The Scheduler’s Dilemma: Back-to-Back Games and Fatigue Effects in the NHL Regular Season

In the course of predicting all 1,230 games of the 2013-14 NHL season, one common occurrence made me doubt my model more than any other: back-to-back games. My model did a decent job overall when it came to picking games, but I often wondered whether I should have factored the effects of travel and fatigue into my predictions. Home ice provides a consistent advantage in NHL hockey, and is probably the most reliable predictor in single games, but it stands to reason that its effects should differ depending on whether one or both teams enters the game having played and traveled the night before. Yet it doesn’t seem that anyone has done a comprehensive study of the issue before. So, I pulled game dates for all regular-season contests since the 2005 lockout; after excluding season openers, this left me with a sample of 10,403 games. After playing with date functions in Excel, I was able to identify all the back-to-backs and travel in each team’s schedule.

First, I wanted to get a sense of the frequency of back-to-backs in a given season. The table below provides the median number of back-to-backs for each team in the eight 82-game seasons since 2005-06 (2012-13 data, obviously, are excluded). On average, a team can expect to play back-to-backs about 15 times each season, though there are clearly differences among teams. Part of this is likely due to the efforts of league schedulers to minimize back-to-back play for teams that travel more. As such, high-travel teams like Calgary, Colorado, Dallas, Edmonton, and Vancouver average fewer back-to-backs than teams like Buffalo, New Jersey, or the Islanders. In some cases, though, this explanation doesn’t really account for the patterns we see. The Rangers, for example, don’t suffer much at the hands of the schedule-makers, averaging the same number of back-to-backs as San Jose (the team with the most consistently brutal travel itinerary in the NHL) and fewer per season than the Anaheim Ducks, who regularly travel nearly 50,000 miles over 82 games. And the Blackhawks and Blues seem to play a lot of back-to-backs for teams that are regularly around 40,000 travel miles a season.


The real question, of course, is how bad it is to play more back-to-backs than other teams. Or, phrased differently, how does back-to-back play affect the expected advantage of the home team? The numbers based on the 10,000+ games in my sample are depicted below.


Overall, NHL teams playing on home ice can be expected to win about 55.1% of the time. If both teams are playing the second of back-to-back games, the home team’s advantage jumps a percentage point to 56.1%. If both teams are playing the second of a back-to-back after having traveled the night before, as in a home-and-home situation, the home team’s advantage is even greater, at 57.1%. This would suggest that the fatigue effect matters more for the road team, and a look at the more typical scenarios only reinforces this. When the home team is playing a back-to-back against a rested opponent, their win probability drops down to 53.8%, or about 1.3%; if the home side has played and traveled the prior night, their chance of winning drops even further, to 52.8% (down 2.3% from the average). When the visitors are playing their second game in two nights, though, the home team’s win probability goes up to 57.9%, or 2.8% above the average, if they’re rested.

I’ve also presented some comparisons involving relative days’ rest, which are not limited to back-to-backs; the picture here is slightly less clear. A home team with an additional day of rest has a 57% win probability; if they have 2 additional days of rest, they have a 58.7% chance of winning. When playing a road team with 1 more day of rest, their win probability goes down to 53.2%. However, the home side still has a 55.3% win probability when playing a road team with 2 additional days’ rest, and their win probability is actually below-average (53.1%) when they have three or more days of rest. A road team with three or more additional rest days than the home side has the best chance of winning than in any other scenario (47.8%). The sample sizes in the bottom three rows of the table are a good deal smaller than those involved in the other analyses, so it’s possible that these estimates aren’t reliable. There may be some reason why we see these results (maybe road teams benefit more from long layoffs than home teams?), but I’d have to be convinced that there’s something more than a small-samples artifact at work.

To summarize, it looks like having an easier NHL travel schedule carries a significant downside of having to play more back-to-back games (unless you’re the Rangers, in which case you apparently don’t have to worry about either issue). Insofar as the most common scenario in a back-to-back involves a rested home squad, this may explain another piece of the consistent edge that home teams enjoy in the NHL. And more to the point, it looks as though having more back-to-backs might actually be worse than traveling more. Many teams that logged over 42,000 road miles this past season, like Boston, Anaheim, Colorado, San Jose, and Los Angeles, didn’t seem to suffer much from it, and you have to go all the way back to 2009-10 to find a President’s Trophy winner with an easy travel schedule. And though it stands to reason that teams with heavier travel may have longer road trips, it’s not clear that the relative fatigue has a consistent effect on win probabilities. But back-to-back games are pretty much a bad proposition no matter how you look at them, especially if you play them on the road.

