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Photo Credit: Gary A. Vasquez / USA Today Sports

The case for firing Glen Gulutzan, Part 2: Process vs. results

When offered the opportunity to write an article for FlamesNation, I told Ari that the research may take me down a rabbit hole or two before it was all over. This is one of the rabbit holes I found myself buried in.

(Here is Part 1.)

Why using results and goal differential is how a team should be evaluated

An early Google search produced an article written by Rob Found from Edmonton, and posted online at The Sports Journal, “Goal-based Metrics Better Than Shot-based Metrics at Predicting Hockey Success.” It is a statistical evaluation of 10 years of NHL data to compare goal-based versus shot-based metrics to see what methods are best at determining team success in the NHL. It was written in 2016.

Here is a summary: 14 hockey statistical models were used in the study, 10 based on shots (Corsi) and four based on goals. Some of the models used a single statistic (i.e. shots for), while others were “composite” in that the model used two or more combined statistics (i.e. goal differential).

Based on his research, Found concluded that goal-based models outperform shot-based models in predicting team success, both in terms of team results and individual contributions to a team’s success, and that defence-based models are better than offence-based models (goals allowed is superior to goals for and shots allowed is superior to shots for). As for individual contributions to team success, only forward contributions were statistically significant, and only when using goal-based models. Contributions by defenceman were not statistically significant using goal- or shot-based models. 

I took the statistics from the 2016-17 season and applied them to the standings. While a simple evaluation in comparison to the research done for the article, the results are very good at showing how effective certain stats are at predicting where a team will finish in the standings.

2016-17 NHL standings relationship to shot- and goal-based statistics (data from Natural Stat Trick)

Standings Team In Playoffs Points CF% CF% Rank Shot Differential SD Rank Goal Differential GD Rank PDO PDO Rank
1 Capitals Yes 118 51.66 6th +213 4th +84 1st 1.027 1st
2 Penguins Yes 111 49.80 16th +80 9th +49 4th 1.015 5th
3 Blackhawks Yes 109 49.89 15th -66 22nd +28 7th 1.013 6th
4 Blue Jackets Yes 108 49.57 18th +52 12th +54 3rd 1.020 2nd
5 Wild Yes 106 49.79 17th +63 11th +57 2nd 1.020 3rd
6 Ducks Yes 105 49.57 19th -4 18th +23 9th 1.010 7th
7 Canadiens Yes 103 51.36 8th +31 15th +25 8th 1.009 9th
8 Oilers Yes 103 50.44 11th +131 7th +36 6th 1.010 8th
9 Rangers Yes 102 49.06 21st -27 19th +37 5th 1.016 4th
10 Blues Yes 99 49.50 20th +4 16th +17 13th 1.007 11th
11 Sharks Yes 99 51.38 7th +187 5th +19 11th 1.001 15th
12 Senators Yes 98 48.56 24th -3 17th -4 19th 0.998 18th
13 Bruins Yes 95 54.48 2nd +524 1st +23 10th 0.990 21st
14 Maple Leafs Yes 95 50.11 14th -56 21st +16 14th 1.008 10th
15 Flames Yes 94 50.39 12th +33 14th +3 16th 1.000 17th
16 Predators Yes 94 51.10 9th +85 8th +18 12th 1.004 14th
17 Islanders 94 47.53 27th -136 24th +1 17th 1.005 12th
18 Lightning 94 51.05 10th -38 20th +6 15th 1.004 13th
19 Flyers 88 52.15 4th +251 3rd -19 22nd 0.983 27th
20 Jets 87 48.96 22nd -100 23rd -9 20th 1.000 16th
21 Hurricanes 87 52.29 3rd +173 6th -18 21st 0.986 25th
22 Kings 86 54.77 1st +434 2nd -2 18th 0.983 28th
23 Panthers 81 51.69 5th +48 13th -26 23rd 0.989 22nd
24 Stars 79 50.34 13th +64 10th -38 25th 0.982 29th
25 Red Wings 79 48.52 25th -175 25th -46 26th 0.988 23rd
26 Sabres 78 47.19 28th -324 28th -32 24th 0.998 19th
27 Devils 70 47.07 29th -294 26th -61 27th 0.985 26th
28 Coyotes 70 44.93 30th -516 30th -67 29th 0.991 20th
29 Canucks 69 48.17 26th -335 29th -63 28th 0.986 24th
30 Avalanche 48 48.65 23rd -299 27th -111 30th 0.966 30th
Playoff Prediction Success 60.00% 66.67% 93.33% 80.00%
Average Error in Predicting Standings 8.4 7.13 1.8 3.53

The results speak for themselves. Corsi is horrible at predicting team success. Shot differential is better, but still ineffective. On the other hand, goal differential correctly predicted whether a team was in or out of the playoffs for 28 of 30 teams. PDO was also very effective. If you believe the Corsi proponents, this would suggest that playoff appearances are nothing more than luck.

