NHL

What's Different With the Toronto Maple Leafs This Year? by Manav Jain

By Liam Kindred

If there's one thing to know about being a Maple Leafs fan, it's to never get your hopes up about a regular season. Over the last few years, fans have seen the iconic franchise break their franchise records for regular-season wins and points yet continuously come up short in the opening round of the playoffs.

The Leafs entered this season coming off a 7-game loss to the rival Canadiens, seeing Auston Matthews and Mitch Marner combine for just one goal while completely shut down by Phillip Danault and company.

A deeper dive into the 2021-22 Leafs shows a far more balanced team than in recent years. Production from the bottom six forward group, a stout defensive core, and a stunning first-half from Jack Campbell in his first season as a starter signals something very dangerous to Leaf fans everywhere: Hope.

As Jake Muzzin returns from injury (he will take the place of Travis Dermott or Timothy Liljegren depending on the night), the differences in the Leafs Game 7 lineup outside of the return of John Tavares are not in the form of big names, yet have still been highly effective. The minor offseason acquisitions of Kyle Dubas have performed well above expectations- the most notable of these signings being Michael Bunting, a player that had only played in 26 NHL games before this season and was selected to play for Team Canada at the 20-21 IIHF World Championships.

Credit: John Blacker, Canadian Press

Seen below, Goals Against Replacement measures player performance based on total goals added to the team relative to a replacement-level player. GAR compresses value based on even-strength offense and defense, powerplay offense, penalty drawing, penalty taking, and faceoff. Using regression techniques, value is calculated and summarized for each player- for example, shot generation and scoring are used as drivers for even-strength offense.

The stat can give an idea- albeit a rough one- of the total value generated by a player. In this case, bars look at actual numbers versus expected numbers based on these factors, with blue indicating positive and red indicating negative results. xGAR, or expected goals above replacement, aims to calculate the number of goals a player would expect to get based on their opportunities.

Source: Evolve Hockey

Seen as a Zach Hyman replacement with early reports before the season listing Bunting as an x-factor for this offense and a potential 20-goal scorer, the first-liner has been a welcome surprise for the Leafs on a sub-$1M deal compared to Hyman’s $5.5M AAV in Edmonton. The 26-year-old rookie has 33 points through 48 games, tied for the league lead in penalties drawn at 27 while on pace and is on pace for a 56 point season (25 Goals, 31 Assists).

While a slightly differing xGAR total does indicate a potential slight cooldown on Bunting’s high point total based on shooting percentages, it cannot be denied that he has been an incredible add for the Leafs. Refreshingly, an extra year for Bunting on his discount deal makes it hard to miss Hyman, especially with the complete game and edge he brings night in, night out.

What makes this such a welcome addition? In the last two series that saw losses to Montreal and Columbus, the team relied way too heavily on the ‘big four’ to generate offence. Not to excuse the fact that the team should have won both of these series, however the lack of depth scoring made it a lot easier for teams to set their line matchups.

This problem existed throughout each of the prior two seasons and continued into the playoffs, with this year’s team looking much more positive in this aspect. Bunting has not been the only welcome surprise for the Leafs. Ilya Mikheyev and Ondrej Kase are on pace to finish this season right around the 20-goal mark and Jason Spezza is set to close out around 30 points, these three guys will have an important impact come playoff time.

Power-Play Prowess

Credit: Billy Hurst, AP Images

It was around this point of last season when the powerplay went ice cold only managing to score 6 goals on 76 attempts (7.8%) in the last 30 games. Starting the season newly-promoted Assistant Coach Spencer Carbery took over for Manny Malhotra in running the powerplay to incredible results.

Carbery’s new system is topping the NHL through the first 48 games of the season converting 31.6% of their opportunities. Incredibly, this number is 4.7% higher than the second-highest St. Louis Blues. The difference between the Leafs and second-place Blues is less than the distance between St. Louis and the 10th-place Colorado Avalanche (23.7%), an incredible feat for the Leafs.

The main difference between this season’s power play and the end of last season is its lack of predictability, with PP1 players constantly rotating through different positions. Take a look at this series of tweets showcasing the Leafs powerplay lines, via David Alter on Twitter.