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Hockey Analytics in 2014

Now that the day-to-day grind of the 2013-14 NHL season is over, and attentions are shifting to things like the draft, coaching hires, and free agency, I’ve been thinking a bit about the future of analytics in hockey. Recently, Jonathan Willis published an interesting article over at Edmonton Journal, making the case that data aren’t driving decisions by NHL teams as much as some analysts would like to believe. And certainly, the examples he cites support his point. San Jose’s reputation as a forward-thinking, analytically-minded team has taken on some water recently with the inexplicable signing of Mike Brown to a multi-year deal, the rumored trades of Joe Thornton and Patrick Marleau, and an interesting exchange (via Twitter) between Sharks beat reporter Kevin Kurz and Derek from Fear the Fin suggesting that the team doesn’t realize they have the best shot-creating power play in the NHL. Other examples of this phenomenon include:

  • In 2011, Edmonton started up an internal analytics shop to, as David Staples says, “help the Oilers enter in to the new world of sports analytics”, and comments from GM Craig MacTavish and coach Dallas Eakins suggest that both have an appreciation for the value of numbers. Yet, as Willis notes, moves like claiming Luke Gazdic off waivers, playing Justin Schultz in a top-pairing role, and overpaying for mediocre veterans like Andrew Ference and Nikita Nikitin – not to mention the team’s disastrous defensive play and on-ice results – don’t suggest a team making much use of numbers to guide its decisions.
  • The Pittsburgh Penguins used the work of the Sports Analytics Institute in making the 2011 decision to trade for star winger James Neal, and, in the words of Director of Player Personnel Dan MacKinnon, “I don’t think we’ve made an impact decision since then without consulting the analytics”. The value of a shot-quality analysis from a model that SAI actually refers to as a “black box” is, of course, open to question, but more importantly, it’s hard to believe the Penguins consulted the analytics when trading two draft picks for one of the league’s worst defensemen, trading a top D prospect to rent a declining winger for a couple months in 2013, signing a badly declining Rob Scuderi to a four-year contract, signing fourth-liner Craig Adams to multiple deals, firing the winningest head coach in franchise history after a 107-point season, or trading Neal to Nashville this week.
  • Stats-savvy Toronto fans were thrilled at the suggestion that new team President Brendan Shanahan was willing to embrace possession metrics in charting a direction for the team. For the time being, I’ll reserve judgment, but the decision to retain coach Randy Carlyle and GM Dave Nonis, the faces of the organization’s notorious hostility to numbers, is not a good sign. Nor is the acquisition of Roman Polak from St. Louis.
  • The Tampa Bay Lightning employ Michael Peterson, a full-time statistical analyst who assists the front office and coaching staff in making all sorts of decisions. One imagines that Peterson isn’t too happy with the six-year deal the team just gave Ryan Callahan.
  • New Flyers GM Ron Hextall reportedly views analytics as a “huge part of what we do going forward”. This sounds great, but it’s a bit at odds with the notion that Andrew MacDonald is “going to be a big part of this team moving forward”, and with the trade of a useful player in Scott Hartnell for a . . . less than useful one in R.J. Umberger.

The point of this isn’t to be discouraging or contrarian, but rather to suggest that the adoption of analytic thinking and results by NHL teams is still in its early stages. It’s certainly fair to say that the profile of this work is higher now than it’s ever been before. Thanks in no small part to the Maple Leafs’ wretched 2013-14 season, as well as the popularity of Moneyball (book or film) and the work of people like James Mirtle, Neil Greenberg, and Sean McIndoe (to name just a few), it’s hard to avoid encountering advanced stats in even mainstream hockey writing, and in some cases (the Kings and Sabres come to mind), local TV broadcasts are bringing possession numbers into their coverage. Willis’s point, which I agree with, is that none of this means that teams are actually leveraging the numbers to make decisions. But we do appear to have reached the point where teams can’t publicly brush the numbers aside the way Nonis and Carlyle did a year ago. Coaches and front-office officials who don’t have at least a vaguely positive answer (like Hextall’s, for example) to questions about their use of analytics risk being painted as behind the curve, or (as we saw in Toronto) having their inattention to statistics become a story on its own.

Still, it appears that much of the NHL’s interactions with the advanced-stats community these days involves using numbers to validate pre-existing notions or observations. While it’s not a bad thing for analysts to be involved in the decision-making calculus of NHL teams, even peripherally, it’s hard to imagine unlocking the potential of analytics in such a limited role. The real value of this work lies in using numbers to challenge popular assumptions about the game, and using those insights to build successful teams in less conventional ways. And obviously, this isn’t going to happen if the numbers are only used (in effect) to justify choices after they’ve been made. Much has been made of the reported hiring of Sunny Mehta, a contributor at Vic Ferrari’s old site, as New Jersey’s Director of Hockey Analytics; while he may be an excellent choice for the position, the real question is the level of influence he’ll have in an organization that Lou Lamoriello has ruled (with something of an iron fist) since the late 1980s. This article from Mirtle suggests that Lamoriello isn’t entirely enthusiastic about embracing the insights the numbers can offer, which is potentially a critical problem.

