Can Mike Babcock Save the Toronto Maple Leafs?

If you’re an NHL fan, and you weren’t preoccupied by sideshows like the Eastern Conference Finals yesterday, you’re doubtless aware that Toronto fans have found a new savior, as the Maple Leafs announced that long-time Red Wings (and Team Canada) head coach Mike Babcock will take over behind the team’s bench next season. Given Babs’ pedigree as a Stanley Cup and Olympic gold medal winner, and as the boss of a lot of superb possession teams, the move has created a lot of excitement, with some expecting a return to the postseason in 2015-16 and others wondering how quickly the team can realistically contend for a Cup.

Image credit: Flickr user Brendon Federko. Use of this image does not imply endorsement.

Leafs fans have certainly suffered a lot in recent seasons, and a part of me is tempted to sit back and let them enjoy this moment, rather than be the voice of skepticism. On the other hand, if you do something well, you’re probably wise to keep it up. So, here are some reasons to be skeptical about Babcock’s ability to engineer a quick turnaround in Toronto:

1. The puck possession brilliance of his Red Wings teams depended significantly on Nicklas Lidstrom. On one hand, Babcock’s ability to wring tremendous performances out of talented lineups is beyond question. Even leaving aside the Stanley Cup championship in 2008 and the President’s Trophies his Wings won in 2005-06 and 2007-08 (along with playing in Game 7 of the Cup Final in 2009), score-adjusted Fenwick data from WAR on Ice reveals an incredibly impressive fact: over the past ten seasons, four of the five strongest possession teams were Babcock-coached Wings teams, including a 56.8% SAF in 2008-09, a 57.6% SAF in 2005-06, a 58.5% SAF in 2006-07, and an unbelievable 59.9% SAF in 2007-08.

Still, it should be noted that having an all-universe two-way defenseman can make an enormous difference in a team’s possession game. Zdeno Chara in Boston is an obvious example, but probably the best lies in the contrasting possession numbers of Randy Carlyle-coached teams with and without Chris Pronger and Scott Niedermayer. Carlyle’s Anaheim teams posted very solid possession numbers in 2005-06 (52.5% SAF) and 2006-07 (53.4% SAF), and respectable numbers in 2007-08 (50.6% SAF) and 2008-09 (50.7% SAF); without Pronger in 2009-10, those numbers plummeted to 46.7%, and without both in 2010-11, they dropped to 45.2% (I don’t think Carlyle’s team possession numbers in Toronto deserve further comment).

The bottom line here is this: in seven seasons with Lidstrom patrolling the blueline, the Red Wings had a score-adjusted Fenwick just over 56%. In the three seasons since Lidstrom retired, that number has been 52.4%. While that’s still a very solid number, the gap between these two figures implies that Babs is unlikely to repeat the dominating possession numbers we often associate with his teams, especially with Toronto’s lineup.

2. While the Leafs’ possession game is almost certain to improve, the wins may not follow. With the dark days of the Carlyle era over, the Leafs’ possession will almost certainly be better than the 43.8% SAF they’ve had over the past three seasons. And honestly, for a team that’s been unbelievably poor defensively, Babcock could be exactly the remedy that’s needed: with or without Lidstrom, his Wings teams have been some of the NHL’s best when it comes to shot prevention. Still, this begs an obvious question: how was Babcock able to maintain the Red Wings’ defensive performance after the loss of Lidstrom?

The answer, it appears, lies in the Wings’ rate of shot creation. After being one of the league’s most dynamic offenses, in terms of the rate of Corsi attempts for, between 2007-08 and 2011-12, Detroit dropped to the middle of the pack in the following two years, and ranked just 23rd last season. Unsurprisingly for a team lacking a true sniper, their goal production dropped off dramatically: after being one of the higher-scoring teams in the league for several seasons, Detroit’s even-strength scoring fell to 27th in 2012-13, 13th in 2013-14, and 25th this season. What these numbers suggest is that Babcock essentially focused on defensive soundness at a considerable cost to the Red Wings’ attack. While this approach was unquestionably effective in terms of goal prevention, the implications for wins and losses are more debatable. While Detroit’s 2012-13 team is best remembered for a playoff run that included besting the Pacific champion Ducks and blowing a 3-1 series lead to the eventual Cup winners, it’s fair to point out that their season got off to a very rocky start, and they needed a scorching stretch run to get into the playoffs as the West’s 7th seed. In 2013-14, a late run and the Maple Leafs’ collapse was the difference in letting Detroit sneak in as the second Eastern wild card. This past season, the Wings got off to a strong start, but slumped towards the end of the year, only avoiding being a wild card team by a single point. So, for everyone who’s ready to pencil next season’s Leafs in for a playoff spot, remember that, post-Lidstrom, Babcock’s Red Wings have essentially been a bubble team.