Source: David Alter, @dalter, Twitter

This setup has been consistent over the past few weeks, with Marner and Matthews rotating between the different flanks while Nylander and Tavares rotate the bumper position in the center of the umbrella. You will also notice that cross-seam pass is a lot less common this year making this year's powerplay much more of a dynamic threat as opposed to past years.

Matthews (20) and Nylander (18) are leading the team in power-play points with Marner (12) looking like much more of a scoring threat in this system. After not scoring a power-play goal since the 19-20 season, he has four since returning from his injury and has been on a heater with 20 points in his last 10 games.

The key part of it all is Auston Matthews- who’s on pace for the first 50-goal season of his career after a COVID-shortened season had him fall just short last year. Overall, the powerplay has been producing consistently and the offensive talent it contains will give them a clear advantage over any team that they play in the playoffs.

Player Spotlight

Source: Kirby Lee, USA Today Sports

One of the most important pieces of the offense throughout this point in the season has been Alex Kerfoot. He has been quietly having one of his best seasons in the NHL, getting top-six minutes consistently playing alongside Tavares and Nylander. This opportunity has allowed him offensive freedom which has translated into a big increase in point production. As seen, Kerfoot is a darling of the GAR stat, adding 19 goals this season compared to a replacement-level player.

Source: Evolve Hockey

In his two most recent seasons with the Leafs, Kerfoot was used as a depth forward, often playing in a shutdown role. When UFA David Kampf was acquired last offseason, the bottom six instantly became much stronger defensively which was a big factor in Kerfoot’s ability to move up the lineup. Kerfoot currently has 33 points with 30 of them at even strength which is on par with Patrick Kane and Evgeny Kuznetsov. He will have an underrated effect on the team in the playoffs as his ability to generate offense for the second line will help take the pressure off the high-powered Matthews line.

Since his standoff with Kyle Dubas to sign a contract back in December of 2018, it always seemed that William Nylander to regain approval from the majority of Leaf's fans. After a disappointing second-half to that 2018-19 season, last season he proved that he’s worth every bit of his deal with the Leafs. He was by far the best forward in the seven-game series in the Habs, totaling 8 points on 5 goals and 3 assists. With Tavares, Matthews and Marner all missing games throughout this season, Nylander has consistently been one of the most reliable forwards to generate offensive chances.

Source: Evolve Hockey

Nylander’s point totals sit at 45 points through 46 games while serving as a key element of the aforementioned powerplay, totalling the second-most power-play points on the team (6 goals, 14 assists). Nylander will be a very important piece of this offence down the stretch and makes his line a legitimate goal-scoring threat every time they are on the ice.

Similar to Alex Kerfoot, Morgan Rielly has been having one of his best years as a Leaf- on pace for 71 points, one shy of his career-high from the 2018-19 season. He’s a player that has been through a lot with the organization, experiencing the full rebuild and most recently signing a lengthy extension that will see him at Scotiabank Arena for the next seven years.

Source: Evolve Hockey

The Leafs defensive situation has been through a lot through the first half of the season- losing players to injury and COVID protocols on a regular basis. The overall lack of defensive depth in the organization has led Sheldon Keefe to rely heavily on veterans such as TJ Brodie, Rielly and Muzzin.

Rielly is seeing career highs in ice time and has been averaging upwards of 24 minutes a night. If rumours of GM Kyle Dubas shopping around for a depth defenseman are sound, some pressure may be taken off Rielly during the playoffs. The addition of TJ Brodie has allowed him a lot more freedom to take chances offensively- which puts him in the top 96th percentile of the league for offensive production.

Looking Ahead

Source: Claus Andersen, Getty Images

With the trade deadline around the corner and the Leafs in a buying position, there are a few of areas that could use some strengthening to make them a harder team to play against come April. Kyle Dubas has already come out and said that the team has the potential to be aggressive at the deadline to address their weak spots.

A lack of defensive depth by way of the many injuries the team has experienced is a part of this. When healthy, this defense core can be relied upon to close out games and win playoff series’ more so now than in the last three-to-four years. However, as we have seen with the most recent injury to Jake Muzzin, losing one key player put lots of additional strain on the top pairing which would not be sustainable throughout multiple playoff series.