None of this, of course, is cause for pessimism. At this point, it’s simply a matter of trusting that bigger opportunities for analytics will come with time. It may not happen in the league’s more prominent and wealthy markets, but eventually, teams that are desperate to win will start to look for new ways to gain an edge on the competition. In the meantime, some things analysts can do to keep this process moving forward are as follows:

  • Even though data analysis can be conducted without attention to basic principles of sound statistics, remember that it isn’t a good idea. While the proliferation of analysis software and web-based data sources has undoubtedly been a boon to researchers, one downside is that people without a grasp of concepts like statistical power, sampling error, and non-causal correlation can easily crunch numbers and disseminate the work online. But a big reason why decision-makers in NHL teams are reluctant to trust the work of analysts is that they don’t have the training needed to critique statistical work; from their perspective, it’s easier to ignore it than risk making a bad decision based on shoddy analysis. Put another way, analysts need to remember that the burden is on them to prove the value of what they do, and that starts with producing work that’s valid and reliable.
  • Don’t give bad advice. Most hockey analysts are fans of the sport as well, and few fans can resist the pull of simplistic narratives or emotional reactions to short-term results (i.e., your favorite team losing in the playoffs). The problem with this is that many of the mistakes of mismanaged teams come down to focusing on short-term results at the expense of seeing a process through. One of the biggest favors the stats community could do for teams would be convincing them that there’s no magical formula to winning in the playoffs, beyond assembling a strong team and hoping the bounces go their way. More generally, tempting as it might be to gravitate towards emotionally satisfying conclusions, and to pick and choose data points to fit them, in the long run this does the cause of hockey analytics no favors.
  • Take advantage of the community of analysts around you. This is pretty self-explanatory: it’s a lot easier to do high-quality work, and to generate better ideas, when you can bounce ideas off of others in the field. While different analysts obviously don’t agree on everything, and have different preferences when it comes to methodology, it’s rarely the case that good work is produced in isolation. Fortunately, thanks to Twitter, jumping into the conversations of analysts and getting the feedback you need has never been easier.
  • Remember that the future is very bright. Hockey analytics have taken a big step forward this season, and with analysts like Corey Sznajder, Eric Tulsky, and Chris Boyle spearheading efforts to produce new data sources based on tracking events by hand, it’s only going to get better. These data sources, as well as ubiquitous video, will make it increasingly possible to connect patterns in the data to specific plays on the ice; this will allow analytics to become more prescriptive, and to incorporate a new dimension of face validity. It might be a long time before NHL GMs are using hockey stats to run their teams, but there’s never been a better time to be involved in them.
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How Did the Puck Prediction Model Do in 2013-14?

The 2013-14 NHL season is in the books, and now that we’re wrapping up for the offseason, it’s time for the big reveal. Those of you who have been reading Puck Prediction since the early days know that this past season was devoted to a prospective trial of NHL game prediction. Last summer, I pulled together game-level data from the eight seasons between 2005-06 and 2012-13, breaking down information on shot differential, event rates, and shooting and save percentages to develop an algorithm for predicting games. In order to provide a good comparison, I decided to track “the wisdom of the crowd” via the gambling markets as well. If you read the site during the regular season, you no doubt saw my daily game predictions against those of the gambling markets (via the Odds Shark website). I took interim looks at the model’s performance at the quarter-season, mid-season, and three-quarter-season marks; now, it’s time to look at how things shook out after 1,230 games.

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

First, I promised a detailed description of my algorithm for picking games, and here it is. Throughout the season, I kept track of each team’s all-situation shooting and save percentages, their average all-situation shots-for and shots-against per game (added together to create a rough event rate), and their average all-situation per-game shot differential; coming into each game, eight total values (these four variables for the two teams in question) were involved in making the prediction. For season-opening games, the model used teams’ season-ending values from the prior campaign. These values were then used to calculate an expected goal differential for the game, as follows:

PP model_eqn

Unpacking this a little bit, the model assumes that each team’s Sh% in game i will be a 50% weighted average of their Sh% in games 1 through i - 1 and (1 – their opponent’s team Sv% in games 1 through i – 1). To estimate the number of shots for each team, we assume the total number of shots in the game will be the higher of each team’s average event rate in games 1 through i – 1 (this is more consistent with the data). We then take Team A’s average shot differential and subtract Team B’s differential from it. This difference is then added to the event rate for Team A, and subtracted from the event rate for Team B; halving each of these numbers gives an estimate of total shots for and against. If Team A enters the game with a higher shot differential than Team B, the implication is that they’ll control the majority of the shots in the game, while the opposite is true if B enters the game with a better differential. The Puck Prediction model picked games as follows:

1. If one team has an expected goal differential of 0.3 or higher, pick that team.
2. If neither team has an expected goal differential of at least 0.3 but one team has an expected shot differential of 9 or higher, pick that team.
3. If neither team has an expected goal differential of at least 0.3 or an expected shot differential of at least 9, pick the home team.

