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Scott Cullen Analytics


Scoring chances vs. Corsi; Pastrnak, Rask, Luongo and more in Scott Cullen’s Statistically Speaking.

Hopefully not to belabour a point too much, but Blue Jackets head coach John Tortorella put the hammer down on modern stats like Corsi and Fenwick recently and, naturally, it drew a reaction.


It’s not the first time Tortorella has ventured down this road, so it comes as no surprise, but it also doesn’t reflect real understanding of the value that can be gleaned from shot metrics. (And all too often I wish that Corsi critiques at least came from a position that showed real understanding.)

For one thing, scoring chances are a subset of shot attempts, so there tends not to be a dramatic difference in performance between the two. Like, the theory of allowing low-quality shots and taking high-quality shots is great, but since that is what every team would like to achieve, it’s just highly unusual to find a team with bad shot differentials that has somehow unearthed the secret to produce really good scoring chance differentials.


Last season, 13 teams were within 1.0%, but there were three teams that had more than a 4.0% difference in (score and venue adjusted) scoring chance percentage and (score and venue adjusted) Corsi For percentage – the two teams that met for the Stanley Cup, the Pittsburgh Penguins and San Jose Sharks and the biggest difference of all, wait for it, the Columbus Blue Jackets.



1 CBJ 48.17 52.96 4.79
2 PIT 52.70 57.13 4.43
3 S.J 51.70 56.13 4.43
4 MIN 48.15 51.41 3.26
5 BUF 47.28 49.41 2.13
6 OTT 46.69 48.66 1.97
7 FLA 49.47 50.52 1.05
8 ARI 46.51 47.18 0.67
9 EDM 48.71 49.35 0.64
10 WPG 50.81 51.31 0.50
11 N.J 46.66 47.15 0.49
12 BOS 50.34 50.69 0.35
13 T.B 51.88 52.16 0.28
14 STL 52.53 52.53 0.00
15 WSH 51.25 51.14 -0.11
16 MTL 50.98 50.60 -0.38
17 NSH 52.26 51.75 -0.51
18 CGY 47.62 47.04 -0.58
19 PHI 49.76 48.89 -0.87
20 TOR 50.56 49.67 -0.89
21 ANA 53.33 52.08 -1.25
22 VAN 46.97 45.35 -1.62
23 COL 44.53 42.89 -1.64
24 NYI 49.62 47.96 -1.66
25 NYR 48.22 46.38 -1.84
26 L.A 56.27 54.21 -2.06
27 DAL 52.43 50.29 -2.14
28 DET 51.45 49.25 -2.20
29 CAR 51.26 48.57 -2.69
30 CHI 51.40 48.22 -3.18

Now, that didn’t really do much for the Blue Jackets – they still finished 27th overall – but it does reveal that there can be some differences between shot attempts and scoring chances.

The dearly departed website War on Ice even had a post about how their scoring chance metric could more accurately predict future goals for players, but it’s refinement, not a massive improvement that renders Corsi invalid, so suggesting that Corsi holds no value doesn’t add up.

The other part of this is that if the Blue Jackets are compiling their own scoring chance numbers, this is where it could become problematic, because when it’s left to the eye test, humans view plays differently and, without rigid definitions, won’t necessarily see eye-to-eye on what constitutes a scoring chance. 


At last year’s PAWS hockey analytics conference in Florida, Panthers assistant coach Mike Kelly talked about how heated debates were between assistants when trying to decide what constituted a scoring chance. Everyone came with a different idea of what counted as a scoring chance.

As I mentioned at the RIT Hockey Analytics Conference this year: 


I don’t doubt that scoring chance information can enhance our understanding of player and team performance. Applying them to come up with an expected goals model could very well help, too, but that’s not quite what this critique sounded like.

Using prescribed scoring chance definitions league-wide helps too because, if nothing else it's consistent, but I don’t think any of it would negate the value of using shot metrics because shot metrics accrue a viable sample size more quickly so that the data has real predictive value. 

Like it or not, the numbers bear it out.

From Monday’s games…


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David Pastrnak is off to a great start in Boston.

David Pastrnak – Boston’s brilliant third-year forward continued his breakout season with a goal and an assist in a 4-0 win against Buffalo. He has five points (4 G, 1 A) in the past four games, and is tied for the league lead with eight goals in 10 games.

He’s not likely to keep shooting 22.2%, but Pastrnak is getting more ice time and generating more shots (3.60 per game) as he skates alongside Patrice Bergeron and Brad Marchand on Boston’s top line, so there’s reason to believe that he will indeed remain productive.

Tuukka Rask – Bouncing back from his worst start of the year, Boston’s netminder turned in a 32-save shutout against Buffalo, raising his save percentage to .941 in eight starts, a solid early recovery from last season’s career-low .915 save percentage.

Roberto Luongo – Florida’s veteran goalie stopped 34 of 35 shots in a 3-1 win vs. Tampa Bay, raising his save percentage to .917 in nine starts. 


Brandon Sutter – The Vancouver centre had a poor possession game (14 for, 21 against, 40.0 CF%, two goals against) in a 4-2 loss at the Islanders, 

William Carrier – Playing in his second career game, the Sabres winger as on the wrong end of the possession game (4 for, 14 against, 22.2 CF%, 0-7 scoring chances) in a 4-0 loss at Boston.


Cal Clutterbuck – The Islanders winger scored the game-winning goal in a 4-2 win over Vancouver, and has recently found himself skating on the Isles’ top line with John Tavares and Josh Bailey

Brock Nelson – The 25-year-old Islanders centre appeared to suffer a knee injury due to a crosscheck from Canucks centre Brandon Sutter.

Valtteri Filppula – Tampa Bay’s veteran centre sat out of a 3-1 loss at Florida due to a lower body injury. 

Tyler Ennis – The Sabres winger, who missed most of last season, has two points (1 G, 1 A) in 12 games this season and played just 7:33 in a 4-0 loss at Boston. Sabres coach Dan Bylsma indicated that the lack of ice time for Ennis was health related.


Islanders G Jaroslav Halak stopped 30 of 32 shots in a 4-2 win against Vancouver, raising his save percentage to .908 in nine games…Panthers D Keith Yandle had rough possession numbers (12 for, 24 against, 33.3 CF%, 2-12 scoring chances), but recorded two assists in a 3-1 win over Tampa Bay which offset those results.


Recently productive players that are still owned in fewer than half of TSN leagues:

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Alexander Wennberg is the setup man in Columbus.

Alexander Wennberg – The Blue Jackets centre is a reluctant shooter, but loves to dish out helpers and is tied for the league lead with 11 in 10 games. Owned: 29.4%

Reilly Smith – Following a slow start, the Panthers winger has points in three straight games. He’s playing big minutes (19:36 per game) and is a critical piece in the depleted Florida lineup. Owned: 33.6%

Travis Zajac – New Jersey’s veteran pivot still logs lots of ice time and has six points (3 G, 3 A) in the past seven games. Owned: 12.1%

Brady Skjei – The Rangers rookie has six assists during a five-game point streak. A rising tide lifts all ships and all that. Owned: 10.3%


Much of the data included comes from and

Scott Cullen can be reached at