Entering a playoff series having two of the three, Dermott, Liljergren or Holl would be less than ideal- even though they have been adequate up to this point in the year. Potential liability for two-to-three mistakes each night could be costly in a playoff setting where the margin for error becomes far smaller.

This Leafs team has the most potential to make a run in the playoffs than any other team in the era of Auston Matthews, however, given the strength of the Atlantic Division, finishing out of the top spot all but guarantees a tough first-round series.

Credit: Perry Nelson, USA Today

Everything seems to be working at the moment with the powerplay toping the NHL, balanced point production across all four lines, and solid defensive play. The x-factor heading down the stretch will be the goaltending tandem of Campbell and Petr Mrazek and whether or not they will be able to play well when it matters most.

The strengthening of the defense core is certain to go a long way as well, helping limit a barrage of shots on goal the Leafs have struggled with in the playoffs since Frederik Andersen minded the net against the Bruins. Campbell has already proved what he's capable of, among a handful of the league’s best in both save percentage and GAA. The netminder has earned the trust towards the idea that, with the offensive production he has been getting and a much-improved D-core, he can lead the Leafs on a run in the playoffs.

With this in mind, the importance of coming first in the Atlantic Division is more important for the Leafs this season than any of the last four. Drawing a wild-card team opponent allows them a chance to build up some momentum before facing powerhouses in the Tampa Bay Lightning and Florida Panthers. While the Leafs can certainly go toe-to-toe with these two teams, seeing either one later rather than earlier is far more ideal.

As mentioned, it will be the second line that will be the most important down the stretch and into the playoffs. Both wingers, Kerfoot and Nylander, on that line, are having career years with Tavares in between them providing offensive support. Every year seems like we get closer and closer to a series win and fall short in the series decider. If the Leafs can’t finally complete the task this year, it’d be hard-pressed to find formula that gets them there.

Data from Evolve-Hockey, Capfriendly, and Spotrac

Featured Image: John E. Sokolowski-USA TODAY Sports

Fixing the Toronto Maple Leafs by Guest User

After another disastrous postseason effort from the Leafs, we take a look at some of the moves GM Kyle Dubas should be looking at in a summer with all eyes on him. Known as an GM who takes pride in analytics, we try to match Dubas and the Leafs with difference-makers for the 2021-22 season.

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QSAO’s Insights around the NHL: Offseason Edition – How two of the NHL's busiest franchises look ahead of the 2020-21 Season by Guest User

As we progress further into the offseason, the NHL landscape begins to settle. With so much uncertainty regarding various aspects of the game we once knew so well, teams need contingency plans to avoid taking a step back next season. Teams like the New York Islanders & Tampa Bay Lightning are already looking at cap overages with outstanding RFA contracts to sign, while franchises like the Colorado Avalanche boast an exemplary cap structure, allowing them to not only keep their contending roster intact but also add a few more high-value pieces to their lineup. In the second instalment of QSAO’s Insights Around the NHL: Offseason Edition, Constantine Maragos breaks down why the Colorado Avalanche are this offseason’s big winners and how the New Jersey Devils can best utilize their roster space.

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QSAO’s Insights around the NHL: Offseason Edition – How the Montreal Canadiens & Vancouver Canucks have fared thus far by Guest User

If there is one thing we learned this year, it’s that things can change on a dime. Through the NHL Draft and Free Agency, we have seen rebuilds kickstarted, rosters reimagined, and of course, the ever-lasting goaltender carousel continues. With so many question marks heading into the season, NHL front offices have (mostly) done their best to prepare their teams for the upcoming 2021 NHL season, whenever that may be. With this much movement, we are looking at an all-new NHL. So, after a short break, QSAO’s Insights Around the NHL has returned for an offseason redux. In the first of two offseason editions, we look at how the Montreal Canadiens and Vancouver Canucks’ busy offseasons have gone so far.

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Analysis: How five elite scorers get their goals by Guest User

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By Owen Kewell

There’s something beautiful about scoring a goal.

Goals are the building blocks that make up hockey success, both on the individual and team level. They are a single moment in time, a culmination of a series of plays that ends with one team’s attack successfully defeating the other’s defense.

