Cam Charron

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Eventually, “Corsi” is going to have to take on a different name. “Corsi” had a good run, but in the end, it’s difficult to carve widespread acceptance of statistical concepts named for the person that created it. Often, I’ll see somebody write out CORSI as if it were an acronym for something.

“Corsi” isn’t really particularly complicated. It’s the number of shot attempts for, minus the number of shot attempts against. It can be used for both a team or an individual. For the team, “Corsi” would count up all the shot attempts a team took in even strength situations and subtract them by the ones their opponent fired against their net. For an individual, you just look at the time he was on the ice.

It’s not a real difficult concept, nor is it difficult to understand what it means. “Corsi” doesn’t assume that every single shot taken on goal is of equal value. All “Corsi” does is approximate zone time. If Pittsburgh takes 5 shots at the New York Islanders’ net and the Islanders take 1 shot at the Penguins net, the logical assumption is that the puck spent more time in Pittsburgh’s offensive end. It doesn’t mean anything more than that. Heck, the one Islander shot could be a breakaway from Michael Grabner or Frans Nielsen. It doesn’t change that the majority of the game was spent with the puck on the stick of a Penguin player.

There’s no substitute for real good puck possession.. In the first half of 2011, the Minnesota Wild drew glowing reviews for their ability to win games despite being outshot. Like the 2013 Toronto Maple Leafs, a lot of proponents of defensive coaching systems are suggesting that Randy Carlyle is creating a style of play that makes the shots given up by Toronto easy on the goalies.

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Hockey’s counting problem

alberts orr

So the analytics movement has gone mainstream. I’ve seen references to the website Behind the Net in several major daily newspapers over the last two weeks. And now, Elliotte Friedman wrote a fairly popular blog post on the subject at CBC. His work itself has a line or two that I’d quibble with, but it’s pretty enlightening about the state of analytics in hockey:

The biggest problem for the NHL is the sport just doesn’t have the statistical bent of others.

“We are third, behind baseball and basketball,” [Washington assistant GM Don] Fishman said.

So teams are creating their own. Because there is no consensus, they are notoriously secretive. One thing I believe some teams do is remove “second assists” from players and see how many points are left over. But good luck trying to confirm that.

I find a lot of useful information in hockey has made its way through the Internet. A lot of the statistical bloggers who have been hired to do some consulting work for NHL teams still post quality information on their websites and it’s not like the whole project is going dark.

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mike brown

intangible |inˈtanjəbəl|

adjective

unable to be touched or grasped; not having physical presence: my companions do not care about cyberspace or anything else so intangible.

• difficult or impossible to define or understand; vague and abstract: the rose symbolized something intangible about their relationship.

• (of an asset or benefit) not constituting or represented by a physical object and of a value not precisely measurable: intangible business property like trademarks and patents.

noun (usu. intangibles)

an intangible thing: intangibles like self-confidence and responsibility.

There’s our official Apple dictionary on the word “intangible” which gets thrown an awful lot around hockey conversation. Google “intangible NHL” and you get about 23 million results, compared with 15 million for the NBA, 843,000 for the NFL and 412,000 for MLB.

In hockey I guess we love our players who bring things that are tough to define. The top Google result for “intangible NHL” comes from Scott Cullen at TSN who used several different statistical categories to come up with an “Ingangibles rating” at the conclusion of the 2011 NHL season. Greg Zanon led the NHL in intangibles and Ryan Callahan was second.

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Pittsburgh Penguins v Washington Capitals

By the time I was born, Wayne Gretzky had played his last game with the Edmonton Oilers. I never got to see them, and all through my childhood I had difficulty placing Gretzky in an Oilers uniform. I saw pictures and hockey cards, and the occasional TV clip, but it always looked weird to me to see Gretzky in something other than a Los Angeles Kings’ sweater.

The Oilers of the 80s are discussed a lot, and they have an impressive collection of stars and Hall of Famers and records and Stanley Cups. That said, it is difficult to imagine just how dominant they were. The first year they won the Cup, they had 446 goals, 86 more than the second place team. That’s more than a goal a game, which is wild, but in the end, just by visualizing, it would have taken a few weeks dedicated viewing for somebody who wasn’t counting the score to gather that Edmonton was putting goals at a much faster rate than Quebec, the New York Islanders or Minnesota.

That’s why things get recorded. Numbers and the detailed notes taken by stat geeks counting scoring chances or zone entries, or the guys in the NHL booth tracking the data that becomes the skeleton for our Corsi and Fenwick models. There’s that, but there’s also goals and assists and points to record for individuals, and goals for each team. For a sport like mixed martial arts, scores are awarded based on subjectivity. There’s no running point total on the board, just three trained guys sitting near the ring each with an interpretation of what leads the victory.

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blocked shot

You can use numbers to prove pretty much anything.

The NHL publishes five types of RTSS, or “real-time scoring statistics”. These are “hits” “blocks” “missed shots” “giveaways” and “takeaways”. They produce a mountain of data and quite oftentimes, there’s so much numbers available that people are constantly adding and subtracting and dividing these numbers to paint a rational picture of why teams are succeeding as they are.

