The final four teams are set to begin the third round of the Stanley Cup Playoffs this week, so we thought it would be fun to look at the remaining rosters for the Conference Finals to evaluate how they were built.
Player acquisition type
NHL Entry Draft, free agency, trades, and waiver wire acquisitions are all the various ways a team can build a roster. To build a contender, you need to use every tool at your disposal. Let’s look at how these teams built their rosters.
The two-time Stanley Cup Champion Tampa Bay Lightning have the highest percentage of players that were acquired via the NHL Entry Draft. It’s fascinating that Colorado’s percentage of drafted players is so small, especially considering that their cornerstone players – Nathan MacKinnon, Cale Makar, Mikko Rantanen, and Gabriel Landeskog – were all acquired through the draft. The variance among the teams that have a high draft percentage is a little surprising as well, being that the conventional wisdom is that successful teams are built through the draft.
To add some context around the roster composition, we should look at which players are scoring each team’s goals by acquisition type.
The second chart shows that players who are still playing for the teams that drafted them contribute a higher percentage of goals scored in the playoffs compared to the quantity of drafted players still on the roster (shown in the first chart).
This is easily explained as the higher-skilled players tend to score more, and teams are more willing to hold on to their drafted, high-scoring, skilled players (i.e., pay more money to assure they don’t reach free agency).
Note that goal scoring is a rather simple and narrow way of evaluating contributions to a team’s success, but directionally, we think this is a fair indictor on how to evaluate contributions by acquisition type.
Draft rounds
Regardless of the acquisition type, it is also fun to look at how many players each team has from each draft round.
As one would expect, players that were selected in the first round account for the highest percentage of players on the rosters. The surprising piece here was that 25 percent of the Rangers roster consists of undrafted players (Alexandar Georgiev, Barclay Goodrow, Dryden Hunt, Artemi Panarin, Kevin Rooney, and Frank Vatrano).
Roster ages
The average age of a team is also an appealing data point to evaluate.
Tampa is the oldest team in the Conference Finals, which makes sense as they have continued to trade away young prospects and draft picks at the trade deadline over the last three seasons. These moves have left their prospect cupboard rather light.
Edmonton is the second oldest team remaining, though this is being inflated by Mike Smith (40) and Duncan Keith (39).
Looking at average age of the rosters is interesting but can be a little misleading because it lacks things like ice time. Plus, having a few players on the extremes of the age range can influence a team’s average age.
Height and weight of NHL playoff rosters
Finally, we are going to take a quick peek at the height and weight of the four teams in the conference finals.
The heights are very similar with all teams having an average height within less than an inch of each other, but the weight of the players is quite different between the Western Conference teams (COL and EDM) and the Tampa Bay Lightning.
Here is a look at the player detail behind the weight of the players:
In Tampa, Victor Hedman and Patrick Maroon are right around 240 pounds and are undoubtedly influencing the average weight of the team. On the other side of the spectrum, Kailer Yamamoto is listed at 153 pounds and is the lightest player across the four remaining teams.
This was a very simple view at evaluating the Conference Finals rosters, but we hope it gives you a different perspective when watching over the next two weeks. If you found this interesting, you might enjoy looking at this story, breaking down all NHL rosters from last year. If you have questions about the data or some additional angles you would like me to consider, let me know in the comments section.
We have been seeing some eye-popping goal totals in games across the NHL, so we thought it would be a good time to dig into the numbers to investigate if there has been a significant increase in goal scoring across the NHL.
Average goals scored by game
As you can see above, scoring is up to 6.30 goals per game compared to 5.9 last year. There could be several reasons for this increase.
Seattle: Adding a 32nd franchise to the league does dilute the talent across the league, which creates more mistakes and more scoring. It is pretty challenging to show the impact, but we need to acknowledge this could be a factor.
COVID: Last season and a good part of this season were disrupted by COVID. It impacted team schedules, practice days, and personnel decisions, and although players and coaches won’t typically admit it, this had to have taken a toll on teams on the ice.
Youth Movement: There are several pundits covering the league that have suggested that the next generation of goal scorers is leaving its mark on the league. Debunked.
Based on the chart above, there is not a strong connection of youth scoring and the increase on scoring across the league. Players that are 24 or younger only account for 21 percent of the goals scored across the league this year compared to 26 percent of goals last year.
Empty-Net Goals: Over the last 10 seasons, the trend is for coaches to pull goalies earlier and earlier to give themselves a chance to win. This is creating more opportunity for empty-net goals.
…And while we are here, we might as well show this chart of the number of empty-net goals against by team.
Ouch. This should be no surprise to Kraken fans who saw enough empty-net goals against to last a lifetime.
Scoring for and against by NHL team
Here is how scoring breaks down by team and how it has changed from last season.
Florida had the biggest increase in scoring year over year and is currently leading the league in average goals scored per game. If the Dallas Stars make the playoffs, they will have the lowest-scoring team in the postseason, though they are just .01 goals per game behind the Los Angeles Kings in this metric.
Conversely, this is how the scoring sizes up for goals against.
