I simulated the 2021-2022 NHL regular season a million times to estimate what is likely to happen. (I used a computer to help me.) To estimate the probability of the home team winning each game I used my prediction model, Magnus. Curious readers will find lots of detail following that link, but, very briefly:
- I estimate the likely rosters for each team, starting from their contract list on
October 5, 2021, and then weighting by past playing time. Injuries and suspensions are taken
into account. For definiteness:
- All restricted free agents (specifically, Brady Tkachuk) are expected to play a full season for their current teams;
- All PTO players are expected to not play;
- Jonathan Toews, Alex Steen, Oskar Klefbom, Jake Gardiner, Shea Weber, Brandon Dubinsky, Jack Eichel, and Brent Seabrook are expected not to play.
- I estimate the individual impact of each player and head coach on:
- Shot generation and suppression, at even-strength and special teams, taking account of teammates, competition, and the effects of score, zone, coaching, and home-ice deployment;
- Rates of taking and drawing penalties
- Individual tendencies towards shooting or passing; and
- Ability to shoot or stop the puck, as appropriate.
- An adjustment for rest.
- six or seven of the thirty-two teams to finish in the darkest box (very close to their name);
- ten or eleven teams to fall into the adjacent boxes;
- seven or eight to fall into the next pair of boxes;
- four or five into the next pair, and
- two or three teams to fall into the faintest boxes or even beyond.
The method I used is strongly similar to the one I used last year, with some key improvements; some of the explanation is copied from last year's preview.
Team Summaries
Using the isolated abilities of their players and their coach, I can form an estimate of how each team will perform "in a vaccuum", that is, before considering the schedule of games which determined opponents and fatigue. As is my usual habit, positive values mean "more shots" or "more goals" as appropriate, and thus on offence red (more than average) is desirable and on defence blue (fewer than average) is desired. Similarly, positive shooting impact is better for shooters and negative impact is preferable for goaltending; the axis for the goaltending distributions is flipped so that "better" appears to the right for both shooting and goaltending.
| Pacific | Central | Metropolitan | Atlantic |
|---|---|---|---|
ANA
Breakdowns:
EV
ST
Finishing
|
ARI
Breakdowns:
EV
ST
Finishing
|
CAR
Breakdowns:
EV
ST
Finishing
|
BOS
Breakdowns:
EV
ST
Finishing
|
CGY
Breakdowns:
EV
ST
Finishing
|
CHI
Breakdowns:
EV
ST
Finishing
|
CBJ
Breakdowns:
EV
ST
Finishing
|
BUF
Breakdowns:
EV
ST
Finishing
|
EDM
Breakdowns:
EV
ST
Finishing
|
COL
Breakdowns:
EV
ST
Finishing
|
N.J
Breakdowns:
EV
ST
Finishing
|
DET
Breakdowns:
EV
ST
Finishing
|
L.A
Breakdowns:
EV
ST
Finishing
|
DAL
Breakdowns:
EV
ST
Finishing
|
NYI
Breakdowns:
EV
ST
Finishing
|
FLA
Breakdowns:
EV
ST
Finishing
|
S.J
Breakdowns:
EV
ST
Finishing
|
MIN
Breakdowns:
EV
ST
Finishing
|
NYR
Breakdowns:
EV
ST
Finishing
|
MTL
Breakdowns:
EV
ST
Finishing
|
SEA
Breakdowns:
EV
ST
Finishing
|
NSH
Breakdowns:
EV
ST
Finishing
|
PHI
Breakdowns:
EV
ST
Finishing
|
OTT
Breakdowns:
EV
ST
Finishing
|
VAN
Breakdowns:
EV
ST
Finishing
|
STL
Breakdowns:
EV
ST
Finishing
|
PIT
Breakdowns:
EV
ST
Finishing
|
T.B
Breakdowns:
EV
ST
Finishing
|
VGK
Breakdowns:
EV
ST
Finishing
|
WPG
Breakdowns:
EV
ST
Finishing
|
WSH
Breakdowns:
EV
ST
Finishing
|
TOR
Breakdowns:
EV
ST
Finishing
|
Stat Breakdowns
Using the above, I can make some summary graphics for the league as a whole.
Even Strength Shot Rates
The most basic result in the sport is the shot. To win a team will shoot often and from dangerous locations and with some measure of finishing skill. First, we look at even-strength shot rates, taking into account the shot's type and location. This gives an idea of "total offence" or "total defence", before we consider finishing talent and goaltending talent. I call this estimate expected goals, or xG for short. The zero point is set to what we saw in 2020-2021, just over 2.4 goals per hour of 5v5 play. If the league opens up, it's possible for this year's average to be above zero (or below zero if the league becomes more defensive). The "NHL" button indicates the average of the team rosters as constructed currently. Before taking any possible injuries into account, I expect the league will be slightly tighter than last season.
The better offensive teams are further to the right, the stronger defensive teams are near the top. The best two-way teams (at five-on-five) are in the top corner, as is typical the best teams fall on a sliding scale between primarily defensive (Minnesota, Boston) through to primarily offensive (Vegas, Edmonton). More unusually, Chicago are woefully bad at both ends of the ice at 5v5, alone in the league.