As was the case at each interim analysis, and as I anticipated here, this method of picking games was statistically no more or less accurate than the gambling markets in the 2013-14 season. With a record of 728-502, Vegas was 59.2% accurate when it came to picking the NHL regular season; my model was 58.7% accurate, with a nearly identical record of 722-508. This difference was not statistically significant (t=-0.493, p=0.622). I picked against Vegas 148 times this season, and was correct 71 times (48%). The gambling markets were slightly more accurate when picking road teams (59.1% vs. 57.5%) and when picking teams with the greater shot differential entering the game (61.1% vs. 60.0%). When it came to specific teams, Puck Prediction was more accurate than Vegas in games involving Boston (69.5% vs. 67.1%), Buffalo (73.2% vs. 70.7%), Colorado (58.5% vs. 56.1%), Montreal (56.1% vs. 53.7%), New Jersey (58.5% vs. 54.9%), Philadelphia (65.9% vs. 61.0%), and Toronto (64.6% vs. 59.8%). The gambling markets were better when it came to games involving Chicago (59.8% vs. 56.1%), Dallas (59.8% vs. 54.9%), Edmonton (63.4% vs. 59.8%), Minnesota (62.2% vs. 50.0%), Nashville (56.1% vs. 50.0%), the Islanders (52.4% vs. 48.8%), Ottawa (51.2% vs. 48.8%), Vancouver (69.5% vs. 65.9%), and Washington (59.8% vs. 54.9%).

Summarizing a project of this magnitude isn’t easy, but a few things are worth noting. The most obvious is that, as I pointed out in my earlier piece, beating the gambling markets consistently is not easy. The fact that my model’s picks agreed with the market 88% of the time should tell you that, by and large, Vegas predictions are not easy to disagree with. Looking at the 148 games for which our predictions differed, 98 of them were “obvious” picks; that is, the expected goal differential was 0.3 or greater, or the expected shot differential was 9 or greater. In those 98 games, Puck Prediction had a record of 53-45 (54.1%), while Vegas managed 45-53 (45.9%). On the other hand, in the 50 “toss-up” games where the pick came down (for me) to home-ice advantage, the model got crushed, with just 36% accuracy (18-32) compared to Vegas (32-18). At 53.7%, home-ice advantage was slightly less reliable in 2013-14 compared to prior NHL seasons, and it looks as though my model was particularly unlucky when I went against Vegas to rely on it. Another thing worth thinking about is the team-specific differences in model accuracy. Given the different approaches NHL teams take to winning games, it’s fair to wonder whether team-specific predictions could offer an improvement over a one-size-fits-all method.

All in all, though, this experience has definitely taught me a lot about the limits of prediction in NHL hockey, as well as the difficulty of beating the gambling markets. I can’t promise I’ll do another single-game prediction project again next season, but it’s been fun.

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Three Wins Short: Looking Back at the New York Rangers

Here at Puck Prediction, we’re closing the book on 2013-14, and as part of that, today brings the last of my team season recaps. The last team on our list is the New York Rangers, who advanced to their first Stanley Cup Final in 20 years this season, but lost to the Kings in five games.

Image credit: Flickr user Anna Enriquez. Use of this image does not imply endorsement.

Throughout most of Henrik Lundqvist’s accomplished career in Manhattan, the Rangers have become known for underachieving in front of him, especially at playoff time. The 2007-08 Rangers were one of the best possession teams of the past seven seasons, yet in the playoffs, they lost the possession battle to a defensively atrocious Pittsburgh team in the course of a five-game loss in the second round. The season after that, they were crushed territorially and blew a 3-1 series lead in the first round against Washington. In 2011-12, New York was the best regular-season team in the Eastern Conference, but their poor fundamentals caught up to them in the postseason, as they struggled to put away two weak teams in the opening rounds before succumbing to a mediocre New Jersey squad in the Conference Final. As such, perhaps it’s fitting that they made their deepest playoff run of the Lundqvist era in a season in which the Swedish goaltender got off to an exceedingly poor start. Renovations at Madison Square Garden meant that the Rangers didn’t play their first home game until October 28. The Rangers won just three times on the long road spell before that; the losses included ugly 9-2 and 6-0 shellackings from the Sharks and Ducks, respectively, and a 4-0 loss to New Jersey. Through these nine games, New York’s Fenwick Close was a miserable 46.6%, and their PDO was an unsustainably low 0.931 as well, with Rangers goaltending serving up a miserable 0.897 Sv% at even strength. At that point, it was fair to wonder whether new head coach Alain Vigneault would have his job for long. After dropping their home opener, however, they reeled off six wins in seven games, and their possession game quickly began to turn around. From early November on, the Rangers would play elite-caliber possession hockey (54.3% Fenwick Close), and Lundqvist and rookie Cam Talbot would give them 0.935 play in goal. They remained one of the coldest-shooting teams in the NHL in 2013-14, scoring on just 6.7% of their 5-on-5 shots. Rick Nash led the team in goal-scoring, potting 26 in 65 games; at 5-on-5, Nash was New York’s highest volume shooter, and scored at a healthy 9.3% clip. Other high-volume shooters on the team, however, included Derek Stepan (7.9%), Benoit Pouliot (6.7%), Brian Boyle (4.2%), and Ryan McDonagh (5.0%). Still, the Rangers were one of the most productive offenses in the league in shot-creation terms, and as such were middle-of-the-road in goal-scoring, while a steady defense and brilliant play in goal made them the fourth-stingiest squad in goals-against.