3. The rebuild. While the public-relations impact of the hiring is obvious, a part of me was more than a bit surprised that the Leafs chose to go with a big-name coach rather than a “placeholder” guy, for the simple reason that the Leafs aren’t, today, a team that’s anywhere close to contention. One obvious concern, if you’re a Toronto fan, has to be this: given the organization’s extensive history of short-term thinking and the notoriously difficult Toronto sports media, are the Maple Leafs really willing to tolerate losing for a few seasons, especially after such a high-profile hiring? The worst thing the team could do right now would be to stand pat with their existing roster in the hope that Babcock can work enough magic to get the Leafs back into the playoffs next season. Whatever your expectations are for Babcock, or Brendan Shanahan, or for Kyle Dubas and the analytic braintrust in the front office, the simple fact is that years of mismanagement by previous regimes are going to take time to undo. There’s no reason to think that the Leafs can’t be good in a few years, but there are plenty of reasons to think they can’t be good next year.

Assuming that Toronto sticks to their plan for a rebuild, their opening-night roster for 2015-16 is unlikely to bear much resemblance to the group that started 2014-15. In order to correct the mistakes of the past and position the team well for the future, the Leafs need to get younger, and (for the time being) they need to get cheaper. Behind William Nylander, Toronto’s current prospect depth is very thin, and there’s a strong case to be made that a few more seasons of high draft picks could do wonders for their talent pipeline. The imperative to shed salary will likely mean the end of Phil Kessel’s time in a Leafs jersey; Kessel is owed $56M over the next seven seasons, but as a proven scorer in a low-scoring league, he’s the only big Leafs contract with a lot of value to other teams. Toronto, unfortunately, has some terrible contracts on the books that need to be moved before any rebuild can begin: Joffrey Lupul hasn’t played anything close to a full NHL season since 2008-09, and he’s owed almost $16M over the next three seasons; Dion Phaneuf, while still a potentially useful player, is vastly overpaid at $7M a year until 2021; the aging Stephane Robidas will make $6M over two more years; and Tyler Bozak will be paid like a top-two center for three more years. The most likely scenarios for these players are either (1) they stay in Toronto, which is bad for the rebuild, (2) they’re traded in retained-salary deals, which is also not great for the rebuild, (3) they’re dealt in return for other bad contracts (again, not good for the rebuild), or (4) the Leafs deal them without retained salary, but are forced to package a good player with them to make the deal happen. Regarding option four, it would be unfortunate, if not entirely surprising, if Nazem Kadri left the team in a deal of this sort, given his conflicts with the team this past season. The broader point, though, is that Toronto fans shouldn’t expect other teams to just take the Leafs’ bad contracts on without some benefit to themselves.

My expectations for the first year of the Babcock era, then, are not all that rosy. Fixing the problems created by Brian Burke and Dave Nonis will not be a quick process, or an easy one. Babs can be counted on to get every ounce of talent out of the roster that he’s given. But for at least the next year or two, he probably won’t be given much.

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2014-15 NHL Playoffs: Conference Final Predictions

After an exciting opening two rounds of the NHL postseason, we’re now on to the final four. It’s been a good playoff year for the Puck Prediction model: with New York breaking the hearts of Caps fans in last night’s Game 7, my record sits at 10-2 so far. You can find a description of my model here. With that, let’s move on to the Conference Finals, which, if my model is correct, will not take long at all.

Eastern Conference Final

New York Rangers (mGF% 52.5%) vs. Tampa Bay Lightning (mGF% 55.8%)

On the heels of their second comeback from a 3-1 series deficit in as many years, the Rangers are back in the Eastern Conference Final. Despite their President’s Trophy, New York has looked far from dominating in the opening two rounds of the playoffs: their possession numbers are essentially neutral, while all twelve of their games have been decided by a single goal. Unsurprisingly, Henrik Lundqvist has been a rock for this postseason (0.943 Sv% at 5v5), but they’re shooting a miserable 5.4% as a team, a far cry from the 8.8% number they enjoyed in the regular season. Unfortunately, they’re about to face a tremendous defensive squad in Tampa Bay. While the Rangers have a sizable advantage in goal – Bolts goalie Ben Bishop has been . . . uneven this postseason – they’ll need their finishing to turn around quickly if they’re to score enough goals to top the NHL’s most prolific offense in 2014-15. Insofar as they’re likely to be at a significant possession disadvantage, this won’t be easy. There’s always the chance that Lundqvist steals the series for New York, but Tampa Bay promises to be a much tougher challenge than either of the Rangers’ first two opponents.


Prediction: Tampa Bay in four games.

