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Category: Analysis

Measuring defense: Relative Corsi and Corsi Against

Dan Girardi: once again, Mr dependable. Photo: McIsaac/Getty

Photo: McIsaac/Getty

If you’ve been reading this blog for a while, you know that we like to combine what we see in the goal breakdowns with what we see in the stats. We are a bit limited by time constraints (thus no gifs or pictures of non-goal events), but we point out various areas where the Rangers have defensive breakdowns that lead to goals. While only pointing out goals is limited –If someone wants to pay me to do this full-time, I’ll gladly point out more plays. But I don’t have the time. So those of you complaining, quit it, it’s annoying and rather pointless– it is useful.

The defensive breakdowns are what we see with the eye test. And while the eye test should never be ignored, it does tend to focus on big screw-ups and lend itself to bias. It’s why defense should also be measured by two key metrics: One that we use regularly (relative Corsi) and one that we admittedly don’t use enough (Corsi Against).

Relative Corsi you are familiar with, as it measures possession on the ice relative to the rest of the team when off the ice. The concept here is that the higher the number, the more time you have the puck in the offensive zone, thus limiting opposition opportunities. Corsi Against measures shot suppression, which is a measure of relative Corsi, and shows us the shot attempts against while on the ice.

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The Rangers are bad at faceoffs, but how bad is the effect?

Dom Moore was brought back on a sensible deal - careful planning? (Photo: Dave Sandford/NHLI)

Photo: Dave Sandford/NHLI

I’m sure you’ve noticed this by now, but the New York Rangers stink on faceoffs. They are at 47.2% right now as a team. Of the players that have taken at least 50 faceoffs, only Derick Brassard (55.4%) and Dominic Moore (53.3%) are above 50%. Martin St. Louis (43.6%) and Kevin Hates (24.6%, ouch) bring up the rear for players that have taken 50 faceoffs. Derek Stepan isn’t a 50% faceoff guy, so his return won’t really help in that department.

But how much does this affect the on-ice product?

Statistical Sports Consulting printed a study on the effect of faceoffs on goals, and the results are pretty interesting. They first measured the faceoff differential to yield a goal differential, then measured the probability of winning a faceoff (Note: Not 50/50, there’s skill involved).

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Building a better goaltending statistic

Over the past few years, the debate has grown more intense about the validity and reliance on #fancystats. The concept of quantifying the game has been a theme we have run with around here, albeit with the conceit that there is no perfect, all-knowing stat that can be universally relied upon to demonstrate a player’s ability level.

Statistics trying to quantify human athletic performance are inherently limited. There are very human characteristics in play; such as intelligence, judgment, emotion, situational awareness, etc. It makes it difficult to measure performance as if they were vital signs. I think that to fully expect that level of quantification or to vilify the statistic for being unable to is missing the point.

Much like politics, I think the emergence of these statistics and the resistance to adoption has pushed the two positions out to the extremes. The old school hockey community has written them off or marginalized their effectiveness, citing “games are played on the ice, not on a spreadsheet”, or taking pot shots at the Maple Leafs for hiring Kyle Dubas for their Assistant GM position, and various stats writers to make up a new analytics department. Read more »

New Rangers lines expecting different deployment strategies

Rick Nash is Canadian for frustrating.

Really need a big year from you buddy.

If there was one thing proven about Alain Vigneault’s coaching style over the years, it’s that he tactically deploys his lines (after a whistle) depending on the zone start and the opposing line sent out. Last year we saw the Brian Boyle-Dominic Moore-Derek Dorsett line get the majority of their starts in the defensive zone, while the Mats Zuccarello-Derick Brassard-Benoit Pouliot line received primarily offensive zone starts. It is a common practice among coaches.

This year the lines have been shaken up with the turnover, and the matchups will likely change, both in zone starts and in quality of competition faced. Using the lines from practice the past few days, we can make some guesses.

Chris Kreider-Martin St. Louis-Rick Nash

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A glance at the score sheet from last night’s game



Obviously a lot of these stats can be taken with a grain (or mountain) of salt and I unfortunately do not have access to the “fancier” stats but I wanted to point out a few things that stood out from last night’s score sheet:

  • The Rangers Fenwick For (FF) was 33 and their Corsi For (CF) was 38. The Devils FF was 45 and their CF was 58.
  • The Rangers penalty kill allowed 1 goal that came from a 5-on-3 and killed off six 5v4 power play chances for the Devils allowing 6 shots.
  • Ryan Malone led the Rangers with 4 shots in 12:33 TOI. Three Rangers had 3 shots. (St. Louis, Bourque and Kristo).
  • Kevin Hayes was 6/11 in faceoffs, J.T. Miller was 8/18, Chris Mueller was 8/15 and Matthew Lombardi was 6/14.
  • The Rangers as a team won 57% of their PP draws and 57% of their short handed draws. At even strength they won 44% and their total for the game was 48%.

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Taking a look at John Moore’s 2013/14 season

john moore

Incase you missed it the Rangers and defenseman John Moore finally reached an agreement on a one-year $850,500 contract on Wednesday. Moore, who is slotted in to the Rangers bottom defensive pairing once again, will be entering his fourth NHL season in 2014/15. At 23 years old (24 in November), the 2009 first round draft pick is running out of time to make me, amongst others, find confidence in his ability to blossom into the top four defenseman we were told he could be.

