do from time to time, and it may just mean that Bernier’s better than his line mates against the same level of competition. It intrigues me though.

Individual Game Averages

Def_20_game_passing_averages

Now we’ll look at averages for the defensemen on a per-game basis. Cells highlighted in green are average or better; those highlighted in red are below average.

If we first look at this by zone, then Zidlicky, Greene, and Larsson complete and attempt the most passes in the defensive zone. The most active in the neutral zone are Zidlicky, Greene, and Harrold. The most active in the offensive zone are Zidlicky, Harrold, and Greene. Overall, Zidlicky and Greene average over 20 pass attempts a game, completing just about the same amount (17.3 and 17.6) with Greene slightly more accurate.

So, when we look at the averages for the defensemen, we quickly see that Volchenkov is the lone defenseman attempting less than 10 passes in the defensive zone each game. Overall, he only attempts 11.4 passes per game. Fayne is not much better at 13.9, and Gelinas is the third lowest at 16.

Had I done this for the first 10 games, I’d be willing to bet that Larsson’s averages climbed dramatically. He really does look a different player on the ice since being paired with Gelinas. I think he might close the gap on Greene over the next 10 games.

Fwd_20_game_passing_averages

A lot of these colors tend to follow the same players, but there are a few interesting takeaways. Ryder, in the defensive zone, and Josefson and Clowe, both in the offensive zone, are completing more passes than the team on average, but attempting fewer than the average. Elias is green across the board, until you get to his percentages. One would think that is Patty can start being a bit more accurate he’d be even more effective. Let’s hope that’s the case.

You’ll also see SAG per game just before the percentages. Jagr leads the team with just over 3 SAG per game. Elias is next at 2.92, followed by Zajac (2.5), Loktionov (2.42), and Zubrus (2.35) as the top 5 on the team. Bernier’s above the average, notably ahead of Ryder and Brunner.

Team Review

Now we’ll look at averages for the entire team and by position grouping. This will eventually be able to tell us who had a “busy” game versus a “low-event” game. Also, it illustrates who is more involved, and how often each player generates a shot attempt on average.

Team_20_game_passing_averages

You can see that on average, the defensemen attempt 109.7 passes, complete 85 of them, and generate 6.2 shot attempts each game. The forwards attempt 119.4, complete 92.7, and generate 20.9 shot attempts each game. Each game, the Devils complete 177.7 of 229.1 passes and 27.1 of their shot attempts are created directly created off of passes.

These figures should be useful going forward on individual game recaps. We will be able to determine how active the team was compared to other nights. Obviously, we already have an idea when looking at Corsi numbers, but hopefully these numbers can eventually offer up some support of existing stats or something new entirely.

Unfortunately, there’s no one else tracking passing stats as far as I know, so I don’t have anything to compare it to. Eventually, I’d like to create a database where followers of other teams can submit their data to, similar to the Zone Exit Project going on that I’m a part of.

Feedback and criticism are encouraged! What are your thoughts on these passing stats? Do you think it’s a viable exercise in tracking and reporting them? What are some questions you have about them? Is this presented easily enough to process? I know it’s a lot thrown at you, especially if this is new, so let me know if I need to rearrange, reword, or redo anything.

In the Next Review

One thing I’m also thinking about is a “contribution to Team Corsi” rate or something similar to that. Obviously, passing stats favor those players that would rather pass than shoot, but I think it’s a decent way to delve into who is responsible for production down to each shot attempt generated. In my 30 game review, I think I’ll look at shot attempts created and shot attempts taken (I believe they have this on ExtraSkater) and see if that works out to a “contribution” or “expected Corsi added” or something. 30 games in, I will also take a look at Corsi and SAG and see if there’s anything relatable that’s interesting. This may be getting too granular. Let me know if I’m down the rabbit hole a bit too much.

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