2016-17 Midseason Rainbow Charts

As the title says, these are the midseason “Rainbow Charts” I released on twitter back in mid-January. Yes, I am putting them up on the blog just now, mid-February. I’ve been busy, yo.

Anyway, much like the original rainbow charts, these charts compare players against the results of their peers who have similar TOI. So a second pairing defender is being compared against the historical average of all second pairing defenders, not against his teammates.

By using standard deviations, the idea is to provide some context around usage, as often we get hung up on decimal places. Especially when looking at relative zone starts, the deviations are quite large, so it takes a lot to move a player outside of the “average” zone (the middle square).

Weighted Corsi is a combination of CF60, CA60 and Relative CF% standard deviations, weighted.

Click “Read More” to get to the charts. Ctrl+F will get you directly to your team if you don’t want to scroll through everything.

Read More »

2015-16 Rainbow Chart Masterpost (M-W)

Ok guys, get ready for an absolute crap-ton of charts coming your way. This isn’t an explainer, merely just a data dump.

The best way to find your team is to hit Ctrl+F and use the team name. Otherwise, everyone’s in alphabetical order.

Feel free to save and use. Consider this blanket permission to use in blogs or other posts as long as it links back to here or my twitter, @Classlicity.

Click this link for Part 1: A-L 

Read More »

2015-16 Rainbow Chart Masterpost (A-L)

Ok guys, get ready for an absolute crap-ton of charts coming your way. This isn’t an explainer, merely just a data dump.

The best way to find your team is to hit Ctrl+F and use the team name. Otherwise, everyone’s in alphabetical order.

Feel free to save and use. Consider this blanket permission to use in blogs or other posts as long as it links back to here or my twitter, @Classlicity.

Click here to go to Part 2: M-W

Read More »

3.10.16 Rolling Average Charts

Under the cut you’ll find all the Rolling average charts I tweeted this weekend. They include all games up through 3/10/16.

These show a teams’ 5v5 score adjusted Scoring Chances For per 60 (SCF/60), Scoring Chances Against per 60 (SCA/60) and PDO as a 10 game rolling average for the 2015-16 season. They’re expressed as standard deviations from the NHL Average. Basically that means very little, other than the fact that positive is good, and negative is bad.

They also include a rolling average of the win/loss record of each team. In these averages, I’ve devalued OT and Shootout wins, as these are far more unpredictable (read as: up to chance) than regulation wins.

The intent of these charts are to show the biggest influences on winning, and why one metric never tells the whole story. (Heck, they don’t even include special teams play!)

Anyway, they’re alphabetical by city, so if you’re interested in one team in particular use Ctrl+F to find them. They’re all watermarked, so feel free to take and share. A tag back to here, or my twitter @Classlicity would be much appreciated.

Read More »

Individual Offensive Contribution Graphs (Through 11/16)

If you follow me on twitter, you’ve probably seen a lot of charts about offense over the last few days. All of these graphs represent a player’s individual offensive contribution to their teams based on two stats.

First, is Individual Corsi For per 60 (iCF/60). This basically tallies all the shots on target, missed shots, and blocked shots a player has taken up until I pulled the data, and then turned it into a rate stat.

The second is Personal Shooting %, often just called Shooting %, which is the number of goals a player has, divided by the number of shots on goal they’ve taken.

The first chart (I’ll use Dallas as an example) shows just this year’s numbers.

11.15 Indiv Offense Contrib - iCF

As you can see, Roussel’s Sh% is really high and likely to come down, especially because his iCF/60 is lower than average. On the other hand, Sharp, Seguin & Spezza have Sh% within a normal range, and have really high iCF/60, so they could probably continue that pace.

Graph two is slightly different.

11.16 - DAL - Change iOffContrib

This shows how the player is doing vs their results over the last 5 years. I’ve excluded rookies because, well, they don’t have any data from the last 5 years. Here we can see Hemsky smack dab at average, indicating he’s doing exactly what he’s always done. Roussel is actually shooting less than he normally does, and both Spezza and Val are shooting a lot more. Klingberg’s shooting % is extremely deflated compared to his normal 5v5 number, which is a scary thought for the rest of the Central Division.

The most important thing to remember is that these graphs only tell you about offense. If you have a player who is sound defensively, but doesn’t take a lot of shots, they won’t look good on these charts.

Under the jump, I have all the teams in alphabetical order by abbreviation.

Read More »

11.10.15 Stars vs Maple Leafs Game Recap (The Albatross Game)

Why is it, that of ANY TEAM in the Eastern Conference, the one that beats us with regularity are the Toronto Maple Leafs. They swept our series with them last year, they swept us again this year, and you know what, I’m gonna tempt fate and say they’ll probably sweep us next year, too.

For what it’s worth, though, the Stars didn’t have a bad game. They buckled down, got some goals, and they literally had bad bounces going the other way.