After noticing a lot of debate amongst Rangers fans I decided to take a closer look at Moore’s 5v5 metrics (his PP TOI was too small a sample for me to consider of any value).

The first thing that pops out when looking at Moore’s 5v5 numbers is his zone start percentage (ZS%) of 64%. Amongst 2013/14 Metropolitan Division defensemen this was the highest ZS% for anyone. Moore should have been able to thrive being placed in the offensive zone as often as he was, however his result was less than impressive. Moore held a corsi for percentage (CF%) of 51.7% with his relative CF% (relCF%) at -1.26%, an awful number when taking into account how he was handed the offensive zone on a silver platter. This is not out of the ordinary for Moore, who has failed to record a positive relCF% since breaking into the league with regular playing time in 2011/12 .

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Tracking the Rangers zone entries & exits for the upcoming season

Mats Zuccarello

Over the course of the summer there has been one major topic that continues to pop up in the hockey analytics world: tracking zone entries and exits. The concept was originally brought to the forefront of the analytics community by blogger turned NHL consultant, Eric Tulsky. From there the idea of tracking these events took off, most noticeably with Corey Sznajder (creator of the Hurricanes’ blog “Shutdown Line”) who undertook a huge workload this summer by tracking every entry and exit from every NHL game of the 2013-14 season.

That’s just a little bit of the background, but why is tracking entries and exits so important?

The days of chip and chase hockey are slowly dying. Just like everything else in this world, hockey is evolving. Many teams have hired people to head up analytics departments this summer, including the Rangers (Jim Sullivan). Puck possession is as valuable as anything else in the game. The belief is that carrying the puck into the offensive zone is a more efficient play than dumping and chasing, and ultimately results in more shot attempts. At the same time, carrying the puck out of your own end results in more success through the neutral zone than stretch passes through multiple opponents. By tracking these events game by game we will be able to get a sense of which players can sustain high possession numbers and contribute to a teams shot total, which in turn will contribute to goals scored.

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Playoff Predictions 2015: Who will be back?

Is it hockey season yet?

Is it hockey season yet?

Throughout the course of a season, a team will play 82 games in the hopes of playing just four more rounds for the chance to hoist Lord Stanley’s Cup. These 82 games are no walk in the park. They consist of grueling hits, tough goals and workouts that most of us would pass out or throw up halfway through. These athletes do it because they want to know the glory of being the very best, having their names etched in glory forever on the greatest trophy in all sports.

Of the 30 teams in the NHL, 16 make it to the first round of the playoffs. For certain teams, making the playoffs is a distant dream. For others, missing them is beyond unacceptable. Below is the breakout of the first round from April 2014:


s/t CBS Sports

s/t CBS Sports

So which of these teams will most likely make it again?

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Using Corsi to measure goals for the Rangers

AP Photo/Gene J. Puskar

AP Photo/Gene J. Puskar

If you’ve been reading us for a while, then you know we are proponents of the new stats that have popped up over the past few years. One that has really taken hold in the community, and led to the hiring of several “stats guys” around the league, is Corsi. Corsi is a measure of shot attempts (on net, missed, or blocked) taken for or against while a player is on the ice. It’s basically the plus-minus of these shot attempts. If Player X is on the ice for three shot attempts for and one shot attempt against, then that shift he was +2 for his Corsi (also a 75% Corsi). Fairly simple concept.

Ignoring some of the noise associated with these stats, the biggest complaint that comes up with the possession metrics is that it doesn’t measure goals, and goals win games. It’s tough to argue with the logic, because it’s partially true. Great work has been done proving that possession directly correlates to wins with large enough sample sizes, but it still doesn’t measure goals. Pucks in the net are what matter.

Luckily, the guys at Hockey Graphs have begun breaking ground on this front. They did a lot of the legwork in measuring goals via possession numbers, and that post is definitely worth a read in its entirety. But to summarize: Players can be separated into four buckets (forwards) or three buckets (defense) based on ice time. Each player falls into a bucket based on ice time, and you can use their Corsi% to project a goal differential across the season.

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PK Subban and the $72M contract

Troll City

Troll City

Montreal Canadiens’ GM Marc Bergevin made PK Subban the third richest player n the National Hockey League yesterday, locking the defenseman down for 8 years at $72 million dollars or, for those mathematically challenged, $9M a year. This comes after the 25 year old Norris Trophy winner of the lockout-shortened 2013 season made only $3.75M last year. The deal was the first to go to arbitration since 2011, despite being settled independently after the first hearing.

With the Jonathan Toews and Patrick Kane signings being significant, it’s important to take a look at the Subban signing as well. He’ll likely be their next captain, as former captan Brian Gionta left for Buffalo during this offseason, and Subban is viewed to be an enormous talent who is outspoken, to say the least. The defense in light of such figures is that with the Canadian TV deal signed last year should raise the cap enough that, towards the end of this deal, Subban will be a steal. But is this logical? Read more »