But what is most impressive is that both PDO and goal differential determined who the top nine teams were, although not necessarily in exact finishing order. Goal differential also predicted the worst eight teams, although not perfectly in order.

In the case of PDO, Found’s evaluation determined that PDO did not even out over 10 years of NHL data, as proponents say it will. He accounted this to some teams taking better shots when compared to other teams, teams allowing better shots than others, and teams having better goaltending than others. PDO is not luck.

On the subject of goaltending, Found pointed out that of the 40 teams to reach the Stanley Cup finals in the 20 years prior to his study, 28 teams had a goalie that received Vezina Trophy votes in the season they appeared in the final, while the other 12 had goaltenders good enough to earn Vezina votes in other seasons. In Smith we trust.

Corsi was so far from being accurate, that four of the top five CF% teams missed the playoffs, and ranked Boston as second despite finishing 13th in the standings. Boston was only one point from missing the playoffs: hardly an endorsement for Corsi being a good tool.

Found best evaluated the results of his findings as such: “There are meaningless shots, but no meaningless goals…”

My point in going down this rabbit hole? Shot-based statistics and goal-based statistics are tools to measure how the “process” is working in achieving team success. But at the end of the day, results come down to wins, losses, and overtime and shootout losses. In other words it comes down to points, and more specifically, points in relation to the teams in the division, and conference.

Increasing shots for and decreasing shots against – controlling possession – is the “process” the Calgary Flames have chosen to use to improve team success. We cannot confuse “results” with “process.”

The Gulutzan Flames: Results and significant statistics

In the NHL, just under 12% of all regular season games go into overtime. Based on this, the average points per team is just under 92. Setting the bar correctly, that means that evaluating teams by the correct standard is to relate everything to 92 points, not 82 and a .500 record.

The 2016-17 Flames finished the season with 94 points, 12 games over .500, but only two games over the average. The 2017-18 Flames are on pace for 97 points, five games over average. The good news: they are better than average.

The playoffs are played and won at 5v5 and on special teams. Relying on 3v3 overtime is not a good strategy, but it has become the norm for Calgary this year. The Flames have been to overtime 17 times this season, second most in the NHL behind Arizona, and in 30% of all games played. They are truly playing for a tie.

In terms of regulation wins and losses in the regular season, the Flames were 32-33 last season. They were the only team to make the playoffs that was below .500 in that category; no other playoff team was fewer than six games over .500. Two Eastern teams missed the playoffs despite being above .500 in regulation.

This season, the Flames are 20-19 in regulation wins and losses, 16th in the NHL. The Gulutzan Era Flames are just above .500 in regulation, and when you include the playoffs, they are three games below .500.

This season, in terms of regulation wins, the Flames have 20, tied for 18th. Vancouver and Chicago are only one win back at 19. They are 11th in regulation wins in the Western Conference.

Even the worst team in the NHL last season, Colorado, is 24-21, three games over .500 and four regulation wins better.

Setting expectations: Roster upgrades

The Flames were upgraded in the summer. On defense, replacing Dennis Wideman and Deryk Engelland with Travis Hamonic and a re-signed Michael Stone made the defensive core one of the strongest on paper. Up front, the core remained intact, with a few minor changes to the bottom six.

The biggest improvement has been the goaltending. Mike Smith was the biggest question entering the season, but he has done better than anyone could have hoped. The backup question has also been answered: although it took some time to figure things out, David Rittich has save and goals against numbers that are better than Smith’s.

There is little argument that Smith has been an upgrade over Brian Elliott and Chad Johnson. As for the rest of the roster, you may disagree that there have been improvements. What we think does not matter: Brad Treliving believes the roster has been upgraded, so much so he leveraged the future to bring in players he believes can take this team to a better finish in the regular season, and on a playoff run in the spring.