In the postseason, the Rangers offered up two thrilling seven-game series on their way to the Conference Finals. Playing Philadelphia in the playoffs for the first time in years, New York controlled possession at even strength as expected, and Lundqvist handily outplayed the duo of Steve Mason and Ray Emery. Nevertheless, a deadly Flyers power play kept them in the series, and allowed them to stretch it to seven games, where New York ultimately prevailed by a 2-1 score. Facing Pittsburgh in the second round, the Rangers struggled in possession against a newly healthy Penguins defense corps, and were shut out twice en route to a 1-3 series deficit. Then Lundqvist gave the team three splendid efforts, and they clawed back to win another 2-1 Game 7, this time on the road. Considering that that series has led to chaos at the top of one of the NHL’s most successful post-lockout franchises, perhaps it’s worth pausing to consider the magnitude of New York’s comeback. Thanks to Montreal’s second-round upset of the President’s Trophy-winning Bruins, the Rangers faced a far easier opponent in the Conference Finals. When Carey Price was hurt during a 7-2 blowout in Game 1, this task got even easier, and with a 1-0 victory in Game 6, New York was back in the Stanley Cup Final for the first time since winning it in 1994. In the final against Los Angeles, the Rangers had their chances, blowing multiple-goal leads and losing in overtime in Games 1 and 2 on the road, then outshooting LA 32-15 in a 3-0 loss in Game 3. They would take Game 4, but back in southern California, they would drop yet another overtime decision, and with it their chance at the Cup.

Despite the sour conclusion to their season, it’s hard not to view 2013-14 as a success for the Rangers. Vigneault’s fresh voice and fast-paced style appeared to grow on his roster as the season went along. Players like Nash, Stepan, Chris Kreider, and McDonagh excelled in two-way roles this season, and New York is one of the NHL’s younger teams, particularly after the buyout of Brad Richards. This could be an interesting offseason for the Rangers, with key contributors like Anton Stralman, Kreider, Mats Zuccarello, and Derick Brassard due new contracts, and several others (e.g., Marc Staal, Stepan, Carl Hagelin) entering contract years; indeed, as of today, Nash, Lundqvist, McDonagh, Dan Girardi, and Kevin Klein are the only Rangers under contract beyond next season. Of course, in the wake of the Richards buyout, the Rangers have loads of cap space to work with, and attracting players to an Original Six market in Manhattan never seems to be a problem. This team could look at lot different come Opening Night this October, but there’s a good chance they’ll be one of the NHL’s best once again.

Other 2013-14 season recaps: Buffalo, Florida and Edmonton, Calgary, Winnipeg and the NY Islanders, Vancouver, Toronto, Ottawa, New Jersey, Washington, Carolina, Nashville, and Phoenix, Tampa Bay, Detroit, St. Louis, Dallas and Columbus, Philadelphia, Colorado, San Jose, Pittsburgh, Boston, Minnesota and Anaheim, Los Angeles, Montreal, and Chicago.

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Don’t Change a Thing: Looking Back at the Chicago Blackhawks in 2013-14

As part of Puck Prediction’s wrap-up of the 2013-14 NHL season, I’m taking a final look back at the last teams left standing this season: the Conference Finalists. Today, it’s time to look at a team that came five wins short of being the first in the salary-cap era to win back-to-back Stanley Cups: the Chicago Blackhawks.

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

When you write about all 30 teams in the NHL, you gradually discover that some teams are just more interesting than others. Some teams (e.g., Toronto, New Jersey) are bad, but in interesting ways; some teams (e.g., Colorado, Montreal) succeed even when the numbers suggest they shouldn’t; and with some teams (e.g., San Jose, St. Louis, Pittsburgh) there’s a pathos that comes with regular-season excellence followed by playoff disappointment. Other teams, however, just aren’t as compelling. Usually this is due to the combination of bad results and limited on-ice talent. And then there are the Chicago Blackhawks, a team whose sustained excellence is so predictable that, in looking back on yet another superb season in Chicago, it’s hard to find much to write about.