Teams are forever searching to add goals to their lineup, and for good reason. Goals win games, playoff series and, eventually, championships.

Goal-scoring is a repeatable talent, and while certain NHLers are far better at it than others, each player does it their own way. Each scorer exhibits unique tendencies of shot type selection and shot location.

Alex Ovechkin, Evgeni Malkin, Connor McDavid, Nikita Kucherov, and Patrik Laine are five of the best scorers in the game. Of the 10 goal leaders for the 2017-18 season, these five players possess the highest career goals per game rates. They are the elite of the elite when it comes to putting the puck into NHL nets.

I wanted to explore how they each do it differently.

Elite Scorers 1.jpg

The above visualization separates by shot type to show how each player scored their goals in the 2017-18 season. Overall, the most popular shot type was wrist shot, followed by snap shot, slap shot, and finally backhand.

It should be noted that the ‘AVG (10+ G Forwards)’ represents a weighted average of the relevant shot rate among all forwards who scored 10 or more goals, weighted by the number of goals that they scored. It’s a way to quantify ‘normal’ rates for the league’s goal scoring forwards.

Let’s take a more detailed look at each of these five players.

Alex Ovechkin

Elite Scorers 3.jpg

It’s no secret that Alex Ovechkin is really good at scoring goals. Since breaking into the league, he’s won the scoring title 7 times and no one else has won it more than twice. Sitting at 607 career goals, Ovi continues to propel himself further up the list of all-time greats. His 0.605 goals per game ranks first league-wide, beating out all other forwards by at least 0.08 G/GP.

Ovechkin loves slap shots, which should come as no surprise to anyone who’s watched Washington’s power play operate. His 17 slap shot goals were an uncontested 1st league-wide, with Steven Stamkos being the only other forward to score more than 7. Ovechkin’s slap shot is so powerful that it beats goalies clean even whey they know it’s coming, meaning that it can be unleashed without needing to be disguised.

Equally noteworthy, Ovechkin scored just 31% of his goals by wrist shot, which represents the lowest rate among all 32 players who scored 30+ goals.

Heat Map courtesy of Micah Blake McCurdy's website HockeyViz (https://hockeyviz.com)

Heat Map courtesy of Micah Blake McCurdy's website HockeyViz (https://hockeyviz.com)

The red areas in the above heat map show where Ovechkin shoots more frequently than the rest of the league. Ovechkin makes an absolute killing at the top of the left faceoff circle, often referred to as the ‘Ovi Spot’. This area lines up with Ovechkin’s average shot distance of 32.3 feet, which ranked in the 80th percentile among the league’s forwards.

Although it’s not reflected in the heat map, much of Ovechkin’s damage is done with the man advantage playing the left point. Of his 49 goals, 17 were scored on the power play, which ranked 2nd only behind a player further down this list. His remaining 32 were scored at even-strength, which again ranked 2nd in the league. Elite scoring across both special teams and even-strength situations throughout his career has propelled Ovechkin to the status of the league’s premier goal scorer.

Evgeni Malkin

Elite Scorers 5.jpg
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Despite being the second-best player on his team, Malkin has put together the resume of an elite goal scorer. He’s scored 75 goals in 140 games over the past two seasons, which converts to 44 goals over an 82-game season. His career goals per game of 0.472 ranks 6th among active forwards, placing him in elite company.

What makes Malkin dangerous is his offensive versatility; he can score from anywhere on the ice. Equal parts power and precision, Malkin possesses a variety of weapons. His snap shot goal rate clocks in at roughly double the league average (his 11 snap shot goals ranked 4th), but his middle-of-the-pack rates for wrist shots, slap shots and backhands speak to his balanced toolkit. Malkin does not rely on a single shot type to score goals, meaning that defenders must respect all shot types that Malkin credibly threatens. 

Heat Map courtesy of Micah Blake McCurdy's website HockeyViz (https://hockeyviz.com)

Heat Map courtesy of Micah Blake McCurdy's website HockeyViz (https://hockeyviz.com)

Did I mention that Malkin can score from anywhere? The sea of red is the beauty of Evgeni Malkin. He’s one of the most complete offensive players in the league. In addition to his heavy shot, his slick puck-handling ability and power forward frame allow him to generate shots and scoring chances at elite rates in the low slot area. His shot distance ranked just inside the upper third league-wide, influenced both by his crease-area chances and his shot activity in the high slot.