Western Conference Final

Anaheim Ducks (mGF% 51.8%) vs. Chicago Blackhawks (mGF% 55.8%)

It’s been an interesting postseason for both these teams. As many expected, the Ducks stormed through the Pacific Division playoffs, dispatching the Jets and Flames in nine total games. Goalie Frederik Andersen has rebounded from the shaky end to his regular season with 0.936 play in the postseason, and Anaheim’s 9.5% even-strength shooting through the opening rounds is kind of what we’ve come to expect from them. Interestingly, the Ducks have also dominated possession thus far in the postseason, though a good bit of that dominance came against a terrible possession team in Calgary. At the other end, the Blackhawks surprised many of us by needing just ten games to move through the tougher Central teams on the way to their third straight Conference Final appearance. After a rocky opening series against Nashville, Corey Crawford rebounded well against Minnesota, allowing just three goals on 111 even-strength shots in the sweep of the Wild. Their playoff possession differential may not be as gaudy as Anaheim’s, but the quality of their opposition has been much higher. I’d expect the Ducks to have a much tougher time controlling play against Chicago, and if Crawford is back to his regular-season form, this series could be over quickly.


Prediction: Chicago in four games.

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NHL Goal-Scoring Environments and Comparative Advantage

While attentions (including mine) are focused on the NHL postseason these days, I continue to marvel at some of the crazy results we had during the regular season: last year’s Stanley Cup and President’s Trophy winners both failing to make the playoffs, the end of San Jose’s long playoff streak, the Pittsburgh Penguins barely scraping in as a wild-card team, the unlikely story of the Calgary Flames, and Anaheim’s continued ability to crush the rest of the league despite middling underlying numbers. Recently, I shared an analysis of why the Los Angeles Kings suckmissed the postseason, which posited the following: in a low-scoring season, LA’s strong defensive game wasn’t an enormous asset, while their below-average scoring (18th in the NHL in goals-for) lodged them on the playoff bubble; bad luck in one-goal games was enough to leave them on the outside looking in. I’ve taken a fair amount of criticism for this theory, but I’m actually more interested in the broader implications of my argument. Is goal-scoring, rather than goal-prevention, what makes teams “elite” in a low-scoring era, and if so, has the opposite been true in higher-scoring eras of the NHL?

If you’re a student of NHL history or of scoring rates throughout various eras of the game, you may be familiar with the graph below, which charts out the average number of goals per NHL game through the league’s history. (The red line indicates the historical average of just over 6 goals per game.) As discussed here, rates of goal-scoring have fluctuated throughout the NHL’s 98 seasons, whether due to changes in playing styles and strategies, technological advances, league and schedule expansion, or the institution of the salary cap in 2005. The early NHL was actually very high-scoring, but rapid innovations in defensive tactics saw goal rates plummet quickly, and apart from a blip from 1941 to 1947, NHL games averaged fewer than six goals per game until 1970, when the effects of expansion made themselves felt. From 1970-71 until 1996, we experienced the Firewagon era, where the rate of goals surged upward, peaking at a rate of roughly eight per game between 1982-83 and 1985-86. In the 1990s, innovations in goaltending equipment and technique, along with the emergence of defensive systems like the neutral-zone trap, caused goal-scoring to trend back downward. Apart from a one-year uptick in 2005-06, scoring has continued at a below-average rate, and with the salary cap making it difficult to assemble dominant offensive squads, it’s possible that we won’t see an NHL season averaging six goals per game again.


I collected standings-points percentages, goals for and goals against for every team-season in NHL history (n = 1,415), and calculated single-season league averages for goals scored and allowed. For each team-season, I then calculated each team’s percentage of goals scored above league average, as well as their percentage of goals allowed below league average. So, for example, the league-average number of goals scored (and allowed) in the 2014-15 NHL season was 224; the Tampa Bay Lightning scored 38 more goals than the average (38/224 = 17%), and allowed 13 goals fewer than the average team (13/224 = 5.8%). As you’ll see below, I used stacked bars to depict how above- (or below-) average each team was on both measures. I then divided the data by season into seven “eras”: 1) the higher-scoring seasons between 1917-18 and 1922-23, 2) the lower-scoring seasons between 1923-24 and 1940-41, 3) the higher-scoring seasons between 1941-42 and 1946-47, 4) the lower-scoring seasons between 1947-48 and 1969-70, 5) the Firewagon era between 1970-71 and 1995-96, 6) the “Dead Puck” era between 1996-97 and 2003-04, and 7) the 10 seasons of the salary-cap era. (Reasonable people have disagreed on ways to characterize the eras in the league’s history, but for now, we’ll just focus on goal-scoring environments.) The data are sorted by season points percentage (obviously, the seasons of better teams are on the left, poorer teams are on the right) and graphed below. The simple way to interpret these graphs: when I look at the best teams in each era, are they heavier on blue or on red?


A glance at the first two eras lends some support to my theory. In the early days of the league, around World War I, the most successful teams were the most defensive. Four of the top ten teams in this very high-scoring era were actually below-average offensively. The team with the highest points percentage from 1917 to 1923 was the 1919-20 Ottawa Senators, who scored just 5% more goals than league average, but allowed 44% fewer goals than the average. Moving into the inter-war years, the league was much more defensive (even more so that it is today, in terms of goal rates), but the highest-scoring teams are heavily represented among the elite squads. Among the top 20% of teams in this era, only three scored fewer goals than the league average that season. Defensive ability, on the other hand, is well-represented even among more mediocre teams from this era.


