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2013 - 2014 Devils Passing Review: Devils vs the Atlantic Division

This is a look at the how the New Jersey Devils fared against their Atlantic Division opponents in the passing game. Read on for the details.

Noah K. Murray-USA TODAY Sports
This is a look at how the New Jersey Devils and their opponents fared in their Atlantic Division matchups this past season. As I’ve written a lot on the Devils with obvious reasons, this post will focus more on the opposing players. Since the sample size for these players and teams is only from two to five games, we’ll treat this as “What Players/Teams were the Devils able to contain?” and also, “Which Players/Teams had their way with the Devils?” In the interest of brevity, on an individual level, I’ll be looking solely at shot generation and Corsi contribution; on a team level, I’ll be looking at efficiency and where shots were generated from.

These four posts will serve as a bit of a preview to future work done on systems, what teams do to counter other teams, and more in-depth analysis. Why were the Devils more/less effective against certain teams? As sample sizes of the opposition grow, we may be able to venture educated guesses into how and why. Let’s get to it.

Summer Passing Series Links


Part One: Efficiency and Winning

Part Two: The Transition Game

Part Three: Offensive Zone Analysis

Part Four: Generating Goals

Part Five: Corsi Contribution

Part Six: Frequency of Offense

Part Seven: Does Accuracy Matter?

Part Eight: Team Comparison

Part Nine: Devils and the Metro

Buffalo Sabres


While the Sabres were nothing resembling a competent team this season, they still managed to play the Devils close (like they always seem to do). The team has made lots of moves recently in an attempt to tank and get Connor McDavid, but they should not have gotten rid of Christian Ehrhoff. In three games against the Devils, Ehrhoff generated eight attempts, six shots, and 46.2% of the Sabres offense ran through him. Unsurprisingly, the Sabres Corsi For was highest when Ehrhoff was on the ice. At the contract they had him at, I’ll never know why they bought him out. In his only game against the Devils, rookie Ramsus Ristolainen generated three attempts and two shots—a solid performance by a young player.


The forward who was on the ice for the most Corsi events for the Sabres was Matt D’Agostini. Yea, I didn’t believe it either. The forwards were woeful as no one came close to matching Ehrhoff’s eight SAG. The closest were Tyler Ennis (5) and Johan Larsson (5). Zemgus Girgensons generated four attempts, but each one resulted in a shot, so that was efficient play. The Sabres’ forwards will be interesting to monitor this coming season as they could be an exciting group if second overall pick Sam Reinhart joins the likes of Larsson, Girgensons, and veterans Matt Moulson, Ennis, and Cody Hodgson. They still might lose, but they might lose in a more entertaining manner than last season.


The Devils controlled the greater share of shot attempts in both transition and the offensive zone, yet were 12% less efficient than the Sabres. What’s noteworthy is the low volume from the Sabres: in three games, they managed to only generate just over thirty shots.

Boston Bruins


Torrey Krug was really the only blue liner that did damage in the passing game against the Devils in their three matchups with the Bruins. He generated five shot attempts and four shots.


David Krejci and Brad Marchand had similar offensive outputs in the passing game as each generated nin shot attempts and four shots. They were both on the ice for over twenty Corsi events for Boston, yet Krejci attempted more shots on his own: six to Marchand’s three. Jarome Iginla generated six shot attempts and five shots, while added four shot attempts of his own. Krejci was the most involved forward of Bruins players over twenty Team CF.


Important to keep in mind was that the third game of this season series was the Devils final home game of the season in which the Bruins rested several key players (Zdeno Chara, Milan Lucic, Patrice Bergeron, etc.), so it does skew these totals somewhat. The Devils were still behind their opposition in terms of efficiency.

Montreal Canadiens


PK Subban generated six shot attempts in his three games against the Devils, leading the Montreal blue line. Andrei Markov generated one fewer attempt (5), but one more shot (3) than Subban. These two were on the ice when Montreal attempted their most shot attempts (Team CF), but were not as involved as often when compared to Rafael Diaz. Diaz contributed to 36.1% of the team’s thirty-six shot attempts compared to Markov’s 31.7% and Subban’s 20.5%. Oh and Douglass Murray and Francis Bouillon are probably not needed.