Special Teams Shot Rates
The same measurement above, but for special teams: power-play offence on the x-axis, and penalty-kill defence on the y-axis. Power-play defence and penalty-kill offence are not considered here.
This season (unlike last season) most of the extreme values are strengths—the Oilers, Rangers, Maple Leafs, and Avalanche (under Toronto) are all likely to have very strong chance generation on the power-play. The Sabres power-play, bereft of its primary driver in Jack Eichel, should be very weak.
The overall distribution of talent in power-play ability is much larger than the distribution of penalty-kills. The difference between best and worst power-plays is around 2.4 goals per 5v4 hour; the difference between best and worst penalty-kills just over 1.0 goals per 4v5 hour.
Penalties
Expected penalty differentials for teams are computed from expected icetimes for each player, multiplied by individual tendencies to cause their team to take or draw penalties, not merely individual rates. Among other things the Avalanche's strong penalty-drawing ability meshes well with their very strong power-play chance generation; while Columbus should draw very few penalties and convert very few of those opportunities.
Shooting and Saving
In addition to the shot volume and quality, some shooters are better at converting chances than others, and, even more obviously, some goaltenders are better than others at preventing those chances from becoming goals.
In per-shot terms, the range of goaltender impacts on goal odds is only slightly wider than the range of shooter impacts, but a team's shots are generated by a much broader range of players than the range of goaltenders who will try to stop the shots which that team allows. This produces the sharp difference in the range of team-level goaltending, being six or seven times broader than the range in team-level finishing talent.
The values I use for goaltender and shooter ability are not as easily interpretable as the previous measurements, but they can still be understood with odds ratios; for instance, the odds of a shot taken against a Philadelphia or Buffalo goaltender becoming a goal are 6% higher than a similar shot taken against a league-average goaltender. In Winnipeg, the high value is primarily due to Connor Hellebuyck (the best goaltender in the league) unlike in most of the other strong teams, where both goalies in the expected tandem are very strong.
Fatigue
All of the above is taken entirely from the team's roster and coach, without regard to the schedule. Of course, not every team has the same schedule, which affects how well they are likely to perform. Not all teams are equally affected by fatigue. The strongest effects from rest are seen when teams play after playing the night before. The table below shows how many times each team plays 'tired' in this sense, as well as how many times they play against a team that is tired. Games played between teams which are both tired in this sense are not counted, since neither team has a rest advantage.
This season the Canadiens have the most-favourable rest schedule, with a net-seven games more playing at rest advantage versus rest disadvantage. The nearby Senators have the least-favourable rest schedule, playing at rest disadvantage nine more times than at rest advantage.
Points and Playoff Chances
The most important factor of the schedule, though, is not rest but the fact that teams do not all play against the same opposition. To measure the effect of this imbalance, only simulation will suffice, the results of which are presented below.
Each team's bar is centred on the average point total obtained in the simulations for each team, sorted with the highest averages to the right, with the divisions indicated by colour. The changing colour intensities indicate "stanines", that is, each coloured square shows half of one standard deviation.
Thus, we expect:
Pacific
| Team | Mean points | Standard Deviation |
|---|---|---|
| Golden Knights | 98.1 | 8.4 |
| Flames | 93.2 | 8.4 |
| Kraken | 92.1 | 8.5 |
| Oilers | 91.5 | 8.5 |
| Kings | 90.7 | 8.5 |
| Canucks | 89.0 | 8.5 |
| Sharks | 87.2 | 8.5 |
| Ducks | 87.0 | 8.5 |
| Team | Playoff Chance |
|---|---|
| Golden Knights | 81% |
| Flames | 61% |
| Kraken | 56% |
| Oilers | 53% |
| Kings | 49% |
| Canucks | 42% |
| Sharks | 34% |
| Ducks | 32% |
The freshly-minted Seattle Kraken have every chance to show well in a weak Pacific division with only one very strong team, the Vegas Golden Knights. Stylistically I expect the Kraken will be more similar to the Flames (very strong defensively but with trouble scoring) than the Oilers (no trouble scoring but with serious defensive issues). I expect that Los Angeles will give fairly serious minutes to some young players; if those players are as good as Kings' fans hope, they might well overperform their prediction here.
Every team's most likely finishing position is marked in the Position Chances graph. Vegas are most likely to finish first in the division (the marked 35%) but have a smallish (∼20%) possibility of missing the playoffs altogether. Amusingly, three different teams are each more likely to finish last in the division than in any other place.