Since appointing Joel Quenneville head coach prior to the 2008-09 season, and bringing the legendary Scotty Bowman into the front office along with his son Stan, the Hawks have arguably become the NHL’s best-run franchise. In 2008-09, the Hawks ended a lengthy spell of futility, racking up 104 points and winning their first playoff rounds since 1996, making it to the Western Conference Final before succumbing to the juggernaut Red Wings. Tellingly, in Quenneville’s first year, the Blackhawks achieved a Score-Adjusted Fenwick differential of 55.46%, the ninth-highest SAF in the Behind the Net era. Entering 2009-10 with the blockbuster signing of free agent Marian Hossa, the Hawks followed this strong campaign with an even better one. Chicago’s SAF of 58.83% that season was absolutely astounding (no team has matched it since), and with the early upsets of key challengers in Washington and Pittsburgh, the Hawks cruised to the franchise’s first Stanley Cup title since 1961. Salary cap pressures forced Chicago to cut loose key contributors like Dustin Byfuglien, Andrew Ladd, and Kris Versteeg, and led them to part ways with goalie Antti Niemi, but the core group stayed intact. For the next two seasons, Chicago played well in the regular campaign and posted outstanding possession numbers, yet lost twice in the first round of the postseason. For some teams, this would have led to panic. But the Hawks simply stayed the course and rebuilt their depth, and in 2012-13, they dominated the NHL like no team since the 2007-08 Red Wings. Along with pacing the league in every measure of possession, Chicago’s season was half over before they suffered their first regulation loss, and they achieved the President’s Trophy-Stanley Cup double, becoming the first team in the cap era to win multiple Cups.

Little changed for the Hawks in 2013-14. They were once again one of the NHL’s elite possession teams; with a Score-Adjusted Fenwick of 55.71%, they are the only team since 2007-08 to post four seasons with a SAF above 55%. Paced by 30-goal seasons from Hossa and Patrick Sharp (along with 57 goals from Patrick Kane and Jonathan Toews), Chicago ranked second in the NHL in goal-scoring this season, just two behind Anaheim for the league lead. They were a middling team when it came to goals-against, mostly due to a poor penalty kill and troubles in goal. Corey Crawford was a solid 0.927 at even strength in 59 games, but backup Antti Raanta had a dreadful 0.895 season; of course, Chicago was able to mitigate these struggles by posting elite shot-prevention numbers at 5-on-5 (26.1 shots against and 47.1 Corsi against per 60 minutes). The team’s form dipped somewhat in January, when they lost nine games in a stretch of 14, but overall the Hawks were remarkably consistent throughout the campaign, and finished with 107 points. Nevertheless, the stunning, PDO-driven season of the Avalanche and the quality (and torrid shooting) of St. Louis dropped Chicago to third place in the Central Division, and sent them on the road to start the playoffs. Their title defense did not start off well, as they blew two late leads to go down 0-2 against the Blues. Nevertheless, they turned the tables on St. Louis, shutting them out in Game 3 and winning in overtime after a late tying goal in Game 4. After a tight-checking Game 5 went to overtime, a bad line change by the Blues gave Toews a breakaway that sealed a 3-2 series advantage; back at home, they blew out St. Louis to advance to the second round. Facing Minnesota in the second round, they terrorized goalie Ilya Bryzgalov to take a 2-0 series lead, but tremendous defensive play from the Wild allowed the underdogs to even the series at 2-2. The Hawks ground out a tough win in Game 5, and in Game 6, two fortunate bounces allowed them to return to the Western Conference Final. Fans were thrilled at the prospects of a rematch of the 2013 WCF against Los Angeles, and if anything the series surpassed expectations: the two teams played breath-taking, fast-paced hockey, and Chicago made a spirited comeback to force Game 7 after being down 1-3. The Hawks took a 4-3 lead into the third period of the deciding game, but an Alec Martinez goal in overtime brought finished Chicago’s season just short of returning to the Cup Final.

Obviously, after coming within 8 minutes of the Stanley Cup Final and racking up 107 points in the regular season, only a fool would consider 2013-14 anything other than a rousing success for the Blackhawks. And unlike other teams (like San Jose or Pittsburgh, for example), the Hawks are likely to stick with what’s worked so well for them. Chicago is pretty tight against the cap, but with 11 forwards and 7 defensemen under contract for next season, their focus will probably be on the following season: the rising cap will help, but the Blackhawks have Kane, Toews, Brandon Saad, Marcus Kruger, Johnny Oduya and Nick Leddy all entering contract years in 2014-15. Uninspired work from free agent goaltenders Raanta and Nikolai Khabibulin this season could see both move on, in which case the Hawks will need to identify a low-cost backup for Crawford. Plodding center Michal Handzus is also unlikely to return. Otherwise, Chicago is likely to spend the offseason and next season working promising youngsters like Teuvo Teravainen and David Rundblad into bigger roles, while looking to move some of their veterans for salary relief. This will doubtless be tricky, but if any organization has shown itself capable of managing significant roster challenges in the cap era, it’s this one.

Other season wrap-up posts: Buffalo, Florida and Edmonton, Calgary, Winnipeg and the NY Islanders, Vancouver, Toronto, Ottawa, New Jersey, Washington, Carolina, Nashville, and Phoenix, Tampa Bay, Detroit, St. Louis, Dallas and Columbus, Philadelphia, Colorado, San Jose, Pittsburgh, Boston, Minnesota and Anaheim, Los Angeles, and Montreal.