The two eras after this include the NHL in World War II, and then the Original Six era leading up to expansion. Given the dilution of league talent caused by Canada’s entry into the war, scoring surged during the former era, while the latter era was characterized by below-average scoring rates. We see the same pattern we saw before: the best teams during the World War II era were the most defensively capable, while the highest-scoring team-seasons from the Original Six era clustered heavily at the top of the standings.


Things get slightly murkier when we move into the modern NHL. Rapid expansion of the league, along with years of particularly helpless goaltending, led to high-scoring hockey between the years of 1970 and 1996. This was, however, also an era of dynasties, including the Canadiens of the late 1970s, the Islanders of the early 1980s, and the Oilers of the mid-80s; as the table below shows, both offensive and defensive acumen were heavily clustered at the top of the standings during the Firewagon era. Unless you were one of the top 5% of teams in that era, your ability to stay in the top half of the standings (i.e., playoff position) was determined to a greater extent by goal prevention than scoring. In the Dead Puck era, elite teams were defined by their goal-scoring more than their defending, as scoring regressed heavily toward league average outside of the strongest squads. That is, while goal-prevention was still important to playoff teams in these eight seasons, goal-scoring fell off a cliff for everyone but the best teams. The Trap years, of course, also have a similar “dynasty” confounder, as the Stars, Red Wings, and Senators are heavily represented among the top team-seasons. Also worth noting: in both eras, teams in the 25th to 50th quartile of standings points were not much better than league average in either scoring or defending.



Finally, we come to the salary-cap era. The effect of the cap on parity can be seen in the middle of the chart, where teams just above and just below the 50th percentile are hard to distinguish from one another. When we look at a table similar to the ones I created for the Firewagon and Trap eras, we see this in the results for teams in the 25th to 50th quartile: on average, these teams are not much better than those below the 50th percentile. Goal-scoring is clustered relatively tightly among the elite teams, and falls off sharply once you’re outside the top 10%. Goal prevention is distributed much more evenly across teams.


Some conclusions to draw from this:

  • To summarize, it looks like the data are consistent with my theory. That is, in high-scoring eras of NHL hockey, superior defense sets strong teams apart from the rest, while in low-scoring environments, the ability to score goals is what defines elite teams. It’s basically a question of comparative advantage: it’s better to be above average at something no one is good at that superb at something everyone is good at.
  • Assuming that the NHL’s cap-induced parity and low scoring environment aren’t going anywhere, obtaining and keeping elite offensive talent would appear to be an indispensable key to building an elite team nowadays. This suggests a guideline for teams to follow in managing their salary cap: if you’re going to break the bank on a massive, cap-crippling contract, only do so for an elite scorer. Defense and goaltending matter, but in a goal-scarce league, the ability to prevent goals without scoring makes you indistinguishable from a lot of teams. So, you know, if you happen to find yourself with players like Tyler Seguin or Phil Kessel, try not to trade them away.
  • These data also suggest that analyses of team quality that boil down to a simple look at their possession differential may be misleading; the event rate driving that differential also matters. Generally speaking, there are three ways a team can build up good possession numbers: giving up a ton of shots but creating even more; not creating much offense but allowing opponents even less; or occupying a middle ground between these extremes. These results suggest that a low-event style may work against a strong possession team in a low-scoring environment. Like the Devils in 2012-13 and 2013-14, such teams may struggle to make the playoffs because their rate of shots is too low for them to score enough goals. This isn’t intended to downplay the usefulness of possession-based analytics, but rather to argue that there’s a bigger picture worth considering.
  • So, was I right about the 2014-15 Kings? Well, if we assume that 82 games is long enough to see the effect of talent versus random variance in the standings, it stands to reason that the regular season tells us pretty clearly which teams absolutely belong in the postseason and which teams absolutely do not: if you’re on the bubble after 82 games, odds are you belong there. In 2014-15, LA’s goal-scoring numbers were 1.7% below league-average, and they allowed 8.5% fewer goals than the average. In the context of the era, those defensive numbers were just outside the 25th percentile, while their goal-scoring fell in the bottom half of teams. These aren’t terrible numbers, but they’re hardly those of an elite team, so it shouldn’t be surprising that LA found themselves battling for a wild-card spot.
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2014-15 NHL Playoffs: Second Round Predictions

A tightly-contested first round is now in the books, and overall, the Puck Prediction model didn’t fare too badly: with Tampa Bay’s victory in last night’s Game 7, I correctly picked six of the eight opening-round series. If you want to learn how my model works, all the details are either described or linked here. All that out of the way, let’s get to the second round.