Setting expectations: Points

Last season, the Flames finished 45-30-5 for 94 points. They came out of the gate very slow then as they adjusted to Gulutzan’s system. Roughly one-quarter of the season in, they were 8-12-1, and were beginning to show signs of improvement. From that point on, the team ran up a 37-21-3 record, 77 points in 61 games, a 0.631 win percentage. Once the kinks were ironed out, this is the level of play last year’s team was capable of. It translates into a 104-point season.

There is no excuse for a slow start this year; of the core, only Hamonic is new to the system. With the offseason moves, 94 points would be a step backwards. At the very least, this year’s team should be capable of matching the level of play they achieved last season, or 104 points.

Setting expectations: Pacific Division standings

If you look at the division, most of the other teams are in a period of decline or rebuild mode. Whether it has been making cap room by moving out players, teams starting the season with key players on injured reserve, or aging players on the decline, only the Flames made significant upgrades. For the most part, things are playing out very close to what should have been expected.

2016-17

Rank

Team 2016-17 Points Projected

2017-18

1 Anaheim 105 94
2 Edmonton 103 75
3 San Jose 99 100
4 Calgary 94 97
5 Los Angeles 86 97
6 Arizona 70 56
7 Vancouver 69 73

Only Los Angeles has shown significant improvement of those in the hunt for a playoff spot. A new coach and improved play following a disappointing season does make this a predictable result. It should not be enough to catch this edition of the Flames.

If we have set the expectations correctly at 104 points, and a 100-point season is what even Gulutzan predicted was possible, then the Flames should be leading the division. To be third of the perceived contenders, and in a dogfight for their playoff lives, is disappointing. A 97-point pace is a step backwards.

And then there was Vegas. That they are in the conversation at all for a playoff spot is the biggest surprise of the year; to be leading the Western Conference is just insane. It has also put a playoff spot in jeopardy for the Flames.

Vegas is on pace for 113 points, a testament to what is possible with solid coaching. At worst, the Flames should be in second, on pace for 104 points and home ice advantage in the first round of the playoffs. But that was last years team’s potential. Improvements were made. This team should be battling with Vegas for first in the Pacific.

The team is underperforming. Next week, I will look at what is causing the team to be sitting below expectations.



    • cjc

      Unfortunately, it’s circular reasoning – predicting the results of one season from the goal differential, obviously there will be a better correlation because goals decide games. So there is no “predictive” value there. Predictions are about the future. The 2014-2015 season saw the Flames with terrible Corsi, but a +25 goal differential (due to a combo of high shooting % and better than avg. goaltending). Everyone knew it would all come crashing down at some point, and it did in 2015-2016 when the Flames missed the playoffs by a country mile and a -27 goal differential. It was the same coach, mostly the same players.

      Another component that Corsi doesn’t really deal with is special teams play. Special teams play is generally less important than ES play, because the vast majority of a game is played at ES. For most teams Special Teams are a push – effecting goal differential a few points either way – but for some it does make a big difference.

      Corsi proponents don’t believe that playoff opportunities are just luck – what they do say is that bad teams can make it and good ones can miss because of luck. But generally Corsi is a much better predictor of future success – Skylardog’s analysis is not predictive, it is retrospective. Here is an admittedly back of the envelope analysis of how well goal differential and Corsi in 2016-2017 explain points % in 2017-2018 (so far) – getting my #s from Natural Stattrick, 5v5 only for the reasons above.

      16-17 CF% vs. 17-18 Points%: Pearson correlation = 0.59
      16-17 Goal Differential vs. 17-18 Points%: Pearson correlation = 0.24

      Last season’s shot based metrics do a WAY better job of predicting what teams are successful this year, and I suspect that pattern holds across years. There is more to the game than 5v5 play, and I think Gulutzan is at least partially responsible for the horrid powerplay. But the analysis used to discredit him here is circular.

      LA is probably the worst example – last year they were very good process wise, but the pucks just didn’t go in. It’s widely acknowledged that LA’s play has suffered this year, they may be getting more goals but they are a borderline playoff team once again.

  • Cup hope

    Thanks for the excellent analysis Skylardog. I have been following several team nation sites and flamesnation seems far superior in quality of discussion.

  • canadian1967

    But, But, But…. Corsiiiiii…iiiii…??? sniffle sniffle whine whine…

    “There are meaningless shots, but no meaningless goals…” This is what “some” of us have been saying all along.