Of the NHL Stanley Cup playoff teams, the Toronto Maple Leafs are allowing the most goals per game in the league, and it will certainly be something to keep an eye on when the playoffs start next week.
Goal differential
Goal scoring is great, but are the games still competitive? No one wants to see blowouts. To get a better idea of the competitiveness of games, we can look at the average margin of victory.
On the surface, the games appear to be getting less competitive. However, when you account for the .06 increase in empty-net goals scored per game year over year, the average margin of victory would be 2.23.
Scoring outlook
Will this trend continue?
Here is one last chart that shows you the distribution of players’ goal scoring by age.
Scoring is up across the league, but it would be a stretch to say that we are entering a new boom of scoring in the league, especially considering the top 10 goal scorers are very familiar faces. Additionally, it would be hard to identify the next generation of players that will backfill guys like Auston Matthews, Leon Draisaitl, and Connor McDavid.
Through the first eleven games of their inaugural season, the Seattle Kraken find themselves at 4-6-1 and at the bottom of the Pacific Division standings. We at Sound Of Hockey are bullish on how they have been playing lately, so we decided to dig into the numbers to identify any trends and validate if our sense of optimism is justified.
Goals scored and goals against
Through the Nov. 5 games, Seattle is tied for 19th in average goals scored per game and 25th in average goals scored against. Those numbers reconcile with their record, but the goals against number is a bit surprising considering most media outlets forecasted the Kraken would be a strong defensive team.
Let us look at these same numbers by game so we can evaluate if the Kraken are trending in the right direction.
Even with Edmonton scoring five goals against the Kraken in game 10, the average goals against has been declining. This is a trend we like to see.
The goals scored is slowly trending in the right direction as well. Up until the game on Thursday against Buffalo, the team was feeling snakebitten after getting Shesterkinned against the Rangers last Sunday and having several near misses against the Oilers on Monday.
Shots taken and shots against
At 29.5 shots per game, the Kraken are 25th in the league, which correlates very well with their goals per game. On the other side, they are averaging the lowest number of shots against in the league which should be considered a very positive sign.
Here are how those numbers project by game.
These trends should give Kraken fans a sense of optimism. Shots for (taken) per game have been on a steady incline while shots against have been on a steady decline. The Kraken have outshot their opponent over the last six games, and if they can maintain that trend, they should start winning more games than they lose.
High-danger and medium-danger shot quality
Of course, it is not always about quantity, as sometimes you need to consider the quality of the shots being taken. To analyze the quality of shots we’re going to look at five-on-five high-danger and medium-danger shot counts by game.
The concept is relatively simple. A high-danger shot has a higher likelihood to go in than medium- or low-danger shots. We’re probably stating the obvious here, but ideally you would have more high-danger shots than medium- or low-danger shots to increase your chances of scoring goals. This data was pulled from NaturalStatTrick.com, a valuable resource if you ever want to know more about the advanced analytics of hockey.
This trend should be considered positive and could be the impact of the “learning to play together” narrative of an expansion team that is compiled of a bunch of players that had limited playing time together before this season.
Wrapping it all up
This is a case where the eye test is aligning to the analytics. We do not like to get pollyannaish about the team’s outlook, but there are some objective signs in the analytics that this team is getting better and is trending in the right direction. It will be interesting to continue to monitor these trends and see if the goals and therefore wins start to follow.
If you have any questions, insights, or feedback, let us know in the comments section.
One of the points of discussion during the Stanley Cup Playoffs is the quality of officiating. We have heard from columnists, coaches, and plenty of fans complaining about the calls going against them this year. This is a common complaint every year.
A few months ago, I published a Data Dump piece on penalties that evaluated how often they were assessed in games and when they were most frequently called during the regular season. For this week’s Data Dump, I wanted to revisit that piece with a focus on comparing regular season penalties called to those called in playoff games.
Penalties called per 60 minutes
I was a surprised to see that the rate of penalties called in playoff games is higher than regular-season games.
But whenever you look at data, it is important to add context to the figures. Like in my previous article, I used the goal differential to provide context to these penalties.
Penalties called where the goal differential is two goals or less seems rather consistent between regular season and playoffs. It is in the blowout game situation (goal differential of three or more) where things seem to get a bit out of hand. If you watch playoff hockey on a regular basis you can formulate why this happens, as teams tend to “send messages” or get frustrated and start committing penalties when the game becomes one-sided.
Penalties called by scenario: leading team vs trailing team
When we looked at the regular season trends a few months ago, there seemed to be some indicators that referees were more likely to call a penalty on teams that were leading a game versus trailing a game.
When we isolate the playoff games, there seems to be less variance between the penalties called on leading versus trailing teams.
The last two playoff seasons appear to have little to no difference in the number penalties called. Before we wrap this up and claim there is no bias in calling penalties if a team is leading versus trailing in the playoffs, let’s add some score differential context.
In the chart above, the difference between penalties called on the leading versus trailing team seems very consistent in the regular season, regardless of the goal differential. Let us look at the playoff games.