Malkin joins Ovechkin as the only two players in the league to finish top-10 in both even-strength goals and power play goals. He scored 28 times at evens, ranking 7th, and 14 times with the man advantage, ranking 6th. Malkin is one of the game’s most dangerous players in the offensive zone, and his goal scoring abilities rank among the NHL’s elite.

Connor McDavid

Elite Scorers 8.jpg
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At this point, not much more needs to be said about Connor McDavid’s offensive game. His 108 points were enough for a second consecutive Art Ross (but not Hart) Trophy. He’s the been the league’s best forward for the last two years, and he’s only 21 years old.

But is he a goal scorer? While it’s true that McDavid has been viewed more as a set-up man than a finisher thus far in his young career, in 2017-18 we saw a transformation in McDavid’s offensive role. Compared to the year prior, McDavid scored 11 more goals and took 23 more shots. He became more of a trigger man, electing to attempt shots more often instead of looking to pass. This development calls to mind a young Sidney Crosby, who recorded seasons of 70 and 84 assists before breaking out for 51 goals in 2009-10.

McDavid prefers to score goals with his wrist shot. His 25 wrist shot goals ranked 3rd league-wide behind only Nathan MacKinnon and Eric Staal, while his rate of 61% ranked 9th among the 32 players who scored 30+ goals. He hardly ever takes slap shots, registering just 7 of these shots during the entire season, of which just 1 beat the goalie. Rather than rely on strength to generate power, McDavid creates offense thanks to generational skating and elite-level hands. He’s able to create and navigate space better than anyone else on the planet and puts himself into positions where a quick and accurate wrist shot is more than enough to beat the goalie.

Heat Map courtesy of Micah Blake McCurdy's website HockeyViz (https://hockeyviz.com)

Heat Map courtesy of Micah Blake McCurdy's website HockeyViz (https://hockeyviz.com)

McDavid has figured out hockey’s (not-so) secret formula: if you get close to the net, you’re more likely to score. He's extremely effective at using his speed, hands, and vision to attack the most dangerous area of the ice. McDavid’s sub-20’ average shot distance is a testament to his elite ability to generate scoring chances from the crease and low slot area.

McDavid’s special teams split is intriguing. His 35 even-strength goals ranked first in the entire NHL, but his 5 power play goals tied him for 96th among forwards. This latter can be explained both by Edmonton’s league-worst power play and also McDavid’s primary role as a puck distributor on the top unit. If Edmonton’s power play improves, which is likely given regression to the mean, McDavid’s special teams goal-scoring could very well take a step forward and supplement his elite even-strength scoring totals. He is already the game’s best forward and he poses a legitimate threat to become the game’s best scorer sooner rather than later.

Nikita Kucherov

Elite Scorers 11.jpg
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A late 2nd round pick, Nikita Kucherov has emerged from relative anonymity to become one of the league’s most dangerous forwards. His 79 goals over the past two seasons place 3rd league-wide, and he was one of just three players to break 100 points in 2017-18.

While Kucherov’s absurdly accurate wrist shot remains his primary weapon (4th in wrist shot goals with 24), he is equally dangerous on the backhand. He scored 8 times (21% of all goals) on his backhand, ranking 2nd among 30+ goal scorers to Brad Marchand in both raw total and rate. Kucherov’s ability to score using wrist shots and backhands is all the more impressive considering that he shoots from further away than 93% of other forwards. He can be successful from this range without relying on the power of slap and snap shots due to his innate ability to find and exploit tiny gaps that goaltenders leave open. His shots are precise and accurate, and he excels at finding any available daylight.

Heat Map courtesy of Micah Blake McCurdy's website HockeyViz (https://hockeyviz.com)

Heat Map courtesy of Micah Blake McCurdy's website HockeyViz (https://hockeyviz.com)

An incredibly versatile player, Nikita Kucherov generates shots at elite rates all over the mid and high-slot. Rather than favour a specific shooting location, he elects to test the goalie from all areas of the offensive zone. This makes Kucherov unpredictable, which helps explain why his quick-release wrist shot and backhand are so devastating. He doesn’t shoot much from the crease area, but driving the net really isn’t part of how he creates offense.