  • Hockeyfan

    it’s settled then, corsi is nerd fluff for nerds who have never played, just as i’ve always said. out of the park homer Skydog, you write better and re smarter than 80% of the nerds i see try to write about hockey.

  • BendingCorners

    I like the PDO comment. A team can have luck-driven PDO in the short of medium term but over multiple seasons it truly does reflect skill.
    Nice job Sky.

    • Mickey O

      Gerard Gallant might not even know what Corsi is. He just rolls 4 lines, they all forecheck like demons, and he doesn’t even bother matching lines most of the time. The team plays their guts out for the guy, because they respect him.

  • The Doctor

    I think this expectation of perfectly linear upward point progression to be a bit unrealistic. I still think we’re a better team than last year, even if it hasn’t (yet) shown up in our point totals. I’d much rather head into a first round playoff series with this group than last year’s group.

    We have pieces that we didn’t have last year — better goaltending, way better bottom defence pairing, Hamonic, Jankowski. Plus a number of our existing guys are better with another year under their belt, notably Matty T, Gaudreau and Monahan.

    It wouldn’t surprise me if we finished strong, given all that, though injuries are always the great unknown.

    I’m as peeved as anyone when we don’t play as well as we could or should, but while I agree with some of SD’s specific criticisms, I don’t see the doom and gloom scenario he’s painting.

      • The Doctor

        I agree that with the best coach out there — maybe Babcock — we’d probably be better. But that’s what historians call a counterfactual — and it’s utterly incapable of being definitively proven or disproven. We don’t have an alternative reality machine that can demonstrate the hypothesis. Mike Babcock is not available.

        The situation will probably take care of itself. If we make the playoffs and do ok, then there’s no reason to gripe. If we miss the playoffs then he deserves to get fired. If we do the same thing as last year (make the playoffs and crap out in 4 games), then that’s the hockey version of the movie Groundhog Day and that would be a bit creepy.

      • muffmin

        That’s what everyone here is overlooking. We have a ‘solid’ group. Gully is gonna get us to the playoffs, maybe win a round or two but I don’t think we’re legit contenders with the current group. My bigger gripe is with Treliving trading away the package he did for Hamonic (even though I love the guy).

        • The Doctor

          I think we’re a couple of pieces away from being a true powerhouse team. The things misssing IMO are a third line scoring right winger and one or two pieces for a fourth line that can score. I think next year we could well have all of those pieces in place.

  • Derzie

    Finally!! Someone has put together a well executed explanation of what I have been wanting to but do not have the ability to say: there is a pecking order with stats and it flows in logical order. A win is better than a goal. A goal is better than a scoring chance. A scoring chance is better than a shot. How many times do I see corsi & shot based metrics being held up as trump cards when the simple logic of “a goal is better than a shot” is ignored.
    Awesome. Top article of the past year for me. Great work.

  • Mickey O

    Skylardog…your first two articles are as well researched and pulled together than I’ve seen on many a site, not just hockey. They must have taken hours to research and write. Kudos to you man, this is top-notch stuff.

  • The GREAT WW

    “Based on his research, Found concluded that goal-based models outperform shot-based models in predicting team success” so teams that score more goals than the opposition have a greater chance of winning?
    This is groundbreaking stuff!!!!!
    We should build our team around this model: all we have to do is construct a team that scores more goals than the opposition and we will win games!….simple yet genius!

    WW

  • Cheeky

    One thing I believe we can all agree on is we want a team that can make the playoffs and go deep. As said, playoffs are won and lost 5 vs 5 and specialty teams and this includes OT. We are good 5 vs 5 but having bad specialty teams (cough PP cough) and relying heavily on 3 vs 3 OT points won’t take us far…

  • Guest

    Just a couple of comments here (and I hope they don’t come off as negative) regarding measurements…

    The finding that goal differential is the most strongly correlated “statistic” to win/loss record is not remotely surprising. This is true in every sport – the more games, the stronger the correlation. There are many variants of Pythagorean expectation and they work great. This is because you have to score more goals that you allow to win. So duh, goal differential is a better predictor of winning.

    Corsi and other stats are there to describe what helps drive scoring more goals and giving up less goals. A baseball equivalent would be on base percentage. Run differential predicts wins better but it doesn’t help you decide what players help get a better run differential.