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Six Wins Short: Looking Back at the Montreal Canadiens in 2013-14

The 2013-14 NHL season is in the books, and here at Puck Prediction, I’m wrapping up the last loose ends. Today, we’ll be taking a look back at the season of the Montreal Canadiens, who made an unlikely run to the Eastern Conference Final before falling to the Rangers in six games.

Image credit: Flickr user Andre Theriault. Use of this image does not imply endorsement.

It’s fitting, I suppose, that the Canadiens surprised everyone by going on a deep playoff run, because nothing about their season was easy to anticipate. In the 2012-13 season, the Habs rebounded solidly from a lackluster 2011-12. Under new head coach Michel Therrien, they finished with the fourth-best record in the NHL; what’s more, they played tremendous possession hockey, with a 53.6% Fenwick Close. They bowed out of the postseason early thanks to a red-hot Craig Anderson, but given their strong possession game, I picked them to make the playoffs comfortably in 2013-14. Of course, had I known in the offseason what I know now about high-event hockey, I might have been a little less confident: the Canadiens played the 2012-13 season at a pace of over 110 Corsi events per 60 minutes at even strength. Still, nothing about their underlying defensive numbers in the shortened season would have suggested what was to come this season.

And, initially, the Habs appeared to pick up where they’d left off: after a month of the 2013-14 season, Montreal had a 52.3% Fenwick Close. They were, however, off to a middling 8-6-0 start. Then, two unexpected things happened: their possession game began to deteriorate, and they began to win games. From mid-November to mid-December, Montreal reeled off 11 wins in 14 games and rocketed back up the standings, even as their Fenwick Close sank to 49.2% by December 10. Much of the credit for this success goes to Carey Price, whose save percentage at 5-on-5 was over 0.944 during these games. More generally, Price rebounded well from a poor finish in 2013, and was undoubtedly Montreal’s most valuable player in 2013-14: with a 0.934 Sv% in 59 games this season, his omission from the list of Vezina finalists was a bit surprising. Much like Semyon Varlamov in Colorado, Price’s superb play disguised his team’s defensive troubles: after being one of the better shot-prevention teams in the NHL in 2012-13, the Habs turned into one its worst this season, allowing over 30 shots and 60 Corsi attempts per 60 even-strength minutes. As the winter wore on, Montreal’s possession game got steadily worse, bottoming out at a 47.4% Fenwick Close in late February. Heading into March, the Habs were treading water in the standings, and essentially praying that their goaltending would hold out long enough for them to make the playoffs. Then, beginning with a thrilling overtime win over Ottawa on March 15, the Canadiens hit a well-timed winning streak, taking 10 of their next 12 and securing a postseason berth in the Atlantic.

Heading into the playoffs with the ninth-worst possession numbers in the league (i.e., 48.4% Fenwick Close) and no home-ice advantage, few observers gave the Habs much of a chance. Montreal, however, was not done surprising us. Though their first-round opponent, the Tampa Bay Lightning, was a top-10 possession team, one stroke of good fortune came to the Canadiens almost immediately, as the Bolts’ Vezina-nominated goaltender, Ben Bishop, was lost to injury. That they were able to beat a team backstopped by the unimpressive Anders Lindback wasn’t remarkable; that they did so while dominating the Lightning in possession, though, was eye-opening. In the course of sweeping Tampa Bay, Montreal had a score-adjusted Fenwick of 57.5%. They then went on to face their long-time rivals, the Boston Bruins. In that second-round series, they delivered the biggest shock of the postseason, yet again riding Price’s brilliance and upsetting the President’s Trophy winners in seven games. In their first Conference Final since 2010, the Canadiens’ luck turned abruptly sour, as Price was hurt in a series-opening blowout, and did not play again against New York. Rookie Dustin Tokarski stepped in admirably in five games, but was bested at the other end by Henrik Lundqvist. More generally, the Rangers’ shot advantage and a suddenly ineffective Habs power play spelled the end for the Canadiens, who were eliminated in six games.

Taking the short view, it’s hard to see 2013-14 as anything other than a success for Therrien and the Canadiens. But looking ahead, there is a pessimistic case that’s worth considering. Most alarming, of course, is the deterioration of the team’s defense and possession game this season. Part of this change appears to be related to personnel: before finding himself a healthy scratch in the postseason, lumbering defenseman Douglas Murray was obliterated in possession despite playing the softest minutes on the team. But it was also due in part to Therrien’s deployment decisions: young players like Alex Galchenyuk, Lars Eller, and David Desharnais were given tougher roles this season, and didn’t crush them the way they did in 2012-13, and two-way players like Brian Gionta and Tomas Plekanec struggled through the difficult minutes Therrien gave them. Many will view this season as a challenging one for 2013 Norris winner P.K. Subban, whose possession numbers dipped in a less sheltered role this year; still, with 53 points in 82 games and a Corsi Rel of 5.1%, Subban handled the challenge very well. But it’s worth remembering that Price is a career 0.925 goalie at evens; if Montreal can’t find a way to cut the shots he’s facing, a regression back to his career norm in 2014-15 could hit them hard. The onus of tightening the Habs defense will fall to Therrien, who has been given a lengthy contract extension, but given his track record, it’s fair to wonder whether he’s the right coach for that task.