Kucherov was more of a goal-scorer at even-strength than on the power play in 2017-18. He recorded 31 ES goals, one of just four players to crack 30, compared with 8 on the man advantage. He played more of a set-up role on Tampa Bay’s 3rd-ranked power play, registering 28 assists as he regularly sent cross-ice passes to Steven Stamkos (15 PP goals). Kucherov’s outstanding season cemented his status as one of the most dangerous goal scorers in the NHL, and at the prime age of 25 he’s as good a bet as any to repeat his offensive dominance next season.

Patrik Laine

Elite Scorers 14.jpg

At just 20 years old, Patrik Laine is already among the game’s premier snipers. His 44 goals ranked 2nd league-wide in 2017-18, fueling the Jets to their franchise-best season. Laine’s biggest asset is his shot, which may very well be the best in the league. Among current NHLers with 50+ career goals, Patrik Laine’s career shooting percentage of 18.0% ranks 2nd behind only Paul Byron. Byron, meanwhile, had an average shot distance of 19.3 feet in 2017-18, least of all eligible forwards, while Laine’s average shot came from 36.1 feet, ranking in the 97th percentile. The kid can shoot the puck.

Laine’s weapon of choice is his snap shot, which he routinely uses to one-time pucks into the back of the net. His quick release and accurate shot placement resulted in 14 snap shot goals in 2017-18, which tied for the league lead with Phil Kessel. He also is a fan of the slap shot, with his 6 slap shot goals placing him in a tie for 4th among all forwards.

Heat Map courtesy of Micah Blake McCurdy's website HockeyViz (https://hockeyviz.com)

Heat Map courtesy of Micah Blake McCurdy's website HockeyViz (https://hockeyviz.com)

Here we see Laine’s favourite shooting locations. A right-handed shot, Laine loves to one-time pucks from the high slot. The fact that he’s able to beat the goalie so consistently from so far away speaks to his talent as a shooter. Like Ovechkin, Laine’s shooting locations lack variety, but he’s so good from his spots that goalies have difficulty stopping the shot even if they can anticipate that it’s coming.

The triggerman for the Jets’ 5th-ranked power play, Laine lead all NHLers with 20 power play goals in 2017-18. He would routinely patrol the space between the left half-wall and left point, making himself open to cross-seam passes and one-timing his quick snapshot on net. His 24 even-strength goals tied for 20th in the league, so he’s no slouch at 5-on-5 scoring either.

Since breaking into the league, Laine has used his generational shot to pick apart opposing goalies. The odds-on favourite to inherit Ovechkin’s throne as best goal-scorer is the league, the sky’s the limit for a kid who potted 44 goals in just his second season in the league.

 

Conclusion

So there we have it; the modus operandi of five of the game’s elite. While Ovechkin, Malkin, McDavid, Kucherov, and Laine possess a shared gift for putting the puck in the net, they achieve it with vastly different sets of techniques, skills, and strategies. There is no uniform way to score a goal across the league, but all that matters is that it goes in.

With goals representing the currency of the NHL, goal-scorers are among the most valuable assets out there. Scoring goals wins you games, playoff series, and, as 32-year old Alex Ovechkin and 31-year-old Evgeni Malkin know, Stanley Cup championships. Kucherov (25), McDavid (21), and Laine (20) have not yet won hockey’s ultimate prize but given their relative youth and their otherworldly ability to put the puck in the net, they might not be far away.

 

Data courtesy of Hockey Abstract (http://hockeyabstract.com/testimonials), Natural Stat Trick (https://naturalstattrick.com), and NHL.com (https://nhl.com)

Shot heat maps courtesy of Micah Blake McCurdy’s wonderful visualization website HockeyViz (https://hockeyviz.com)

Cover photo credited to NHL.com

The Stanley Cup Formula: An investigation through machine learning by Guest User

Crosby Cup.jpeg

By Owen Kewell

NHL seasons follow a formulaic plotline.

