Visualizing Corsi and the Blue Jackets

I haven’t had an ample amount of free time lately, but I’m hoping to finally get this blog off of the ground.

I’ve been following along with @mc79hockey for awhile now and his insight into the world of fancy stats is probably the best you can find. Yesterday he posted a visual that compares 5v5 Corsi% when a forward – defenceman combination is on the ice. It was inspired by a post over at Arctic Ice Hockey which pointed out that they’re a good team when certain players are on the ice, and a bad team when those players are not on the ice.

Canucks Army writer @camcharron took the same concept from mc79hockey and applied it to a post that was specific to the Canucks. I’ve used his method to come to the results below.

Basically, the chart I’ve provided is separated by forwards with the most TOI/60 on the left, and defencemen per TOI/60 above. The numbers you see are their Corsi For % while on the ice together during all 5 on 5 situations. Green is good (over 50%), pink/red is bad (less than 50%). 


Stats are courtesy of

Corsi is the sum of blocked shots, missed shots and shots on goal. Corsi for percentage = Corsi for / (Corsi for + Corsi against). 

Mc79hockey sums up the purpose of this exercise very well:

If we assume that the coach uses his best players the most, we would expect that the Corsi% for when the most heavily used defenceman and the most heavily used forward are on the ice to be the highest on the team, barring something really unusual – a defenceman who plays exclusively in the defensive zone or something. … If my theory’s right, things should get worse as we move from more frequently used to less frequently used players.

This is purely an exercise in extracting information, but I’ve taken the liberty of adding a few of my examinations.

Now, I’ve been searching for an effective way to expose the horrid play of Jack Johnson, who is adored in Columbus and I’ve never understood why. He gets more ice time than any other defender on the team, but his numbers here are the worst on the team. His shifts generally begin in the neutral zone (43.2%) with 1/3 shifts beginning in the defensive zone and 1/4 in the offensive zone, so it isn’t like he is one of those exceptions that plays only in defensive zone situations. He’s just a bad hockey player, and he makes players around him worse. These numbers are not limited to this season only. Johnson, since his entrance into the league in the 2007-08 season, has peaked with a Fenwick for percentage of 48.5% twice in 2009-10 and 2010-11.

However, Tyutin isn’t very appealing either, but it’s tough to say if his numbers would receive a bump if he wasn’t constantly paired with JJ. He’s played less than 66 minutes with any one of the rest of the defencemen on the team and his numbers hover around 33% while on the ice with those players. Given this fact, perhaps Tyutin is dragging down Johnson’s numbers, but I’m led to believe they are both anchoring each other down since Johnson’s numbers are less than stellar when paired with other defencemen as well.

If you’re having trouble accepting these numbers as evidence, let’s look at the d-pairing that was on the ice in overtime against St. Louis this past Saturday. Johnson and Tyutin started the OT period and within seconds Johnson turned the puck over which led to David Backes scoring the game-winner 22 seconds into OT.

Scott Howson traded Jeff Carter to obtain Jack Johnson, but he also drafted Ryan Murray who stands out on this chart. The rookie has shown a level of competence that most defencemen strive to achieve during their peak. His pairing with Wisniewski should not be tampered with unless it is to give them more ice time.

Offensively, Dubinsky, Johansen and Atkinson are the leaders of the pack. This should really come as no surprise. Gaborik’s numbers can be overlooked because he’s missed so much playing time and we’ll have a better opportunity to gauge how effective he really is once he’s returned to the lineup.

The last observation is the 4th line. MacKenzie, Comeau and Letestu are a very effective 4th line. Their numbers hover near or above the 50% mark in most pairings and you can’t ask for more than that. Once Horton makes his debut, Umberger can finally be bumped to the bottom 6 permanently and, with exception to the top 2 defenders, the Blue Jackets should have a well-rounded team that can compete for a playoff position.

But I’m often too optimistic about the Blue Jackets.



  1. […] hard to understand, this article breaks it down and provides a color coded, easy to read graph. [ Rubber Duck Hockey […]

  2. anon coward · · Reply

    It would be interesting to compare the chart to actual +/- %, instead of just Corsi % numbers – to see if they correlate.

    Here’s my rationale, defense men fall in to a spectrum of offensive-minded to stay-at-home. The latter won’t generate as many shots by virtue of not being in a position to shoot, but that doesn’t necessarily mean that they give up goals either, because they maybe blocking shots, etc. And on the otherhand, an offensive defense man might get shots but give up weak goals.

    1. Sure thing. This kind of analysis could also broaden the understanding of Corsi as well. I’ll keep this in mind for future posts.

  3. […] Canucks. In the comments section of Cam’s post, I noticed links to the same chart for the Blue Jackets and Rangers. Although, I am not sure if these last two examples filtered by at least 60 minutes of […]

  4. In regards to Tyutin, I would say that Jack Johnson is dragging him down, not the other way around. Johnson was pretty much the reason the Kings went from a middling 6-8 seed with him to one of the dominant teams in the league without him. He is one of the very worst players in the NHL.

  5. […] has also been noted to make players around him look as though they are performing worse, as he drags his teammates’ Corsi percentages down as […]

  6. […] I made one of these charts earlier this season in December, if you’d like to compare the two charts you can view the post here. […]

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