No bling today, as it wasn’t earned. Dallas still leads the Western Conference, but it’s only by 1 point. Seguin is still tied for first in points, and Jamie is in a three-way tie for first in goals.

11.11 goals

Per usual, all numbers are from war-on-ice.com, are 5v5 and score adjusted, unless otherwise mentioned.

The Good

11.10 v TOR Game Chart

The Stars were out possessed in the first, but came back in the second, and really split time in the third.

  • Side Note: Faksa again impressed me. When Moen (who??) and Eaves come back, do they really want to send him back to Cedar Park?
  • Side Note 2: Jordie and Jokipakka got slaughtered by the Leafs. Like, they could not hold onto a puck to save their lives last night. JJ lost literally every match up, while Jordie only put up positive numbers against Spaling and Grabner. I wonder if we’ll see Nemeth & Oleksiak against the Jets on Thursday. After all, Lindy may want to add some size to the lineup against them anyway, given their hard-hitting history.

This goal by Vern Fiddler is a thing of fucking beauty. Watch it over and over and let it heal your soul.

Jason Demers is having himself a season. He got the assist on both Stars goals last night (primary ones at that) and deservedly so. He plays like he’s 6’5” and 240 and goes fearlessly digging for pucks, which is how the Sharp goal tied the game. Four for you, Demers.

The Más o Menos

Niemi wasn’t spectacular? I really don’t know how to judge this. Two out of three goals took deflections off our own players, and we’re pretty used to three goals against, but also it could’ve gone the other way if he’d just been a TAD sharper.

  • Side Note: It was mentioned that they’ve gone “off plan” with respect to the goaltending. I think you’ll see Lehtonen on Thursday.

We only took one penalty 🙂 They scored on the power play 😦

The Bad

TWO OUT OF THREE GOALS TOOK DEFLECTIONS OFF OUR OWN PLAYERS. The first, of course, went in off of Jordie Benn’s skate, because life was going TOO WELL for him. The second (and the game winner) deflected off Sceviour’s stick as he tried to block the shot lane.

  • Side Note: My conclusion here is that defense is useless.

For some reason, we just…didn’t…shoot the puck yesterday. No, I know we had 38 shots total, but honestly this is the least amount of scoring chances our top guys have had in a while.

  • Side Note: Look, I have a chart to prove it.

11.11 iSC60 for top 4 fwd

  • Side Note 2: You know how guys talk about “needing to get to the net”? It’s kind of cliché, but it’s also super-true. Sharp’s goal came from that exact kind of play, but look at this. That red outline is right around the net. We had like, NO SHOTS there. Instead, most of our shots came from the left side of the ice (incidentally, Goligoski led the team in SOG with 5). Toronto, on the other hand, got right up in our goalie’s grill to get some good rebound action.

11.10 shot locations

Goals on Goals


And another look at that Fiddler goal because sometimes we deserve nice things.


When 2 Become 1: The Dallas Starhawks

With the blockbuster Patrick Sharp trade, and the recent signing of Johnny Oduya, the jokes are pouring in about the new Blackhawks South. Jim Nill has mentioned several times that they’re the organization to mimic, so I wanted to take a look and see – just how alike are the two teams?

Obviously, I don’t have any data with the Sharp & Oduya playing in their new uniforms, but by looking at this past season, we can get a reasonable look at how close these two teams really are.

First, here are the With or Without You charts via @IneffectiveMath. If you want to focus on the individual numbers, go ahead, though I’ll be going through offense and defense separately. What strikes me on a macro level, is just how much more tight the grouping is for the Blackhawks than the Stars, especially defensively (y-axis).

Chicago WOWY 1415Read More »

Relative Fenwick per Salary Band Over Time Masterpost (Defense)

Just yesterday I published a set of charts showing scoring chances relative over time for the forwards, and now I have a similar set for defenders. These charts show Fenwick For % Relative to a player’s team, but show the change over time per salary band.

Why Fenwick? Well, by removing blocked shots from the analysis, we can get a better idea of how good the defender is at shot suppression. If they’re blocking shots (as shown by Corsi) then they’re letting the opposing team get into a shooting lane with the puck, and that’s less than ideal.

The most important thing to know when reading these charts is that a higher Fenwick For % Relative is better, just like a higher Scoring Chance For % Relative is better for forwards. And if your team isn’t positive, you’ll want them to at least be higher than the league average.

Here are the NHL Averages:

All NHL FF Rel Over Time - DRead More »

Relative Scoring Chances per Salary Band Over Time Masterpost (Forwards)

And here’s another Salary Band post, comparing Relative Scoring Chances For % over time. Some teams have trends, some you can see have guys from ELCs move into big contracts, etc. Despite the emergence of analytics over the last few years, there hasn’t been much of a change in GM behavior from 2006 to now.

Here is the NHL Average chart:

All NHL SCF Rel Over Time - F
Read More »