Entering training camp, teams share a common goal: win the Stanley Cup. The gruelling 82-game regular season separates those with legitimate title hopes from those whose rosters are insufficient, leaving only the sixteen most eligible teams. The attrition of playoff hockey gradually whittles down this number until a single champion emerges victorious, battle-tested from the path they took to win hockey’s top prize. Two months off, then we do it all again.

Teams that have won the Stanley Cup share certain traits. Anecdotally, it’s been helpful to have a dominant 1st line centre akin to Sidney Crosby, Jonathan Toews or Anze Kopitar. Elite puck-moving defensemen don’t hurt either, nor does a hot goalie. Delving deeper, though, what do championship teams have in common?

I decided to answer this question systematically with the help of some machine learning.

Some background on classification

Classification is a popular branch of supervised machine learning where one attempts to create a model capable of making predictions on new data points. We do this by building up, or ‘training’, the model using historical data, explicitly telling the model whether each past data point achieved the target class that we’re trying to predict. In the context of hockey, this data point could be some number of team statistics produced by the 2015 Chicago Blackhawks. The target here would be whether they won the Stanley Cup, which they did.

Sufficiently robust classification models can identify a number of statistical trends that underpin the phenomenon that they’re observing. The models can then learn from these trends to make reasonably intelligent predictions on the outcome of future data points by comparing them to the data that the classifier has already seen.

Building a hockey classifier

We can apply these techniques to hockey. We have the tools to train a model to learn which team statistics are most predictive of playoff success. To do this, we must first decide which stats to include in our dataset. To create the most intelligent classifier, we decided to include as many meaningful team statistics as possible. Here’s what we came up with:

team stats.jpg

It’s worth noting that we engineered the ‘Div Avg Point’ feature by calculating the average number of points contained by all teams in a given team’s division. The remaining statistics were sourced from Corsica and Natural Stat Trick. An explanation of each of these stats can be found on the glossaries for the two websites.

Our dataset included 210 data points: 30 teams per season over the 7 seasons between 2010-11 and 2016-17. Each data point included team name, the above 53 team stats, and a binary variable to indicate whether the team in question won the Cup. Using this data, we trained nine different models to recognize the statistical commonalities between the 7 teams whose seasons ended with a Stanley Cup championship. The best-performing model was a Logistic Regression model trained on even-strength data, and so all further analysis was conducted using this model.

Results: Team stats that matter most to Stanley Cup winners

To evaluate which team stats were most strongly linked to winning a Cup, we created a z-score standardized version of our team data. We then calculated the estimated coefficients that our logistic regression model assigned to each team stat. The size of these coefficients indicates the relative importance of different team stats in predicting Stanley Cup champions. The 5-highest ranking team stats can be seen below:

top 5 team stats.jpg

Of all team statistics, ‘Goals For Per 60 Minutes’, or GF/60, is most predictive of winning a Stanley Cup. Of the 7 champions in the dataset, 4 ranked within the top 5 league-wide in GF/60 in their respective season, with 2016-17 Pittsburgh most notably leading the league in the statistic. Impressive results in ‘High Danger Chances For’ and ‘Team Wins’ both strongly correlate to playoff success, while ‘Scoring Chance For Percentage’ and ‘Shots on Goal For Percentage’ round out the top 5.    

What does it mean?

Generating a list of commonalities among past champions allows us to comment on what factors impact a team’s likelihood of going all the way. Most apparent is the importance of offense. It is more important to generate goals and high-danger chances than it is to prevent them, as GA/60 and HDCA rank 36th and 13th among all statistics, respectively (their corollaries are 1st and 2nd). In the playoffs, the best team offense tends to trump the best team defense, which we saw anecdotally in last year’s Pittsburgh v Nashville Final. If you want to win a Stanley Cup, the best defense is a good offense.

offense vs defense.jpg

We can see that a team’s ability to generate scoring chances, both high-danger and otherwise, is more predictive of playoff success than their ability to generate shots. Although hockey analytics pioneers championed the use of shot metrics as a proxy for puck possession, recent industry sentiment has shifted towards the belief that shot quality matters more than shot volume. The thinking here, which is supported by the above results, is that not all shots have an equal chance of beating a goalie, and so it is more important to generate a shot with a high chance of going in than it is to generate a shot of any kind. Between a team who can consistently out-chance opponents and a team who can consistently out-shoot opponents, the former is more likely to win a hockey game, and therefore playoff series.  