In the chart above, the rate at which penalties are called is flipped in games where the goal differential is three or more. The data shows that penalties are more likely called on the trailing team when the goal differential is three or more. As previously stated, the reasons for this are the “message sending” and frustration-type penalties.
Penalties called in the third period
One of the most compelling visuals in the regular season post I did in March was the chart showing penalties called in the third period based on goal differential. Here is the updated visual with the breakdown.
One of the takeaways I see in the chart above is that the leading team seems more likely to be called for a penalty in the last five minutes of a one-goal game than any other time in the game. Now we can look at how this same data looks in the playoffs.
The large discrepancy of penalties in the playoffs in the last five minutes of a one-goal game between the leading and trailing team is no longer present. What jumps out at me in this chart is the spread in the two-goal game. In the first 10 minutes of the third period in a two-goal game, the leading team is much more likely to get a penalty called on them (about 61 percent) compared to the trailing team (about 39 percent).
Conclusions
Directionally, there are some interesting things in this analysis of penalties called in the regular season versus playoff games, but before we draw any hard-and-fast conclusions, here are a few other things to consider:
Because only the top-16 teams qualify for the playoffs, there should be more parity in playoff games compared to regular season games, which could explain some of the variance when comparing the two types of contests.
There is also a much bigger sample size when looking at the regular season versus the playoffs. The higher volume of regular-season games will smooth out any anomalies that could create higher variance with a smaller sample size.
There are always other dimensions that could be added to the analysis to gather more intelligence about the data (i.e., type of penalty, player personnel deployed, etc.).
I hope this gives you a little deeper understanding of penalties called during the Stanley Cup Playoffs as opposed to just believing a coach’s remarks in a post-game press conference or a tweet you might have seen from a prominent journalist.
In my world, nothing beats overtime hockey in the Stanley Cup Playoffs and without a rooting interest in this year’s Playoffs, I can enjoy it without having heart palpitations. This year’s Playoffs kicked off with three straight overtime games and last night the hockey gods treated us with two more overtime games. For this week’s Data Dump Saturday, I am going to look at how this Playoff season is tracking in various categories to previous years.
Overtime games in the Stanley Cup Playoffs
As the chart shows, this year we have seen an above average number of overtime games through the first 22 games with eight. It is important to call out that the NHL categorizes last year’s play-in round as playoff games and for the purposes of this post, they are also categorized as playoff games.
Average goal differential
A playoff season with more overtime games is naturally going to have a lower goal differential compared a to playoff season with less overtime games so the lower goal differential this season should be expected.
Empty net goals in the Stanley Cup Playoffs
Historical goal differential might be a bit misleading considering the trend of pulling the goalie earlier in the third period to get an extra attacker when a team is down. By the down team pulling their goalie earlier provides more opportunity, i.e. time, for the team that’s up to score and thereby increase the differential.
Here is a look at the empty net goals scored in the first 22 games.
This increase of empty net goals will contribute to a higher goal differential that might mislead to show that games are not as close as they really were. Game analytics support pulling goalies earlier leading to overtime games and thereby improving a team’s chances of winning. For more on this I would suggest you check out the great work by Meghan Hall on pulling goalies.
Summary
Between the quantity of overtime games and the smaller goal differential, it appears there is a parity across the teams. The divisional playoff format might explain some of this parity. Traditionally, the best regular season team in the conference plays the lowest qualifying team in the conference, a one seed vs eight seed. The 2021 Stanley Cup Playoff format has the one seed playing the four seed inside the division. Mathematically this will create match ups of teams of closer ability. However, with a regular season schedule that was made up of exclusively divisional opponents, it is difficult to draw any conclusions from this format, but it makes you wonder if we should see this division playoff structure in the future.
For now, let’s just root for more overtimes and hope for some game sevens.
Every NHL Stanley Cup Playoff season I enjoy digging into rosters to see how teams compare across relatively basic demographic information such as nationality, age, and acquisition type. As they say, sharing is caring. (Note: data sources are a combination of capfriendly.com and various statistical reports out of NHL.com.)
Average age across Stanley Cup Playoff rosters
Stanley Cup rosters by nationality
The league is roughly 45% Canadian, but variance across certain teams can be profound. Here is the breakdown of nationality by team.
How the players were acquired
This is a fun view on how these teams were built.
An interesting callout for Vegas is that Nicolas Hague is the first draft pick to make an appearance in the Stanley Cup Playoffs for the Golden Knights. This is his fourth season since being drafted and should be a good example on setting expectations for Seattle Kraken NHL Entry Draft picks in July.
Salary cap by playoff team
Technically there is no such thing as a salary cap in the Stanley Cup Playoffs, but this year playoff salaries are getting a bit more discussion. The defending Stanley Cup Champion Tampa Bay Lightning brought back Nikita Kucherov from long-term injured reserve just in time for the playoffs, pushing the team way over the limit of what would be the cap. But again, there is no salary cap for the playoffs.
I hope this gives you a little more insight into the teams in the Stanley Cup Playoffs this year. If you have questions about the data or some additional angles you would like me to consider, let me know in the comments section.