This tweet from Sault-Ste. Marie Greyhounds head coach Sheldon Keefe caught my eye:

I’ve never met Sheldon, but I have heard that he has “a real affinity for advanced stats”. I’ve seen the RTSS used so many different ways. I saw a blogger two years back mention if Detroit is such a good hockey team, why are they always ranked so low in takeaways and blocked shots? (Her conclusion was that the Red Wings were flawed, not the numbers) I’ve seen people credit Toronto being first in hits for why they’ve improved this season (side note: after 19 games this season, the Leafs have 22 points. After 19 games last season, the Leafs had 22 points). I’ve seen defencemen judged by their “giveaway:takeaway ratio”.

The most egregious over-analysis of these numbers was CBC during last playoffs who added blocked shots and hits together to form some sort of catch-all “grit” rating that had the Rangers ranked very high. PJ Stock alluded to both numbers in the pre-game show for the Leafs game against Ottawa on Saturday. (Don Cherry Saturday mentioned toughness as a reason the Leafs are improved by, again, zero points)

The problem with these numbers is that they lie and that they really mean the exact opposite of what you’d think they mean. In the real world, a “giveaway” is actually preferable to a “takeaway”. In the real world, “blocked shots” correlate so highly with losing you may as well just be counting goals against. In the real world, the importance of “hits” is imaginary.

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Ultimately, most of today will centre around Taylor Hall talk. How dirty is Taylor Hall? How many games suspension will Taylor Hall get? I’m not too sure on the first, since I don’t know Taylor Hall. The only thing I know for sure about Taylor Hall is that he bears a striking resemblance to the stoner that worked electronics the summer I worked in the warehouse of a large Canadian retail chain. I don’t think that on those qualifications that I know enough about Hall to discuss his personality or intentions with regard to his hit on Cal Clutterbuck Thursday night:

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Goaltenders are like football quarterbacks and baseball pitchers in that they play their sports’ position that’s judged by the dubious ‘wins’ and ‘losses’ statistics.

Unlike football quarterbacks and baseball pitchers, goaltenders aren’t tasked with the role of putting the play in motion. A pitcher can control the flow of a game—oftentimes an effective pitcher will speed up and slow down his rhythm to get in batter’s heads, like a veteran golfer in a match game. A quarterback is limited by the play clock, but otherwise snaps the ball, and usually has the power to change the play at the line of scrimmage.

Consider Jonathan Quick. Nothing has gone right for Quick this season. He’s been bad, surely we can all admit that much. Perhaps the Los Angeles Kings are giving up some quality shots in front of him, but no goaltender should make it through 10 games after coming into a year with such high expectations. Many pundits picked Quick for the Vezina Trophy. Many more pundits picked the Los Angeles Kings to be the top team in the Western Conference. With more than a quarter of the season done, the Kings, after a 3-2 loss to Chicago on Sunday, sit four points out of a playoff spot.

Wait, four points is not all that much, and the Kings still have games in hand over the teams they’re trying to catch up to. Rumours of their demise have been greatly exaggerated, and Quick, well…

Of course, Quick did stop 34 of 37 on Sunday for his fifth “quality start” on the season.

Again, Quick doesn’t have the ability to control the game on his own. We’ve seen goaltenders win and lose games all by their lonesome, but when a goaltender like Quick is struggling, particularly on a very good team that doesn’t give up a tonne of shots, it gives the man less opportunity to redeem himself and find that form from last season’s playoffs.

I bring up the word “regression” a lot, and that’s because particularly at a position like goaltender, where a player isn’t in control of the game, can have so many goals against happen as a result of bad bounces, things are never as good as they seem, nor as bad as they seem.

Blogs are a visual medium, so I’ve taken the liberty to paste out a chart I put together of Quick’s career to date (via Hockey Reference). The blue line is Quick’s career save percentage, and the red line is Quick’s save percentage in his last ten games.

The pattern is distinct: the blue line has slowly progressed throughout Quick’s career, as he’s gotten more experienced and faced more pucks, and the red line bounces up and down, with slightly higher peaks and slightly higher valleys than previous.

In January of 2011, Quick had hit what was his lowest point in his career to date. He had gone just 2-7, with a save percentage of .869 and a goals against average of 3.29. In his next ten appearances, he was 8-1-1 with a .933 save percentage and a 1.84 goals against average. The second number is the Quick we’re used to from playoffs past. Of course, in the ten games *after* that he averaged out again.

Basically, goaltender numbers are a fast moving target around a common mean. Every goaltender’s mean is different, obviously. Quick’s .917 save percentage (playoffs included) is much better than a similarly-aged Kari Lehtonen. Or Cam Ward.

That said, the Kings were probably better off not signing Quick to a ten year deal while Quick was standing at one of the highest peaks of his career. I don’t know what they were looking for, but Quick isn’t as good as the goaltender who had a .946 save percentage in the 2012 playoffs. No goaltender is. They can play that well and have a very good streak, but it’s madness to expect that kind of consistent output from a goaltender every season.

Quick, and the Kings, will be all right.