    Corsi and its variants have a strong correlation to goal differential expectation and hence can be a tool that helps team predict what players and systems can help drive a better goal differential and hence more wins and less losses. An example of a stat that has not correlation to better goal differential is # of hits/60 or #of blocked shots/60.

    This article, while well written, doesn’t explain why or how goal differential can be better except saying the coach is bad – i.e. the data does little to test the thesis (which admittedly is hard to test).

    Anyways, judging by the comments it seems people are confused by a fact – goal differential (or any point differential in any sport) is strongly correlated to win – does not at all means Corsi has no value or that the coach is necessarily bad or good. It could mean that but this data has little meaning in that regard.

    The PDO part is more interesting however…

    • IUsedToHaveAName

      Shot location, I think, is the most important part of predicting a players ability to score goals. By eye, it looks like the closer to the net you get, in addition to the magic spaceship scoring areas (the entire slot as well as both points), the easier it is to score, hence the high/med/low danger scoring chance metric for goaltenders.

      I think I would start by looking at a heat map of shot locations throughout a season and compare it to their corsi. Hockeyviz does a pretty good job of this on a game by game basis, so if we took these heat maps and put them over an entire season we can see who is scoring the most goals from these high percentage locations, compare that to the player’s corsi and combined, we should be able to reasonably ascertain a player’s value relative to their corsi rating and then potentially extend that to cover and hopefully predict a team’s success. I’ve been out of following analytics for a while but I suspect that this is was xGF/eGA is all about.

      The easy thing about on base percentage in baseball is that everyone knows where first base is. We know a player is good if he gets there, but in hockey, such a fluid game, first base is a far less defined area spread throughout the offensive zone and not every high danger scoring area is going to be first base at any given time.

      Essentially, this was a long winded way of explaining that I agree with you on the article’s dismissal of corsi as a whole and also agree that there is some worthwhile information to be gained from examining and then differentiating between “good” corsi and “bad” corsi.

      My feeling is that if we measure goals from forwards relatively close to the net and measure assists from defensemen from the points or high slot area we’ll get a much more accurate measure of player value than just raw corsi alone.

      • Mickey O

        Baseball is also a stop and start game. Somebody throws the ball, and somebody tries to hit it. I can see analytics being of much greater value in baseball, for one thing it is easier to calculate.

        But for a completely fluid and dynamic game like hockey, I doubt that the analytics crew will ever get a real hold on the game, or even figure out what they are trying to measure and extrapolate.

    • Greg

      I need to read the source research article, but it seems like correlation is being confused with predictive ability. I’m not defending Corsi here (it seems to have lost some predictive ability overtime, I suspect teams have found better strategies since Dallas “throw everything at the net” Eakins).

      But goal differential having the strongest correlation to wins at the end of a season seems obvious. You won more, ergo you scored more, ergo you have a better goal differential. That’s just the end result.

      Does it predict who will succeed going forward though? It seems like it would be better to look at goal differential at, say game 41, and how well that predicted the final standings at game 82. Or how each well each game could be predicted by looking at the team’s current goal differential.

      The big value of data is helping make decisions. Corsi and PDO helped identify teams that were having unsustainable success, individuals who were worth more than their counting stats indicated, etc. I’m not sure goal differential gives you anymore insight than the win loss column does.

  • RKD

    Gully was hired last minute because they didn’t have a coach, he’s missed the playoffs twice in Dallas. Even though Hartley was a more seasoned both of their player usage is mind boggling. Hartley would bench Backlund while Gulutzan would put Brouwer on the 1st unit pp or put him on the ice to take a faceoff. He also has some weird loyalty to Bartkoswski who keeps popping back into the lineup even though he’s a massive liability. GG never seems to take timeouts to calm his troops down. He has issues line matching. The reality is GG is still learning as a coach, we don’t need one who is still learning how to coach.

  • BlueMoonNigel

    Hell, the Flames chased the larger-than-life, legendary, angelic Bob Johnson out of town because he apparently couldn’t motivate Al MacInnis, Joey Mullen and Dougie Risebrough and their mates against the one-wing Jets in the ’87 playoffs.

    Despite Badger being lauded throughout Canada and the US for his being able to motivate and develop players and teams, he wasn’t good enough to keep his job in Calgary. Why?

    While Calgary has been a magnet for bad coaches–remember Gibby?–maybe the org makes good coaches bad. Maybe the org grinds good men down to useless stumps just as marriage does to a lot of fine blokes.

