Much has been made about the Leafs not being quite as good as they seem due to their division being categorically weak. But is this categorization fair? Certainly, Toronto has dominated each team in its division this year, and are now seemingly presented with an attainable path to a Stanley Cup semi-final, due to the divisional playoffs. The question everyone seems to be posing now is: aren’t the Leafs going to get demolished in this semi-final? Which is a question that, considering everything I’ve learned about being a Leafs fan, definitely puts the cart before the horse.
Regardless, it’s an interesting question, and one that we can reasonably answer with some numbers, and this post aims to do just that.

# Measuring Opponent Strength

There are two ways to measure strength of opponent that I feel are simple enough to analyze. The first is by goal scoring. Goal differential is one of the most common ways to look at how strong a team is as they head into a Cup run. The second is by shot attempts, or Corsi. We’ve shown in our Advanced Stats Primer that Corsi is a really good predictor of future success.
With both of these, we’re going to calculate how strong each team should have been this year by using data from the 2019-20 season with how much of an effect the personnel changes from last year to this year would have had on the team. The specifics on how I did it are a little out there, but I’ve attempted to explain it at the bottom.

## Goals

Even though shot attempts are a stronger dataset, we’re still going to look at goals because it probably will correlate most with our intuitive estimation of how strong each team is. Goals are easy for us to remember; teams that score a  lot and allow not not so much, we’re likely to remember those teams as being good. And similarly in the reverse.
I’d like to point out that I wrote the paragraph above before I saw the results. Here are the teams in order of lowest strength of schedule (SOS) this year, in terms of goals.
 Team Goals +/- Goals SOS Montreal Canadiens 8.3 -244.3 Toronto Maple Leafs 10.3 -243.6 Vancouver Canucks 4.7 -205.7 Winnipeg Jets -5.1 -123.9 Edmonton Oilers -0.2 -82.2 Calgary Flames -9.1 -67.6 Ottawa Senators -25.9 82.3 Colorado Avalanche 55.8 94.1 Tampa Bay Lightning 51.2 99.4 Boston Bruins 42.6 130.0 Minnesota Wild 34.0 268.2 New York Rangers 24.4 275.1 St Louis Blues 33.0 276.6 Philadelphia Flyers 19.6 314.1 Pittsburgh Penguins 15.7 345.2 Nashville Predators 18.3 362.8 Washington Capitals 10.9 383.7 Columbus Blue Jackets 15.0 389.3 Carolina Hurricanes 13.9 397.7 Florida Panthers 10.8 422.8 Vegas Golden Knights 11.6 447.3 Dallas Stars 4.4 473.8 New York Islanders -2.6 491.2 Arizona Coyotes 4.6 504.0 Chicago Blackhawks -5.8 556.0 Anaheim Ducks -5.5 584.6 Buffalo Sabres -14.5 586.8 Los Angeles Kings -22.4 719.7 New Jersey Devils -37.2 768.2 Detroit Red Wings -44.2 862.8 San Jose Sharks -43.5 888.3
I’d call that a hypothesis proven. As one might expect, teams in the North division seem to have it the easiest, because when it comes to goal scoring, 5 of the 7 teams might have had a negative goal differential this year, as shown by the Goals +/- column, based on their players’ data in 2019-20.
It’s abundantly clear that when it comes to goal differential, the North division is by far the worst. We also might expect that the Leafs would struggle against teams that have high a high goal differential, like the Avalanche and the Lightning.

## Corsi

What happens, though, when we look beyond goals and into on-ice strength? Here are the teams sorted by their strength of schedule (SOS), as per Corsi. By doing so, we’re doing two things: eliminating goaltending and goal scoring from the equation. Instead, we can see how strong teams are in terms of generating shot attempts. We’ve shown many times in the past that this is a more powerful predictor of playoff success than goal differential.
 Team Corsi +/- Corsi SOS Boston Bruins 329.0 -6619.7 Philadelphia Flyers 234.7 -5865.3 Washington Capitals 180.1 -5428.5 Pittsburgh Penguins 102.3 -4806.0 Montreal Canadiens 772.6 -3272.0 Carolina Hurricanes 554.2 -2484.8 Buffalo Sabres -243.3 -2041.1 New Jersey Devils -253.5 -1959.5 New York Rangers -315.5 -1463.7 Tampa Bay Lightning 419.2 -1405.1 New York Islanders -532.4 271.5 Toronto Maple Leafs 411.4 280.9 Edmonton Oilers -144.8 408.9 Nashville Predators 134.1 875.5 Florida Panthers 82.4 1289.4 Dallas Stars -52.5 2368.5 Columbus Blue Jackets -101.2 2758.1 Calgary Flames 40.0 3126.4 Vancouver Canucks 33.8 3188.8 Chicago Blackhawks -222.1 3725.2 Vegas Golden Knights 662.7 4230.5 Colorado Avalanche 378.4 6505.0 Detroit Red Wings -570.5 6512.2 Ottawa Senators -327.1 6927.6 St Louis Blues 306.2 7082.7 Winnipeg Jets -386.2 7157.5 San Jose Sharks 36.7 9238.5 Minnesota Wild 20.3 9370.0 Los Angeles Kings 8.6 9463.6 Anaheim Ducks -82.8 10194.8 Arizona Coyotes -138.5 10640.0
Now, things look a lot different. We can see that by shot attempts, Toronto’s schedule is middle of the pack, and a fair bit more difficult than some of those top from the East and Central divisions like Boston and Tampa Bay.

# What does it mean?

Well, since these are numbers that I cobbled together by myself (huge thank you to www.naturalstattrick.com for the data), probably not much.
However, it does make some kind of point that perhaps the North division isn’t as weak as everyone is saying. When you look at on-ice talent, a team like the Canucks isn’t really that bad, it’s just that their goaltending is terrible. It’s a similar story with the Montreal Canadiens and Calgary Flames. So, while that would inflate the points Toronto can earn against the standings, it wouldn’t inflate the kinds of statistics that we look at here, like Corsi, or the more advanced models.
One such model, the one used by Money Puck, has the Leafs as the most likely team to win the Cup. Now, we know that Toronto probably did better at scoring goals than they might have if they played against all the teams. But we also now know that Toronto had an average schedule in terms of opponents’ shot attempts numbers. That means that these models probably aren’t overrating the Leafs as much as public opinion would suggest.
That’s it for the content of this post, from here on I will just give a description on how I came up with the numbers in the above tables. If you have any questions about any of this, feel free to hit me up on Twitter (@ryandhobart) or comment here.

# The Method

All of the data is from Natural Stat Trick, and is 5-on-5, Score and Venue adjusted.
I started with taking each player’s on-ice goals and shot attempts from the 2019-20 season, and then the same for 2021. For both, I set a cutoff of 300 minutes of ice time.
Then, I overlayed the player, team and ice time they played in 2021 with their on-ice stats for 2019-20. For anyone who didn’t meet the cutoff in 2019-20 but did in 2021, I used their 2021 stats. This made sense, since they’re mostly rookies, and the the 2021 effects on a dozen or so players of a few hundred would have minimal impact, since we’re only using this for team-level analysis.