This is a look at all New Jersey Devils skaters passing data from Game 1 until this point in the season. The focus this time around is going to be on the ratio of shots generated (SG) to shot attempts generated (SAG). Also, we’ll take a look at shot attempts by zone and what percentage of each player’s passes occur in each zone.
The tables may not look right at a first glance, but since I started tracking SAG by zone around the 27 game mark, and SG around the 33 game mark, I had to edit my formulas if I wanted to keep everything on one chart. Basically, you’ll see the totals for everything, but they obviously won’t add up. In order to ensure the percentages were accurate, the D/NZ SAG and OZ SAG ratios only include data from game 27, and anything including SG is as of game 33. If that’s confusing, let me know, but all you need to know is that the percentages reflect the new data since I started tracking it.
All Corsi, Quality of Competition, and Quality of Teammates figures were pulled from ExtraSkater.
Terms You May See:
30 game summary is here for your reference. Let’s get to it.
Marek Zidlicky: In the 9 games that Zidlicky played over the last 10, he managed to increase his DZ% and NZ% slightly, while his OZ% continues to decline—this time 2.3%. Although, his overall accuracy improved by 1.1%, so the amount of passes he’s taken in the offensive end has probably decreased. His CC% has remained about the same, 28.1%, good enough for 4th among defensemen.
With 13 games tracking SAG by zone and about 7-8 of tracking SG (shots generated), we can see that Zidlicky generates 1 shot per 4 shot attempts in the offensive zone (25%). 8% of his passes result in shot attempts, but only 1.8% of his passes result in shots. That 1.8% SG/Pass rate is 5th highest among defensemen. In the last review, Zid’s CC% was 2nd highest among defensemen, so he’s clearly been passed by others on the blue line in terms of production. Zid’s tied for 3rd among defensemen in terms of QoC as well as QoT. However, Zid’s CF% rate is 3rd lowest among the Devils defensemen.
Andy Greene: Greene’s completion percentages increased in the DZ and NZ, but dropped slightly in the OZ. His shot attempts had a higher percentage of resulting in shots than Zidlicky (55.6% compared to 25%). In fact, 4.0% of Greene’s passes end up in shots. His CC% is 0.5% higher than Zid and 1.3% higher than at the 30 game mark. Greene faces the highest QoC and middle of the road QoT. Greene increased his accuracy to 81.3% and his CF% is the 2nd highest among defensemen. He’s generated the most SAG from outside the offensive zone.
Mark Fayne: Fayne’s completion percentage improved in each zone and he continues to be the Devils most accurate passer in the offensive zone. His passes generate shots at the same rate as Zidlicky and he does so in fewer passes (0.3% fewer). Fayne’s QoC has risen to 28.9%, tied with Zid, but his QoT is the highest on the team. Fayne’s OZ S/SAG% is only 16,7%, so even though he’s the most accurate passer, for some reason the shot attempts he’s generating are not finding their way on net that much. Now, this represents only a 7-8 game sample, so we’ll see how it changes, but it stood out in stark contrast to his overall passing ability.
Eric Gelinas: Gelinas’ OZ% took a 6% dive in the last 10 games. Unsurprisingly, his accuracy dropped 0.6%. Less than 1% of his passes result in a shot generated and 4.5% result in a shot attempt. Always a defenseman looking to shoot first and pass later, Gelinas own shot attempts account for 24.1% of the shot attempts when he’s on the ice, easily the highest among defensemen. Due to that stat, Gelinas is the only defenseman whose CC% is over 30%, an almost 1% increase from the previous summary. He’s still facing some of the weakest QoC among defensemen, but his QoT is also the lowest, so he’s still managing to come out ahead and be effective at generating offense.
Jon Merrill: Merrill continues to be the team’s most accurate defenseman and shows no signs of slowing down. Even his S/SAG rates are high: simply put, Merrill makes accurate passes and when he sets up a teammate for a shot attempt, more than likely it’ll result in an actual shot on net. Unfortunately, Merrill has taken fewer shot attempts himself (3% fewer from the last summary) so his CC% is only 22%. He’s in much the same situation as Gelinas (lowest QoC and QoT on the blue line), but, like Gelinas again, he continues to outplay his opposition as his 55.6 CF% is 3rd highest among defensemen.