Max Pacioretty and Lars Eller each generate ten shot attempts against the Devils. Pacioretty was particularly efficient as seven of those ten registered as shots (only three for Eller). When Pacioretty (41) and Brandan Gallagher (42) were on the ice, Montreal attempted its highest number of shot attempts. Pacioretty was involved in just over half (51.2%) of those 41 shot attempts. Tomas Plekanec and Gallagher led the group with fourteen of their own shot attempts (iCF) and contributed to 54.3% and 45.2% of the team’s on-ice Corsi respectively.

In the three games against the Devils, Brian Gionta and David Desharnais illustrated how different their roles were. Gionta generated three shot attempts and zero shots, but attempted thirteen of his own; Desharnais generated seven shot attempts, five shots, and attempted only one of his own. Desharnais clearly was more of setup man in this games, while Gionta was more of shooter.


Same story, different chapter. Devils controlled nearly two-thirds of all offensive zone shot attempts, but Montreal was more efficient (10% better) and controlled more transition shot attempts (5% more).

Toronto Maple Leafs


The Leafs D generated twenty-six shot attempts and only eight shots, which is quite terrible. Jake Gardiner led the group with 8 SAG, but only 1 SG. Dion Phaneuf led the blue line in shot attempts (11) and was the Leafs most involved defender as he contributed to 55.2% of their Corsi events (16/29). Morgan Reilly attempted eight shots, but failed to generate a single one. Carl Gunnarson was just behind Gardiner in volume of shot attempts generated (7), but only offered a single shot attempt of his own going forward.


Nazem Kadri led Leafs forwards with ten shot attempts generated, six of which resulted in actual shots. He also attempted eleven shots himself, contributing to 60% of the Leafs Corsi events. He was only bettered by Phil Kessel who generated nine shot attempts and attempted fourteen for a 65.7% contribution. Of course, Kadri’s passes were more efficient as they led to two more shots, but both really drove the bus for the Leafs.

Tyler Bozak was the Leafs most efficient forward as he generated seven shots on nine attempts, but offered little in terms of his own shooting (two attempts). Mason Raymond also generated nine shot attempts, yet only three shots. Lots of volume of the Leafs, but the efficiency was mixed, though it was better than the blue line.


The Leafs controlled 59.1% of the shot attempts in transition, but only34.4% offensive zone shot attempts and were slightly behind in SAGE (45.6% to the Devils 47.9%). When teams control larger shares of transition shot attempts but are behind in SAGE that is a sign that their opponents were vastly more effective in the offensive zone. Considering transition shot attempts are more likely to actually register as shots, the Devils were all over the Leafs in these games.

Florida Panthers


In terms of volume, Brian Campbell led the way, generating seven shot attempts and three shots. The Panthers attempted forty-one shots while Campbell was on the ice, and he contributed to fourteen of them (34.1%). There wasn’t much volume from the rest of the Panther’s blue line, but when they did generate shot attempts, more often than not they would register as shots, so it was decent group in terms of efficiency (ten shots on eighteen attempts).


Alexander Barkov only played in one of the three games against the Devils, but he was massive in it. With Barkov on the ice, the Panthers attempted twelve shots: Barkov generated seven and attempted two, contributed to 75% of the team’s Corsi. Nick Bjugstad generated seven shot attempts and four shots, attempted eight of his own and contributed to 53.6% of the team’s Corsi. Bjugstad was on a line with Brad Boyes and Sean Bergenheim which received the nickname “Killer Bs” from Panthers fans. They did play well together and would be a solid depth line for any team, but the Panthers need a bit more quality at the top of their lineup. Jonathan Huberdeau generated five attempts and three shots over two games against the Devils. Scottie Upshall led the group with ten shot attempts, one more than Boyes.


The two teams split the transition shot attempts generated and the Devils controlled 59.5% of the offensive zone shot attempts generated. The Panthers won the efficiency battle 52% to 43.3%.

Detroit Red Wings


The Red Wings blue line generated only fifteen shot attempts and eight shots over three games. Their matchup against the Devils was one that seemed to game plan in a specific way. Their defensemen would linger in their own end and make a pass to a forward as they entered the Devils zone. The forwards did most of the work from there, but it was a very quick transition from defense to offense. When I track A2 SAG figures (potential second assists) this coming season, I’m hoping this may shed more light on a system like the Red Wings.