Application: The 2017-18 season

A predictive model isn’t very helpful unless it can make predictions. So let’s make some predictions.

By feeding our model the team stats produced by the recently-completed 2017-18 regular season, we can output predictions of each team’s likelihood of winning the 2018 Stanley Cup. Since this is the fun part, let’s get right to the probability estimates for all 31 NHL teams:

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The rankings above essentially indicate how similar each team’s season was to the regular season of teams that went on to win it all. In doing so, they hope to identify the teams most likely to replicate this success The model favours the Boston Bruins to win the 2018 Stanley Cup, predicting a victory over the Nashville Predators in the Final.

The above data highlights a few curiosities. Notably, we can see that some non-playoff teams had 5-on-5 numbers that were relatively comparable to past Cup champions. Specifically, the Blues, Stars, and Flames played 5-on-5 hockey well enough this season to qualify for the playoffs. The Blues and Flames can attribute their disappointingly long off-seasons to the 30th and 29th-ranked power plays, respectively. The Stars’ implosion is more of a statistical anomaly, and while conducting an autopsy would be interesting it would be better served as a subject for another article.

The lowest-ranked teams to have made the playoffs in the real world are the New Jersey Devils and the Washington Capitals. While their offensive star power might have been enough to get these squads to the dance, the model predicts a quick exit for them both.

A computer-generated bracket:

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For fun, I’ve filled out the above bracket using the class probability rankings generated by our model. Of the 8 teams who have won or are winning their first-round playoff series, the model picked 7 of them as at the winner, with Philadelphia being the exception. While it’s far too early to comment on the model’s accuracy, as only a single playoff series has been completed, it’s an encouraging start.

Limitations of the analysis

The above results must be considered in the appropriate context. The model was trained and tested using only 5-on-5 data, which would explain the lack of love for teams with strong special teams like Pittsburgh and Toronto. The model is also blind to the NHL’s playoff format. Due to the NHL’s decision to have teams play against their divisional foes during the first two playoff rounds, teams in strong divisions have a much harder road to winning a Cup. Consider that Minnesota’s path to the conference final would likely involve Winnipeg and Nashville in the first two rounds, who finished 2nd and 1st in NHL standings in the regular season. Divisional difficulty is not reflected in the probabilities listed above, though incorporating divisional difficulty either probabilistically or through a strength of schedule modifier could be areas of further analysis.

A final limitation of the model is that it is trained using only 7 champions. In an ideal world, we would have access to dozens or hundreds of Stanley Cup positive instances, but due to the nature of the game there can only be one champion per year. We considered extending the dataset backwards past 2011 but ultimately decided against doing so. The NHL is different today than it was in the past. Training a model on a champion from 2000 tells us little about what it takes to have success in 2018. Using 2010-11 onwards represented a happy medium in the trade-off between data relevance and quantity.

What next?

Winning a Stanley Cup remains an inexact science. While it’s valuable to identify trends among past winners, there is no guarantee that what’s worked before will work again. It’s a game of educated guesses.

I believe that the most legitimate way to build a Stanley Cup winner is a combination of the past and the future. Analyzing historical data to identify team traits that are predictive of a championship is half the battle. The rest is anticipating what the future of the NHL will look like. The champions of the next few years will be lead by managers who are best able to identify what it’ll takes to win in the modern NHL. While the above framework approaches the first half in a systematic way, the latter remains much harder to crystallize.

In the meantime, let’s turn to what’s in front of our eyes. The playoffs have been tremendously entertaining thus far, and that’ll only pick up as teams are threatened by elimination. Let’s enjoy some playoff hockey. Let’s see which playing styles, tactics, and matchups seem to work. Let’s learn.

Even if your team gets eliminated, just remember that this season’s playoffs are just a couple months away from being data points to train next season’s model.

Then we do it all again.

Cover photo credited to Christopher Hanewincke — USA Today Sports