Eastern Conference

New York Rangers (mGF% 52.5%) vs. Washington Capitals (mGF% 51.7%)

If this feels like a matchup you’ve seen before, you have: in the ten seasons since the 2005 lockout, this will be the fifth time the Rangers and Caps have met in the playoffs, with each team winning two of the prior meetings. While many observers were doubtless hoping for the first Rangers-Islanders matchup in a long while, instead the Capitals will continue to rack up frequent-flyer miles between Dulles and JFK. Still, this should be a fast-paced, exciting matchup. Throughout the 2014-15 regular season, the Rangers’ superb goaltending masked a mediocre shot-prevention game, though New York carried the possession battle in the first round against a strong puck-control squad in Pittsburgh. Although their smothering effort in Game 7 against the Isles is freshest in our minds, Washington struggled to drive the play at many points in their opening series. I’d expect their control of possession to be a bit more consistent against the Rangers, but without home-ice advantage and with Henrik Lundqvist in the opposing net, this will be another tough test for them.


Prediction: I won’t be surprised if I’m wrong, but New York in seven games.

Montreal Canadiens (mGF% 52.7%) vs. Tampa Bay Lightning (mGF% 55.8%)

These teams met just last year in the first round, when the Bolts limped into the postseason without starting goalie Ben Bishop, and bowed out in four poorly-played games. This year, while they looked very mortal at times against Detroit in the opening round, this was mostly due to the brilliant play of Wings goalie Petr Mrazek: as that robust mGF% number suggests, the Lightning are a very good team, and for the most part, they drove play against Detroit like a very good team. The Canadiens, in contrast, dispatched the Senators in six games despite not playing very well at all. Montreal’s first-round victory owed a lot to strong play by Carey Price, the early-series struggles of Ottawa rookie Andrew Hammond, and plenty of fortunate bounces. They enter the second round with home ice and a considerable advantage in goal – Bishop did not have a good 2014-15 season or a strong first round – but the obstacles they’re facing are pretty significant. For one thing, few teams are more stingy in allowing shots against than Tampa Bay, and few teams make their goaltender work harder than Montreal. If the bulk of this series is played in the Habs’ zone, as seems likely, the goaltending advantage may not matter much. For another thing, the Lightning were the highest-scoring team in the NHL this season; if any team in the field is capable of breaking through Price, it’s this one. I usually dislike boiling predictions down to a simple thing like the expected difference in possession, but if there was ever a series when doing so made sense, it’s this one.


Prediction: Tampa Bay in four games.

Western Conference

Anaheim Ducks (mGF% 51.8%) vs. Calgary Flames (mGF% 50.8%)

No two teams were responsible for more traffic to this website in the first round than these two: unlike many analysts, I had the odd distinction of a) predicting both to win, and b) using a purely statistical approach to do it. Anaheim’s regular-season success may have resulted in no small part from an insane 33-1-7 record in one-goal games, but their 51.7% score-adjusted Fenwick implies that the Ducks are more fundamentally sound than they’re often given credit for, and they carried the possession (against a strong possession team) in their first-round sweep of Winnipeg. The Flames, of course, caused no small amount of consternation among many numbers-inclined NHL fans, advancing to the second round despite a miserable 45.6% regular-season SAF. When it comes to the fundamentals, there’s no question Calgary are playing over their heads right now: the Flames are one of the league’s worst teams in both shot creation and shot prevention (not an easy feat for a non-lottery team), yet have ridden ex-Ducks goalie Jonas Hiller and the hottest team shooting in the Western Conference to where they are now. Still, to put Calgary’s first-round win in a bit of perspective, they aren’t the first team to make a playoff run despite awful underlying numbers. The 2006 champion Hurricanes, after all, entered the playoffs with an ugly 48.6% SAF, and the 2008 Penguins (46.6% SAF) came within two wins of a Cup themselves*. I didn’t pick the Flames to beat Vancouver because I thought the former was a strong team, but rather because I didn’t trust the Canucks to win a battle of percentages against anyone. In this series, I’d expect Hiller to offer better work in net than his ex-teammate Frederik Andersen (who’s had a poor season), but overcoming Anaheim will be a tougher task for the Flames.


Prediction: Anaheim in seven games.

Chicago Blackhawks (mGF% 54.6%) vs. Minnesota Wild (mGF% 52.3%)

Fans of the “divisional” playoff format, I hope you enjoy this: for the third straight season, the Wild and Hawks will meet in the postseason. Unlike prior seasons, however, this matchup feels much more even, with Minnesota and Chicago having roughly equivalent regular-season possession and shot-prevention numbers. Surprisingly, these two teams experienced roughly equivalent offensive output this season, as Patrick Kane’s injury dropped Chicago’s even-strength Sh% to an ugly 6.9%, while Minnesota’s shot up to an uncharacteristic 8.5%; still, given the Hawks’ higher rate of shot creation, any hint of regression to the mean will tend to favor them rather than the Wild. Minnesota will be hoping for more strong work from Vezina nominee Devan Dubnyk, who resurrected his career this season and played well in the opening-round upset of the Blues. At the other end of the ice, they’ll be looking at another opponent that had goaltending troubles in the first round. (My projection here assumes that Scott Darling will start for the Blackhawks.) This matchup should be interesting, though heavy on defense, but I’m guessing that home ice and their underlying quality will be enough to carry Chicago back to the Conference Finals.