Anton Volchenkov: Volchenkov’s completion percentages didn’t change much from an overall point of view. None of his SAG have resulted in a single actual shot yet, but at least 5.9% of his passes still generate shot attempts (3rd highest among defensemen). I was surprised that Volchenkov continues to put up his own shot attempts (21.6% of Team CF) as he’s 2nd only to Gelinas in that department. As a result, his CC% is tied with Andy Greene. Part of the reason I wanted to look at Shot rates and not just Shot Attempts Generated was because we know Greene is a much more effective player than Volchenkov, but it you only went by SAG and CC%, you’d think they were much closer. Anyways, Volchenkov increases his overall accuracy slightly, above the position average actually.
Bryce Salvador, Adam Larsson, and Peter Harrold: Not much to add to these skaters as Salvador just returned, Larsson is still out, and Harrold hasn’t played since the Devils win over the Rangers in OT. Hopefully Larsson returns soon and we’ll have more data on both by the Olympic Break.
Dainius Zubrus: Zubrus’ completion percentages in NZ and OZ decreased and increased, respectively, by 2.6% and 1.1%. His DZ% barely moved. Zubrus’ S/SAG% is one of the higher rates on the team at 63.6%. His production, like his play, is consistent and he’s hovering just under 38% for his CC rate. Between Travis Zajac and Jaromir Jagr, Zubrus’ numbers will always be just a bit lower, but there is only one puck to pass and shoot after all. His iCF of 93 ranks behind Jagr, Damien Brunner, and Steve Bernier in a tie for 4th among forwards with Michael Ryder.
Travis Zajac: Zajac improved his DZ% by 2.8%, saw his OZ% decreased by 1.5%, and had his NZ% remain about the same. His CC% improved slightly to 39.5%, and of course, his work is coming against the strongest QoC on the Devils. His CF% is 55.9% which is impressive when you consider that game after game Zajac is up against the best the opposition has to offer. Yes, he has Jagr and Zubrus on his wings, but I think Zajac is criminally underrated in the league. He’s more of a passer in terms of his CC% (22% breaks down as SAG, while 17.5% is from iCF), but he’s taken 86 shot attempts this season so he’s no slouch in that department.
Jaromir Jagr: Jagr increased his DZ% nearly 4% and actually increased his OZ% by 0.5%—that’s a first. Jagr, simply, is a beast. His CC% increased 3% to 48.9%, so he’s upped his offensive game recently. He’s behind only Patrik Elias in that department. Jagr leads the team in both shot attempts (114) and shot attempts generated (132), so he’s a dual threat in every sense of the word. Over half of his SAG result in a shot on goal, so there’s enough quality with his quantity.
Patrik Elias: Speaking of Patty, he cracked the 50% barrier in terms of his Corsi Contribution (50.4%). I believe there a two reasons for this: 1)Elias is freaking amazing; 2) Pete Deboer puts him on the 4th line, so who else is really going to contribute? Elias on a line with Stephen Gionta and Steve Bernier? Sigh.
Elias improved on his DZ and NZ completion rates, but his OZ% dropped 1.5%. I mentioned his CC%, but if you look at its components, only 20.7% of that 50.4% is coming from his own shot attempts. Shoot the puck more, Patty! He does have a very strong S/Pass% at 9.7%, so he’s still a great passer, but I’d like to see him be a little more selfish with the puck; of course, I feel like we’ve been saying that for years with Elias. His QoC and QoT figures are about equal given he plays against strong competition, but his QoT will no doubt drop if he remains on a line with Gionta.
Adam Henrique: Henrique has had a great 10 games. His completion percentages rose in each zone between 1.7% and 3.2%. He’s up to 103 SAG on the season, 5 behind Zajac and tied with Elias. Henrique’s CC% is 42.6%, with a similar breakdown to Elias’: 17.4% from shot attempts and 25.2% from SAG. However, he had an almost 6% increase, so he’s really stepped up his game over the last 10. Between Michael Ryder and Ryane Clowe, I see that continuing.
Ryane Clowe: One half of the Newfoundland connection, Clowe’s numbers are still sullied by his early season struggles. Should he stay healthy over the next 10 games, we should start to see more of the player we thought we were getting from San Jose and not the shambolic head case the Rangers traded for.
