At this time of year team records can be deceiving.
Every year some teams get off to fast starts but then collapse, and others start slow but work their way into a playoff position by season’s end.
Last year the Coyotes picked up 34 points in their first 25 games – tied for the seventh-best start in the league – only to end up out of the playoffs with 89 points.
In the other direction, Columbus and Philadelphia started last season with 21 and 24 points, respectively, and worked their way up to 93 and 94 points, and resulting playoff berths.
So what happened?
Teams can go on hot runs while being largely outplayed, but that success is generally not sustainable for a full season. The converse can occur as well.
This isn’t to say a team’s record after 25 games doesn’t matter; far from it. But models that include points and possession measures do significantly better in explaining who made the playoffs and who didn’t.
Specifically, a model with points and Score Adjusted Corsi fits the data much better than models with one variable, and better than any of the models with two variables that were looked at.
For those not familiar with Score Adjusted Corsi, it is a possession metric that reflects the fact teams generally do better in terms of possession when they’re trailing (or worse when they’re ahead) – a phenomenon called “score effects.” Thus, some teams’ possession metrics look better than they really are simply because they play from behind a lot, while others look worse because they have the lead a lot.
From the model using points and Score Adjusted Corsi, we found that on average, each additional point a team has at the 25-game mark increased its chance of making the playoffs by about 7.2 percentage points; each percentage point increase in its Score Adjusted Corsi increased its chance of making the playoffs by 8.1 percentage points.
So what does that mean for this season’s teams? We can generate probabilities for each team of making the postseason this year based on data from past seasons. Keep in mind the model only accounts for 42 percent of the information that one would ideally like to have. For example, it doesn’t account for teams that have above-average shooting or goaltending. Unfortunately, it does not even account for the recent change in playoff format, with divisions and wild cards. However, it does give insight as to who are likely candidates for collapses and who might yet climb the standings.
According to the model, the team most likely to collapse is Calgary, with its chance of making the playoffs being 34.6 percent, even though it had 32 points after 25 games, good for sixth best in the West and third in its division.
In the East, Tampa Bay, Montreal and Detroit were sitting in the divisionally guaranteed playoff positions after 25 games, while Boston, Toronto and Florida were tied with 29 points. Only two of those teams could make the playoffs as a wild card, however, as either the Rangers or the Capitals would get the nod by virtue of being third in the Metropolitan. According to the model, Toronto would be the odds-on favorite to be on the outside looking in (again), while Washington would be favored to get that third divisional spot.
Things almost certainly will change between now and the end of the season – but already there are some indications that all is not as the standings suggest.
Data was taken from puckon.net. For more on the predictive properties of the various statistics, as well as the method used to generate these probabilities, go to depthockeyanalytics.com.