Prediction: Chicago in five games.

* Some other lousy possession teams who at least equalled Calgary’s feat this season: the 2008 Canadiens (47.2% SAF, advanced to second round), the 2008 Flyers (46.7%, advanced to Eastern Conference Final), the 2010 Canadiens (46.7%, advanced to Eastern Conference Final), and the 2012 Predators (47.4%, advanced to second round). Honorable mention has to go to the 2013 Maple Leafs (44.5%), who came within 10 minutes of third-period score effects of advancing to the second round.

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Weekend Hockey Analytics Links: April 25, 2015

The first round of the playoffs is nearing its conclusion. As I write this, the Anaheim Ducks and New York Rangers are through to round two, and three more teams will try to punch their ticket today: the Washington Capitals will try for the fourth time to eliminate a team led by Jaroslav Halak, the Blackhawks will take their second crack at knocking out the Predators, and the Flames will try to keep their unlikely 2014-15 season going. In the meantime, below are links to some interesting hockey analytics reading I came across recently:

  • Following their 5-1 drubbing at home at the hands of the Senators last night, the Canadiens are a bit more nervous about their first-round series, having gone from a 3-0 lead to 3-2 (with Game 6 looming in Ottawa tomorrow). Prior to yesterday’s game, Chris Boyle wrote an interesting (and prescient) analysis suggesting that the Habs may be closer to blowing that 3-0 lead than many realize. As a Sharks fan, let me offer a word of advice to the Montreal faithful: watching this happen is even less fun than it sounds. No word on whether the team is panic-starting Alex Stalock for Game 6.
  • Earlier this week, ESPN’s Grantland released a short documentary on the role of analytics in pushing enforcer players out of the NHL. At about 9 minutes, it’s well worth your time. My thoughts about the film are here.
  • This is, of course, the time of year for statistical predictions of NHL playoff series, including mine. (In a change from last season, I’m not reposting revised series-win probabilities every day to this site; if you want them, follow me on Twitter.) Over at the Contrarian Goaltender blog, Philip Myrland warns about the dangers of overfitting playoff models. Basically, the temptation is to throw every variable you can into a model to increase its fit to the data (the NHL’s own SAP playoff model is an excellent example), but past a certain point, you might end up adding correlates with no causal relationship to playoff success. It’s an excellent piece, and a subject I touched on a year ago. I would extend the same critique to many simple playoff models, such as those that claim incredibly high accuracy using Score-Adjusted Fenwick % alone. Let’s face it, with the Kings and Stars watching the postseason from home, the Penguins and Jets already eliminated, and the Isles, Blues and Predators sitting on the brink, the predictive power of SAF% alone isn’t looking so hot right now.
  • Speaking of playoff series, Arik Parnass wrote an interesting piece recently at Hockey Prospectus on whether score effects exist at the series level as well as the game level. I need to think about this more carefully, but the implications for playoff models (mine and others’) are potentially huge, insofar as we usually assume each game in a series is independent from the others.
  • Ryan Stimson posted a fascinating analysis over at the Devils blog In Lou We Trust on the relationship between passing sequences and shot quality. Ryan is one of the most meticulous analysts I know of, and the article is very rich in detail, so I’ll just encourage you to read it and digest it for yourself rather than trying to summarize.
  • Ben Wendorf is a great source for insights into historical trends in the NHL, and recently he posted a piece on how parity in the league has shifted patterns in player usage. Basically, the data demonstrate an increasing trend toward optimal deployment by CF%. I’d recommend the whole piece.
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Knuckles vs. Numbers: Some Thoughts

Yesterday, hockey analytics had yet another “moment”, with the release of the short documentary Knuckles vs. Numbers, produced by the Grantland team at ESPN. The premise of the film, which runs just under nine minutes, is that the increasing influence of number-crunchers is pushing “enforcer”-type players out of the NHL. You can view the film, for free, on YouTube.

All in all, its an enjoyable movie. The perspective of the enforcers is provided in face-to-face interviews with Brian McGrattan, Paul Bissonette, and Colton Orr, and Barry Melrose drops in to add context. The primary narrator is Grantland’s Sean McIndoe, author of the Down Goes Brown column, and the analytics side is represented by two notable friends of this blog: Steve Burtch (who’s done great work on Sportsnet and the Maple Leafs blog Pension Plan Puppets) and Ben Wendorf (one of the creators of (If you like the film, Ben provides some behind-the-scenes anecdotes at his site, including descriptions of interesting footage that didn’t make the final cut.) In general, the documentary feels slightly slanted toward the enforcers; my obvious bias aside, the players are given repeated chances to explain their value in the game, and the film focuses on their struggles to stay in the NHL, while the value provided by the analytic side isn’t discussed in much depth. Nevertheless, the discussion of the metrics and the thinking behind them is solid, and easy for a novice to understand. Knuckles is definitely framed in old-school vs. new-school terms, and (perhaps unsurprisingly) it’s not very sympathetic to the new school. But a traditionalist fan unfamiliar with analytics can at least understand them better by watching this.