Michael Ryder: The other half of the Newfoundland connection, Ryder has seen his completion DZ and OZ% climb slightly, while his NZ% increased 3.1%. Ryder attempted 30 shots in the last 10 games and that helped increase his CC% to 39.2%. John has often made the comparison of Ryder to Sykora and that fits if you look at Ryder’s tendency to shoot a ton. I was surprised to see that 10% of Ryder’s passes end up in shots on net though, 3rd highest among forwards behind only Damien Brunner and Steve Bernier.
Andrei Loktionov: Loki had another strong pass stretch. His completion rates increased in each zone and he remained in the 43% range for his CC%. He hasn’t played in enough games while I was tracking SG to warrant analysis on that, but his SAG/CF% increased to 24.6%, behind only Elias, Jagr, and Henrique. Loki remains one of the more accurate passers on the team.
Steve Bernier: Bernier has played in every game this season and in the last 10 managed to increase his DZ% by 2%, but saw his NZ% and OZ% decrease by 3.1% and 3.8% respectively. His 41.8 CC% is 1.5% higher than the last summary. He’s improved his SAG/CF% rate and maintained his solid iCF production. Bernier’s QoC is 0.1% stronger than his QoT and his CF% is a solid 54.7%. His accuracy has gone down, but his production has remained consistent and he has the highest S/SAG% thus far since I’ve been tracking it.
Damien Brunner: Brunner saw his DZ and OZ rates increase slightly, while his NZ% dropped 3.2%. Brunner’s CC% dropped 0.7%, but playing on a line with Elias, one would expect their CC% to drop as they naturally would give way to Elias to dominate production. Even missing 8 of the first 40 games, Brunner has still put up 98 of his own shot attempts, good enough for 2nd of the forwards. Once he returns and rejoins Elias, I’d like to see Loki between them: one of the team’s best passers and one of the team’s best shooters (volume-wise) together with (arguably) the team’s best player would be an exciting line.
Jacob Josefson: Josefson maintained his high completion percentages in the 3 games he played since the last summary. It’s a small sample size, but Josefson did have the 6th most efficient SG/Pass %. He increased his CC% by 1.4%. All his numbers look pretty good for someone who’s played sporadically and with an assortment of line mates. I hope he has a good career elsewhere because it’s obvious he’s not going to get a regular chance under Deober. JJ’s QoT is the lowest of any forward except for Cam Janssen and Tim Sestito.
Mattias Tedenby: Which leads us right into Tedenby. Tedenby improved his completion percentages in each zone. He hasn’t played since I started tracking the shot generated stat. Unfortunately, Tedenby is one of the few skaters that has a sub-50% CF% rate, but has maintained an overall passing accuracy above 80%. He’s playing with better teammates than those he’s skating against, so he should be able to put up better numbers.
As an aside, some of you may be getting tired of my constant banging of the proverbial drum for JJ and Tedenby to get their chance to play consistently. I don’t blame you, but it may continue into the future, so just a warning.
Reid Boucher: Boucher has now played in 12 games this season, but his completion percentages need some work. His DZ% is only better than Stephen Gionta and Tim Sestito. Boucher has a strong CC% of 44% and is equally balanced between his own shot attempts and his SAG. He has a 54.2% CF rate and has enjoyed having an advantage in his QoT of his QoC. Boucher needs to fix his passing, particularly those in the defensive zone, but his offensive contributions have been steady and impressive thus far. A 4th line of him, JJ, and Bernier would prove to be highly effective, I would think.
Stephen Gionta: Gionta came back and played 6 games over the last 10. I’ve made mention of it elsewhere in this article, but his numbers are bad any way you look at them. He is the least accurate passer on the team.
Ryan Carter: Carter hasn’t played since the Rangers OT victory, I believe. By the time this posts, he should make his return and he would make for a solid 4th line player.
Cam Janssen and Tim Sestito: These two just shouldn’t be the lineup. Of the two, Sestito has at least made some passes and contribute somewhat. Janssen is just hard to watch.