The efficiency from the Red Wings forwards was astounding. 57.4% SAGE is crazy good. Johan Franzen was a beast (7 SAG, 6 SG), David Legwand, in his only game with the Red Wings against the Devils, generated five shots on only five attempts. Gustav Nyquist led the group with eleven of his own shot attempts, but still managed to generated four shots on eight attempts. Daniel Alfredsson generated five on nine. It went on and on like that. Most of this offense came in the home-and-home series the two teams played in early March.


The Red Wings controlled 63% of the transition shot attempts and managed to keep close to the Devils in terms of offensive zone SAG (45% - 55%), an area the Devils usually dominate. They were very efficient, operating at 56.6% in their passing, compared to the Devils’ 46.3%. Systems like the Red Wings will be of more importance this coming season.

Ottawa Senators


Well, Erik Karlsson is good. He generated ten shot attempts, five shots, and attempted fifteen of his own in Ottawa’s three games against the Devils. There wasn’t much behind him in terms of passing offense as no one else averaged more than one SAG per game.


The Senators attempted the most shot attempts with Clarke MacArthur on the ice and MacArthur contributed to nineteen of the forty shot attempts (nine via pass and ten from his own shooting). Jason Spezza was the team’s best passer, generating ten shot attempts and seven shots while adding eight of his own shot attempts (60% CC). Kyle Turris led the team in volume with fourteen SAG, but only five resulted in actual shots on net. Nevertheless, Turris was involved in 55.3% of the team’s thirty-eight shot attempts while on the ice. Very involved.

Matt Stone played in only one game against the Devils this past season, but was very efficient. He generated three shots on four attempts. Zac Smith put up identical passing stats to MacArthur (four shots on nine attempts).


The Devils were actually more efficient than the Senators (55.4% to 48.3%), but once again gave up a considerable amount of offense in the transition game (61.1% to 38.9%). The teams’ were quite even in offense generated in the offensive zone. The Senators were one of the few Eastern Conference teams to generate more offense via their passing than the Devils in their head-to-head matchups.

Tampa Bay Lightning


Sami Salo (7 SAG, 4 SG), Matt Carle (8 SAG, 5 SG), and Victor Hedman (6 SAG, 1 SG) were the busiest defensemen for the Lightning. Rako Gudas attempted thirteen shots, but did next to nothing in the passing game (1 SAG). Carle was the most involved based on the Corsi the team put up while he was on the ice (47, 36.2% CC). Lightning_f

The Tampa Bay Lightning should probably win a Cup in the next couple of years. They have so many good, young forwards it’s not even funny. Ondrej Palat generated seven shots on nine attempts and contributed to 53.6% of the team’s Corsi while on the ice. Nikita Kucherov, in one game, generated five shots on eight attempts and attempted five shots of his own. Tyler Johnson generated four shots on five attempts. Alex Killorn generated four shots on six attempts. This is just a very efficient and talented team.

Oh yea, then they have some guy named Steve Stamkos and Jonathan Drouin hasn’t even played in the NHL yet. So glad they aren’t in the Devils division.


The Lightning controlled 69% of the transition shot attempts and nearly evened out with the Devils in offensive zone shot attempts generated (46.1% to 53.9%). They were 14% more efficient than the Devils.

Lend a Hand, Will Ya?

As I mentioned in the opening paragraph, with more data comes more concrete analysis. As any statistical work should do, this process evolves and becomes more refined based on what is most relevant. After compiling all of this data for a season of the Devils and their opposition, I’ve discovered that about 10% of the tracked data tells us 90% of what’s relevant. By this I simply mean passes that lead to shot attempts and shots tell us far more than the passes that do not lead to events. I’ve decided to change up my approach for the coming season.

I’ll be updating my Primer to reflect this, but by adding new categories for how and where shot attempts are generated, it will give us a more in-depth look at how and where teams create offense and what players are more involved than others. In addition to this, I’ll be tracking all 5-on-5 situations as well as 5-on-5 close situations to be able to account for score effects. An added bonus is that this significantly reduces the amount of events I’ll be tracking and makes it much less time-consuming. That’s where you come in.

If anyone has been interested in tracking stats or has tracked zone exits or entries previously and wants to try something new, feel free to hit me up on Twitter (@RK_Stimp) and let me know. If you just did one team, you’d probably be looking at 50 – 75 events each game, which isn’t too bad and won’t interrupt the flow of the game that much if at all (think 15 – 25 events per period). Let me know and don’t be shy.