Still, one thing about the documentary bugged me, and I ended up discussing it on Twitter with Steve and David Johnson of Hockey Analysis: pointing to statistical analysts as the reason why the game is passing enforcers by seems overly simplistic. For me, the biggest reason these players are leaving the game is that they don’t have much of a role in the modern NHL. That fighting is on the decline is indisputable: McIndoe chugged through the numbers going back to the early 1990s, and more recent data are available here. Partly, this is due to the league’s decades-long crackdown on fighting (i.e., the instigator rule, the “third man in” ejection, stiff suspensions for leaving the bench or penalty box to fight, automatic ejections and supplemental discipline for line brawling, the “helmet rule”, and encouraging linesmen to break up more fights before they start). In recent years, increased concern for player safety and the long-term effects of head trauma have probably also played a part. The deaths of ex-enforcers like Derek Boogaard, Rick Rypien and Wade Belak, in particular, have shone a harsh light on the challenges many fighters face after their playing days end, and have led many to question the romantic notion of enforcers as providers of toughness and courage.

But the biggest changes have probably been to the game itself. Between the many post-lockout rule changes intended to increase the speed and flow of the game, the heightened parity introduced by the salary cap, and the scarcity of goals in today’s game, the modern NHL places a very high premium on hockey ability. And despite the old-school insistence on the value of enforcers (articulated very well by Melrose in the film), the role they actually play in today’s game is very telling: whether their teams are analytics believers or skeptics, enforcers these days are essentially specialists who play less than 10 minutes a game and only see the opponent’s worst players. This usage suggests that teams don’t view the value of enforcers in the same way that someone like Melrose does; more to the point, it suggests that they see what the numbers guys do, that these players are liabilities on the ice. On this point, it’s probably fair to credit the analytics movement to some extent; by breaking down the data on enforcers’ detrimental on-ice impact, and writing publicly about it, analysts have likely pushed the conversation within hockey in the direction that we’re seeing. Nevertheless, it’s probably fair to say that the NHL would have phased out the enforcer without our input, and that (at most) we’ve just helped the process along. I’m not sure that fighting will ever entirely vanish from the game, but I tend to agree that fighting specialists will be out of the NHL fairly soon. And insofar as the forces driving them out are unlikely to change, I don’t expect them to return.

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Why Did the 2014-15 Los Angeles Kings Miss the Playoffs?

The 2015 NHL playoffs are underway now, and (predictably) interest in the regular season has passed quickly into the rearview. Still, the 2014-15 season remains notable for the team most surprisingly absent from the postseason: the defending champion Los Angeles Kings. Following a 3-1 loss in Calgary just before the season’s final weekend, the Kings were officially eliminated. (I’m a Sharks fan, and chose to note the occasion this way.) Yet even to seasoned hockey analysts, this was a difficult result to explain.

Photo credit: Flickr user rtype03. Use of this image does not imply endorsement.

Aside from their pedigree as winners of two of the last three Stanley Cups, the Kings have been a popular favorite of the hockey analytics community due to their elite puck possession numbers over the past four seasons: LA has been one of the league’s top-five teams in Score-Adjusted Fenwick all four years, and have exceeded 55% SAF over the last three. Yet, interestingly, the typical explanations for good possession teams missing the playoffs don’t really apply to this season’s Kings. When the New Jersey Devils missed the playoffs in 2012-13 and 2013-14 despite superlative Fenwick numbers, it was straightforward to point to their terrible team shooting and even-worse goaltending as the culprits; those Devils stand alongside other solid possession clubs that have been undone by subpar play in net (the 2010-11 Flames come to mind). Yet this season’s Kings had a PDO a hair above 1.000, on the strength of solid 0.926 goaltending from Jonathan Quick and Martin Jones. So, what the hell happened in Los Angeles?

Unsurprisingly, analysts have had a tough time dissecting exactly what went wrong. Over at Hockey Analysis, David Johnson summarized many of the more common explanations I’ve seen rolling around the Twittersphere. The most popular analytic narrative for LA’s collapse is that, essentially, they had just enough terrible luck at the margins to knock them off the bubble: a 0.351 winning percentage in one-goal games and a 3-15 record in overtime/shootout games cost them just enough points that they finished two back of Calgary for the last playoff spot. Ben Wendorf also offered an interesting take over at Hockey Graphs, to the effect that lower scoring league-wide increased the impact of random bounces by creating more one-goal games, and tanking for the McDavid/Eichel lottery created more parity among the non-tanking teams.