I like these pass averages per game charts because it lets us know who is the busiest of the bunch. It’s no surprise Greene and Zidlicky, on average, complete and attempt more passes in each zone than most of the other defensemen. But, this chart reveals similar data in different ways. For example, we know that Merrill completes 14% more of his passes in the DZ than Zidlicky does, but this chart helps quantify that. How so? Zidlicky and Merrill, on average, both complete 11.4 passes in the DZ per game; however, Zidlicky needs 2.5 more passes each game to complete the same number as Merrill. That 14% difference is now more tangible when you look at it as 2.5 passes each game. It’s the same thing in the OZ: Zidlicky needs 5 more pass attempts to complete just 1.2 more passes than Merrill each game.
The forward averages fall into mostly predictable patterns. I’m not sure if games played is the best measure to divide their passes by. Should it be total passes divided by total time-on-ice minutes? Either way, you have to look at the average per game and also take into account the completion percentages. For example, Andrei Loktionov might not attempt as many passes per game as Elias or Jagr, but he is one of only three forwards whose completion percentages in all three zones are above average (Zubrus and Josefson being the other two). I may have to play around with the raw data and divide by their time on ice or something more akin to pass per minute of ice time or something. Thoughts on this? I’m really asking.
What are some of your observations from these averages charts?
Through the first 40 games you can see that each position group is averaging roughly the same amount of passes in each zone. Compared to the averages from the 30 game summary, the completions are up in every zone for the forwards, while the defensemen have seen increased completions in the neutral and offensive zones, with the Avg DZ C remaining the same. The forwards are averaged nearly 4 more passes per game in the OZ than they were at the 30 game mark; that’s a significant increase to move the data from 30 games with just 10 additional games of data.
The Devils as a team are now averaging 193.6 completions per game and 244.5 attempts per game. The SAG totals have increased by 2.2 shot attempts per game and since I started tracking SG, the Devils are averaging 14 shots per game created by passes.
Something New: Pass Percentage by Zone
Here we are at my latest wrinkle to these passing stats: pass percentage by zone. I thought this could serve as another territorial stat if we are ever wondering who spends more time in each zone: sort of a time of possession or heat map or the skaters. I figure that there are more passes each game than shot attempts, so if we isolated a player’s passes by each zone than we’d have something closer to an approximation of how much time they spent in each zone. Make sense? Remember that green and red just mean above or below the position average for that zone; it doesn’t necessarily mean good or bad. And I’m sure that zone starts impact these as well, but let’s take a look just for fun.
What this tells us is that on average, 72.8% of a defenseman’s passes will occur in the DZ, 10.5% in the NZ, and 16.6% in the OZ. Now, we can see that 22.7% of Zidlicky’s passes are at the offensive end of the end, 3.5% more than any other defenseman. He also has the lowest percentage of passes at the Devils end of the ice. You can also see how conservative (timid?) Larsson was early on this season, as only 9.5% of his passes were in the OZ.
For the forwards, their averages were 27.4% of their passes occurred in the DZ, 17.6% in the NZ, and 55.1% in the OZ. Stephen Gionta had the highest percentage of passes in the defensive zone. What can that tell us? Is it that Gionta is pinned back more than any other forward? Remember that these are just 5-on-5 stats, so it doesn’t take any penalty killing into account. After Gionta, Cam Janssen and Ryan Carter had the next highest percentage passes in the DZ, so you can see by that trio that this is another stat that affirms what we already know about these players: generally, they will get beat in possession and pinned back in their own zone.
At the other end of the ice, Zubrus leads the team with 63.2% of his passes occurring in the OZ. Next highest? None other than Deboer’s favorite Swede: Mattias Tedenby! Zajac and Loktionov are the only other forwards who exceed 60% of their passes in the OZ. Oh, and 55.4% of Josefson’s passes occur in the OZ as well: nearly 12% more than 4th, no 3rd, no wait, 2nd line center Gionta. I give up: will someone please explain to me in the comments why Stephen Gionta is one of the 12 best forwards on this team? Seriously, am I missing something? Every stat I look at or put together continually shows he’s one of the worst players on the team: he’s the Peter Harrold of the forwards.
Anyways, what are your thoughts on this new chart?
In the Next Review
I think that I’m going to wait until the Olympic break to put together the next summary. That will after the first 59 games. I’d like to combine the PE% data from the Zone Exit summaries and compare it to the passing data in order to see if there are any patterns there. What are your thoughts on this latest summary? Anything you’d like to see added? Sound off below!