Using Corsi to measure goals for the Rangers

August 26, 2014, by
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.

We can use the work done here to look at the expected goal difference for each player on the Rangers from last season (all numbers at even strength):


Player TOI/60 Corsi% Expected Goal Difference
Marty St. Louis 15.84 0.504 2.95
Derek Steoan 13.68 0.533 8.14
Rick Nash 13.52 0.542 9.75
Mats Zuccarello 13.51 0.540 9.40
Chris Kreider 13.38 0.552 11.54
Carl Hagelin 13.19 0.544 10.11
Derick Brassard 12.72 0.534 3.55
Dominic Moore 9.88 0.485 -2.56


Player TOI/60 Corsi% Expected Goal Difference
Ryan McDonagh 18.48 0.513 3.04
Dan Girardi 18.01 0.501 0.96
Marc Staal 17.53 0.542 8.06
Kevin Klein 15.43 0.466 -3.33
John Moore 13.62 0.517 0.36

First thing to notice here is that based on possession numbers, there were only two players that were expected to finished with a negative goal differential: Kevin Klein and Dominic Moore. Now, that’s not to say that they were ineffective in their roles, because while this is certainly great information, it –at the moment– doesn’t take into account other factors. The article says that zone starts, quality of competition, streak effects, etc. That’s a long-winded way of saying that Corsi on its own isn’t the best way of using these stats.

This isn’t a predictive measure by any means, something the author also states. The value here is using the raw puck possession numbers to evaluate how players performed, while making note of the role they played. For example, Dom Moore is expected to have a negative expected goal differential because the only regular to start more shifts in the defensive zone was Henrik Lundqvist (full zone start information here). You can combine what you see above with the zone starts to see how effective a player was last season.

Categories : Analysis


  1. SalMerc says:

    Is there a way to measure, what I call “finishers”? These are the guys who do the dirty work around the net and have a habit of putting loose pucks into the net. If I were a coach, I would like to put a guy with a high Corsi, but who is low on goals, with a “finisher”, who may not have a ton of attempts, but has a high goal-to-shot ratio. These 2 players would seem to be able to have a high +/- as a pair.

    Also, while I have not looked, do we have Corsi by line? +/- by line?

    • Dave says:

      The first part: There’s a site that tracks shot location by team/player. I don’t have it readily available at the moment, but I can find it for you later tonight.

      I wouldn’t rely solely on raw Corsi, even by line. It’s all about Corsi in relation to usage. Right now, we don’t have one stat that measures it all, but Steven Burtch is putting the final touches on dCorsi, which is supposed to be the next step in this process.

      • SalMerc says:

        These are all interesting stats, but there is still no way to measure heart & guts guys. Guys who muck along the boards may not have good Corsi’s, but do provide a strong role in the offense. There is also a chemistry aspect in hockey that is also there is BB and football. Unsure if there is a way to “measure” how Brady knows where the Bronk will be (for the Pats) or how Zucc knows that Brassard will be in the slot when he throws a blind, backhand pass. Just a 6th sense that comes with chemistry.

  2. DropthePuck says:

    Well lets start with our player with the 2nd best Corsi, Steps. This is a player who misses the net probably more then anyone on the team & shoots from the blueline towards the net “to keep the goalie honest” (or cause a turnover in most case – which is what I call it). What a stat, yeah I would say it needs a little more work.

    • Dave says:

      I think you’re looking at the wrong column. Stepan is 6th best in terms of raw Corsi on the team. You’re looking at even strength ice time I think.

  3. Ray says:

    What this table is doing is translating Corsi into a +/- scale. By and large, the players that one wants to have on the team are those who will have a strong +/- this season. My question is whether these numbers (which are less subject to sample size problems) outperform last year’s +/- as a predictor of the +/- numbers for this year.

    Corsi is a variant of +/- which is less subject to sample size problems and more easily integrated with complementary stats such as zone starts. The question though is whether or not these benefits are more important than things it overlooks, e.g., finishing and defensive lapses. In baseball, last year’s ERA is a better predictor of this year’s W-L record than last year’s W-L record is and so is a better stat even though winning is the most important thing.

  4. frank cerbone says:

    Dave- don’t like the stat & what it implies.

    If Staal has such a high (8.06) number,
    I wonder what Stralman posted compared to Staal as I consider Stralman a much better player.

    Plus, St Louis scored ONE goal during his 18 or 19 games with the Rangers during the regular season last season.

    Taking MDZ, Callahan, & Pouliot off the power play towards the end of the season and playing St Louis, Richards, & Girardi was a terrible decision & killed the power play.