    If Badger and Gibby represent opposite ends of the coaching competence spectrum, then the Flames have truly had it all.

    Would Gerry Gallant as coach of the Flames have them higher in the standings? Maybe, but what would happen if he took them to first in the Pacific and they were out in the first round? “The idiot Gallant was badly outcoached!” “Fire the bum!” “Hire a real coach!” These are a sampling of what I would hear after a brilliant Flames’ regular season followed by a speedy playoff exit.

    In conclusion, no conclusion. It’s a crock.

  • Peachy

    So data analysis. Corsi to goals to wins. If you want to explain who won the game last night, goals will do that better. In fact, they’ll do it perfectly: the team who scored the most goals won. That’s not a very interesting finding, but that’s the analysis you conducted.

    But what if you want to know who will win tomorrow? Goal differential falls apart in small samples due to the influence of variance, luck, randomness, PDO, whatever you want to call it. Corsi, Fenwick, expected goals, etc are all superior predictors.

    But nothing is deterministic, and luck can persist throughout an entire season – see Hartley, Bob.

    TL;DR it’s easy to “explain” results via goal based metrics, but they don’t “predict” future performance well.

  • Off the wall

    Absolutely loved this Skylardog!
    I read the report and found it fascinating, yet still curious as to why certain metrics are more revealing than others.

    If it’s true that defence have very little to do with this model (goal differential) in predicting future success, then it shows there is more evidence needed to draw conclusions on all metrics alone.

    I think you can’t rely on stand alone metrics(Corsi), but in inclusion what best describes winning vs losing games.
    Maybe I’m being simplistic, however I believe if a player is between offensive dots and the slot, his chances of goals increases substantially. It’s about shots, but also where those shots are taken.

    In his analysis, Found said something that made the point clear to me:
    “When comparing approaches to evaluating team success, and individual contributions to that success, it is important to recognize that no single metric exists in isolation. Goals can only come from shots, shots can only come from possession of the puck, and possession is an inevitable result of winning faceoffs, getting powerplays, forcing turnovers, and so on. This explains why all our tested metrics were actually significant predictors of team success, and our models simply identified which were the best of this demonstrably good bunch.”

    I appreciate all the work you put into this, and I agree with your conclusions that we should be mired in the Pacific lead, not Corsi’ reliant on postseason hockey. GG may or may not get us there. However, is that what we’re settling for?

  • deantheraven

    Admiration and gratitude, Dog. Your work is a revelation!
    The ‘play for a tie’ might be on the players, too, in that they can play outside systems and responsibilities and possession dogma. I bet many of our top players believe they have the best chance to win at 3v3, when they’re not bound to the system GG has them play. And they’re right, unfortunately.

  • deantheraven

    Thanks, Skylar. Finally, a capable somebody has proved that ‘fancy stats’ aren’t as predictive as many here think. But people who know more than me have insisted that stats, graphs and charts prove the value of corsi, corsi rel, HDCF etc… Ilike the pretty colours, but I still have no idea what constitutes a “scoring chance for” to whoever it is that comes up with corsi events for/against, but it’s always funny to me to see shots for and shots against totals being so far outta whack with CF & CA. To me, every SOG is a Scoring Chance, and anyone who attempts to put a value on the quality of each chance is chasing a fool’s errand. How many times have I seen a huge gap between shots for and “chances for” (+ or -). Subjectivity is the flaw in these models. If I flip one at the goalie from centre and he bobbles it, it’s a goal even if you say it’s not a scoring chance.
    I’ve said it before and I’ll say it again: Corsi, Schmorsi. GF, GA, Gdiff trump CF et al.
    Thanks muchly, sir. Good dog!

    • muffmin

      A scoring chance is just a shot from the “home plate” area in front of the net. Basically from the slot. If you google it there’s even a wikipedia article on it. Also Goals for and against are a better predictor of how a team has performed in the past. If they’re getting caved in possession wise it suggests that they are over performing and might regress. It’s what happened to the Flames in 15-16 after the playoff season and the same thing is happening to the Sens this year. It can also happen in the opposite direction where teams under achieve. For example Boston barely making playoffs last year and being a top team this year. Of course at the end of the day goals are all that matters but advanced stats are a way of figuring out why certain teams score more goals. These type of stats are in their infancy but completely ignoring them is silly and taking them as gospel is also silly. They’re just a tool to try and understand the game better.