Playoff cutoff: 90.9 points
Central
| Team | Mean points | Standard Deviation |
|---|---|---|
| Avalanche | 100.3 | 8.3 |
| Predators | 93.9 | 8.5 |
| Wild | 93.6 | 8.5 |
| Jets | 91.7 | 8.5 |
| Stars | 88.6 | 8.5 |
| Blues | 86.8 | 8.5 |
| Coyotes | 86.3 | 8.5 |
| Chicago | 82.7 | 8.5 |
| Team | Playoff Chance |
|---|---|
| Avalanche | 88% |
| Predators | 65% |
| Wild | 64% |
| Jets | 55% |
| Stars | 40% |
| Blues | 32% |
| Coyotes | 30% |
| Chicago | 17% |
Colorado remain the class of the division by some distance, the most complete team in the league without any weaknesses to speak of. Chicago, by contrast, have an excellent goaltender coming off a Vézina-calibre season, and little else: a head coach with a dreadful defensive system, a weak defence corps with some freshly-overpaid personnel and an aging core of forwards who rely almost entirely on finishing ability without any volume generators to speak of. The six teams in-between are more muddled. Some, like Winnipeg, rely on goaltending and finishing to cover defensive weaknesses; others, like Minnesota, rely on their extraordinary defensive strength to cover weaknesses in offence generation.
Playoff cutoff: 90.7 points.
Metropolitan
| Team | Mean points | Standard Deviation |
|---|---|---|
| Islanders | 95.9 | 8.4 |
| Penguins | 95.0 | 8.4 |
| Hurricanes | 91.9 | 8.5 |
| Capitals | 90.1 | 8.5 |
| Rangers | 89.8 | 8.5 |
| Devils | 88.1 | 8.5 |
| Blue Jackets | 82.7 | 8.5 |
| Flyers | 79.5 | 8.5 |
| Team | Playoff Chance |
|---|---|
| Islanders | 77% |
| Penguins | 73% |
| Hurricanes | 60% |
| Capitals | 51% |
| Rangers | 50% |
| Devils | 42% |
| Blue Jackets | 20% |
| Flyers | 11% |
The metropolitan division is the only one without a particularly strong team at the top, which should make the contest for top seed especially interesting. The Flyers re-worked their defence corps over the summer without any obvious net improvement and even a hefty "bounce-back" for Carter Hart, their presumptive starter, still leaves him well below average given how dire he was last season. The Rangers (on their way up) and the Capitals (on their way down) meet in the middle.
Playoff cutoff: 89.9 points.
Atlantic
| Team | Mean points | Standard Deviation |
|---|---|---|
| Leafs | 104.0 | 8.3 |
| Lightning | 98.0 | 8.4 |
| Panthers | 94.6 | 8.4 |
| Bruins | 92.2 | 8.4 |
| Canadiens | 88.4 | 8.5 |
| Senators | 87.3 | 8.5 |
| Wings | 83.5 | 8.5 |
| Sabres | 79.1 | 8.5 |
| Team | Playoff Chance |
|---|---|
| Leafs | 95% |
| Lightning | 83% |
| Panthers | 70% |
| Bruins | 60% |
| Canadiens | 42% |
| Senators | 36% |
| Wings | 21% |
| Sabres | 10% |
The atlantic is the most stratified division, with both the strongest and weakest team in the league. Toronto's perennial post-season disappointments have swelled in the popular imagination to obscure the fundamentals of an extremely strong all-around team, with an improved goaltending tandem over last year without any matching weakenings in other aspects. Buffalo, meanwhile, lost some of their only good players in the off-season and seem destined this season to play without their best player, Jack Eichel, stripped of his captaincy amidst an increasingly rancorous dispute about how to remediate his neck injury. Montreal, who massively overperformed in a felicitous run to the cup final last season, are very unlikely to repeat such a performance.
Playoff cutoff: 90.2 points.
Wooden Spoon
Since the league still hasn't yet implemented Gold drafting (which guarantees a full slate of exciting games for fans of all teams, win or lose, while eliminating tanking and giving the best picks to the worst teams), many teams will once again play many games at the end of the year which would be in their best interests to lose. Although there will be many trades and confusions between now and the end of the year, these are the early probabilities (including all three lotteries) for who will get the 2022 first overall draft pick.
| Team(s) | Chance of First overall pick |
|---|---|
| BUF | 9.0% |
| PHI | 8.7% |
| CHI | 6.6% |
| CBJ | 6.6% |
| DET | 6.1% |
| MTL | 5.5% |
| ARI | 4.9% |
| STL | 4.3% |
| ANA | 4.2% |
| S.J | 4.0% |
| OTT | 4.0% |
| N.J | 3.5% |
| DAL | 3.4% |
| VAN | 3.2% |
| NYR | 2.8% |
| WSH | 2.7% |
| L.A | 2.5% |
| EDM | 2.2% |
| WPG | 2.1% |
| SEA | 2.0% |
| BOS | 2.0% |
| CGY | 1.7% |
| MIN | 1.6% |
| NSH | 1.5% |
| FLA | 1.3% |
| PIT | 1.2% |
| NYI | 1.0% |
| VGK | 0.7% |
| T.B | 0.6% |
| TOR | 0.1% |
| CAR | 0.0% |
| COL | 0.0% |
The Colorado chance is zero because their first-round pick for this draft was traded to Arizona as part of the Darcy Kuemper deal, the Coyotes' chance is higher than it would otherwise be for this reason. Carolina does not have a first round pick this draft, having given it to Montreal as part of the Kotkaniemi offer-sheet compensation. It is possible that the Coyotes will have another first-round pick this season, from the Dvorak trade, but the conditions on that trade make this unlikely to affect Arizona's probability (or Montreal's) very much.