Atlantic Division Analysis
Last updated on May 09, 2022.
Division Standings
Currently, the Florida Panthers are first in the Atlantic division with 122 points. The Toronto Maple Leafs, Tampa Bay Lightning and Boston Bruins round out the top four spots. The Montreal Canadiens sit last in the division with 55 points.
| Atlantic Division Standings | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| 21/22 NHL Season | |||||||||
| Team | GP | W | L | OTL | PTS | PTS% | GF | GA | Diff |
| Florida Panthers | 82 | 58 | 18 | 6 | 122 | .744 | 337 | 242 | 95 |
| Toronto Maple Leafs | 82 | 54 | 21 | 7 | 115 | .701 | 312 | 252 | 60 |
| Tampa Bay Lightning | 82 | 51 | 23 | 8 | 110 | .671 | 285 | 228 | 57 |
| Boston Bruins | 82 | 51 | 26 | 5 | 107 | .652 | 253 | 218 | 35 |
| Buffalo Sabres | 82 | 32 | 39 | 11 | 75 | .457 | 229 | 287 | -58 |
| Detroit Red Wings | 82 | 32 | 40 | 10 | 74 | .451 | 227 | 310 | -83 |
| Ottawa Senators | 82 | 33 | 42 | 7 | 73 | .445 | 224 | 264 | -40 |
| Montreal Canadiens | 82 | 22 | 49 | 11 | 55 | .335 | 218 | 317 | -99 |
| Source: National Hockey League | |||||||||
Scoring
Goals Per 60 Minutes
The chart below depicts players on each team by goals per 60 minutes of play. The players on each team within the league wide top decile are highlighted to demonstrate the quantity of high-end offsenive playmakers.
The Florida Panthers have 5 players in the top decile in the league in scoring.
The Tampa Bay Lightning and Toronto Maple Leafs each have 4 players in the top decile.
Players Per Scoring Quintile
The chart below shows the number of players on each team within a given quintile of goals per 60 minutes. Players with less than 20 games are excluded.
Florida has a plethora of high end scoring, with 14 players between the 60th and 100th percentile.
Toronto possess alot of high-end scorers, with 7 players in the fifth quintile. They have less secondary scoring with 3 players in the fourth quintile.
Montreal lacks high-end scoring talent, with only one player in the fifth quintile.
Fenwick For Percentage Vs High Danger Shots Per Game
The next chart uses some more advanced metrics to measure offensive ability. On the x-axis, teams are plotted by their Fenwick For percentage (FF%), which measures the percent of total unblocked shot attempts by a team in the average game. Therefore, a FF% above 50% indicates that team had more unblocked shot attempts than their opponent. On the y-axis, the adjusted expected goals (AXG) measures the expected goals an average team would have scored, adjusting for successive rebounds, score metrics and whether the team is home or away. Essentially, a higher value indicates more and better scoring opportunities. For more information on this metric, visit Money Puck.
Teams that lie along the line of best fit are normal in terms of the distribution of low, medium and high quality shots. Teams that lie above the line tend to take more medium to high danger shots relative to their total shots, while teams that lie below the line tend to take more low to medium danger shots.
Florida takes alot more shots than it gives up, and alot of them are dangerous. Florida ranks first in FF% and first in high danger shots per game, league-wide.
Boston has a relatively high FF% but just above the league average in AXG, indicating it does not produce as many high danger shots. Boston ranks second in shots per game, but twelfth in high danger shots per game, league-wide.
Detroit is just under the league average in AXG, despite a lower FF%. They rank ninth in high danger shots per game, despite ranking twenty-eighth in FF%.
Special Teams
Penalty Kill
Rather than using the typical penalty kill percent, we will look at the “Penalty Kill Yield” (PKY). See Bleach Report’s article on this metric. This metric is calculated as follows:
PKY = (Power Play Goals Against - Short Handed Goals For) / Games Played
It accounts for team discipline in refraining from penalties, as well as accounting for shorthanded goals for, rather than just powerplay goals scored against. For reference, the league wide average PKY is 0.473.
The Toronto Maple Leafs lead the Atlantic in this category and are sixth league wide.
The Montreal Canadiens have the worst PKY in the Atlantic and are thirty-second league wide.
Power Play
We can look at the power play with a similar metric, Power Play Yield (PPY), calculated as follows:
PPY = (Power Play Goals For - Goals Against with Man Advantage) / Games Played
This metric works in a similar way, accounting for a teams ability to draw penalties and goals scored against while on the man advantage. For reference, the league wide average PPY is 0.473.
The Toronto Maple Leafs lead the Atlantic in this category and are fourth league wide.
The Montreal Canadiens have the worst PKY in Atlantic and are thirtieth league wide.
Goaltending
Lets look at advanced goalie statistics. Goalies who have played less than the median games played by NHL goalies this year (20 games) have been removed from the analysis. To mitigate clustering of data labels, only the goalie with the most games played on a given team are given data labels.
The chart below shows box plots for goals saved above average (xGSAA) in 5-on-5 situations. The calculation for this metric is simple - each shot attempt is assigned a numerical value based on its likelihood of being a goal. Goals saved above average is the difference between what the average goalie would’ve allowed based on these shot likelihoods, and what the reference goalie actually allowed. For more on this metric and other advanced goalie metrics, visit the Hockey Writers.
Andrei Vasilevskiy leads the Atlantic with an xGSAA of 18.74, good for second league wide.
Sergei Bobrovsky is second in the Atlantic with an xGSAA of 14.15, good for eighth league wide.
Rebounds above average per unblocked shot attempt (RAX) can give us an idea of each goalies’ puck control. This figure provides insight to a goalies puck control and is calculated as follows:
RAX = (Rebounds - Expected Rebounds)/Unblocked Shot Attempts
Thomas Greiss leads the Atlantic with an RAX of -0.008 and is third league wide.
Interestingly, Sergei Bobrosvky ranks very poorly in this category, at sixtieth league wide.
To see more goalie stats league wide, use the table below. Apply the filters to get the desired statistics, rankings or players.