I’m not convinced, though, that this is the whole story. First off, it’s not clear to me that lower scoring created an unusual number of one-goal games in 2014-15: in 82-game seasons since 2005-06, the NHL has tended to average between 570 and 590 such games, and this season’s 589 are on the high side, but not exceptionally so. As far as the impact of one-goal losses in 2014-15, playoff teams had a winning percentage of 56.3% in these games. This disparity is above average (normally playoff teams win roughly 54% of one-goal contents), but it’s not easy to interpret: aside from being somewhat trivial (i.e., more wins will tend to be associated with more standings points), it’s impossible to say from this number which teams lost because they were unlucky and who lost because they weren’t very good to begin with. Also worth noting is that the relationship between one-goal game win % and playoff probabilities is far from linear. Over the past 10 seasons we have plenty of examples of teams with poor one-goal-game records having strong seasons, and vice versa. To give some of the more dramatic examples:

  • This season’s Blue Jackets missed the playoffs with a 1GG record of 23-8-5.
  • Last season’s Maple Leafs had a 1GG record of 19-8-8. We know how their season turned out.
  • Last season’s Blackhawks had one of the worst 1GG records in the NHL (17-8-15).
  • In the shortened 2012-13 season, the Jets and Flyers had a combined 1GG record of 24-8-6. Both missed the playoffs.
  • The Cup champion Kings of 2011-12 won just 37% of their one-goal games.
  • The 2011-12 Lightning missed the postseason despite the best 1GG record in the NHL.
  • In 2010-11, New Jersey missed the playoffs despite a 21-8-5 1GG record.
  • Nashville missed the playoffs in 2008-09 despite a 22-8-8 record in one-goal contests.
  • In the same season, a 12-7-12 record in these games did not prevent the Blackhawks from reaching the Conference Finals.
  • In 2007-08, the Oilers and Islanders had a combined 1GG record of 48-16-15. Both missed the playoffs.
  • Ottawa made it to the Finals in 2006-07 despite winning just 31.3% of one-goal games that season.

Clearly, then, it’s quite possible to be one of the league’s better teams despite poor performance in one-goal games. Those of you interested in the shootouts side of this can check out some work I did last year (basically, shootouts matter, but not a ton). So I’m not entirely satisfied with this explanation for the Kings’ poor results. Fortunately, a deeper dive into the Kings’ numbers identifies the problem. On the defensive side, only six teams allowed fewer goals than LA, and no team allowed fewer shot attempts at even strength (score-adjusted) than the Kings’ 45.9 per 60 minutes. On offense, though, the story is less positive. Los Angeles attempted 58 shots at even strength per 60 (again score-adjusted), one of the highest rates in the league, but this was coupled with a thoroughly mediocre 7.5% team shooting percentage at 5-on-5; thanks to poor finishing and middling power play, the Kings ranked just 18th in goals scored this season. As such, it appears there is a metric on which LA looked like the bubble team they were.

The real question, then, about this season’s Kings isn’t whether poor performance in OT and shootout situations knocked them out of the playoffs, but rather why they were on that bubble in the first place. I think the answer lies in a concept from baseball analytics known as a “run-scoring environment”; this is the notion that the game is higher-scoring in some eras relative to others, and some strategies work better in higher-scoring environments than lower-scoring ones. I believe an analogous concept carries over to goal-scoring in the NHL. The important thing to remember about scoring environments is that it’s more important to be good at things others aren’t good at than exceptional at something everyone’s good at. No one questions the Kings’ defensive acumen; only the St. Louis Blues have allowed fewer goals over the last four seasons than LA’s 667, and in none of those seasons have the Kings averaged more than 50 even-strength Corsi attempts against per 60. Yet in a league that averages just 5.4 goals a game, great defending doesn’t differentiate you much from other teams. When goals are tough for everyone to come by, being able to score has a greater ability to set you apart from the pack, and some of the NHL’s best teams in the last four seasons are among the highest scoring: Pittsburgh tops that list with 894 goals, followed by Chicago (871), Tampa Bay (870), and Boston (854). (This may also provide a clue as to why Anaheim has been so successful in recent years, and why New Jersey hasn’t.) The Kings, in contrast, sit 23rd in goal-scoring over that time, and at this point, it’s hard to see their miserable 6.8% even-strength shooting as simple puck luck. And their regular-season results since 2011-12 have borne this out: they were a bubble team in 2012 and a mid-seeded playoff squad the last two years, and haven’t come within 15 points of a President’s Trophy* (even in the 48-game 2013 season) during that time. Given these results and what happened this year, one has to ask whether goal-scoring is a genuine flaw in the Kings that many analysts (myself included) have tended to overlook because of their playoff success and strong Fenwick differential.

* Critics will undoubtedly point to their Stanley Cups in 2012 and 2014. My usual response is that a goalie giving a team nearly 0.950 goaltending for two months isn’t necessarily an indication of their overall quality. Nor is two months of 8.9% shooting for a team that typically performs far below that.

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