The offseason for Montreal will be highlighted, of course, by the $64M (or, likely, a much higher number) question: what sort of deal will Subban see as a restricted free agent? The Canadiens have quite a bit of cap space to work with, so some upgrades at their depth positions aren’t out of the question. Gionta and defenseman Andrei Markov are both 35 and UFAs; it’s hard to imagine the Habs not making an effort to retain both of them, even if their roles are reduced going forward. Winger Thomas Vanek, acquired at the trade deadline from the Islanders, played decently well for the Habs, but is likely to attract intense interest on the free-agent market; at 30, any team that signs Vanek is likely to end up paying for his declining years. Eller is an RFA, but will almost certainly be retained; the Habs might also work on extensions for a number of quality players heading into contract years, including Galchenyuk, Brendan Gallagher, and Nathan Beaulieu. But the priority is clearly Subban. The young blueliner hasn’t always had the warmest relationship with his coach or the hockey media, but he’s very clearly the face of the future for the Canadiens.

Other season wrap-up posts: Buffalo, Florida and Edmonton, Calgary, Winnipeg and the NY Islanders, Vancouver, Toronto, Ottawa, New Jersey, Washington, Carolina, Nashville, and Phoenix, Tampa Bay, Detroit, St. Louis, Dallas and Columbus, Philadelphia, Colorado, San Jose, Pittsburgh, Boston, Minnesota and Anaheim, and Los Angeles.

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Last Team Standing: Looking Back at the Los Angeles Kings in 2013-14

Now that the 2013-14 NHL season is officially in the books, there are a few loose ends to wrap up here at Puck Prediction. One part of this involves a last look back at the seasons of the four Conference Finalists. In recognition of their achievement in being the last team standing this season, I’m going out of order; today, I’ll be writing about the 2014 Stanley Cup champion Los Angeles Kings.

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

The week or so after the Cup is awarded is typically the time when we see lots of articles describing how the winner serves as a model for building future champions. In 2009, the key to winning the Cup was depth at center; in 2011, it was size and toughness. This year, fresh off of correctly predicting the Toronto Maple Leafs’ collapse, many hockey analysts are pointing to the Kings’ league-best Fenwick differential and positing a strong possession game as the reason for a parade in Los Angeles. One statistic I’m seeing bandied about a lot is that, of the five teams with a regular-season Score-Adjusted Fenwick over 56% since 2007-08, four (this year’s Kings, the 2007-08 Red Wings, and the 2009-10 and 2012-13 Blackhawks) won the Cup, while the fifth (the 2008-09 Red Wings) came within a game of doing so. This sounds impressive until you remember that drawing broad conclusions based on five teams and one statistic usually isn’t a good idea. If we lower that SAF threshold to 55%, we’re still focused on outstanding possession teams, and I can’t be convinced that a 56% team is meaningfully better in possession than a 55% team. But this gives us a sample of 17 squads, and a much murkier picture. This set of 17 includes the five teams mentioned above, but it also includes the 2008-09 and 2013-14 Blackhawks (lost in the Western Conference Final), the 2012-13 Kings (WCF loss), the 2007-08, 2008-09 and 2013-14 Sharks (2nd-round, 1st-round and 1st-round losses, respectively), the 2007-08 and 2008-09 Capitals (1st-round and 2nd-round losses), the 2007-08 Rangers (2nd-round loss), the 2011-12 Penguins (1st-round loss), the 2011-12 Red Wings (1st-round loss), and the 2012-13 Devils (failed to make the playoffs). Even if we discount 55% teams eliminated by teams with better possession numbers, two of every three teams with a SAF of 55% or higher has failed to win a Cup. Lower the threshold to 54% and the picture gets even worse. The point being that it helps to be a good team if you want to win the Stanley Cup, but in any year there are plenty of excellent teams in the NHL, only one of whom (maybe) wins it all.

Rather than being a magical key explaining their postseason success, LA’s superb possession game had its biggest impact in the regular season: by consistently pushing the math of goals-for and goals-against in their favor, puck control enabled the Kings to withstand some extended spells of very cold shooting, as well as the variability in goaltender play that every team experiences. Their possession game was remarkably consistent throughout the regular season: in 82 games, LA controlled less than 50% of close-score Fenwick events just 18 times. A month into the season, their Fenwick Close sat at 56.7%, and would stay there pretty much the rest of the way. And through the first part of the campaign, their results reflected this consistency. From Opening Night until Christmas, the Kings won 25 of their first 38 games, and lost consecutive regulation contests only once. They achieved much of this success despite an injury that cost starting goalie Jonathan Quick almost seven weeks between November and January. Partly, this is due to the trememdous work of Ben Scrivens (0.942 Sv% at even strength before his trade to Edmonton) and rookie Martin Jones (0.947). Indeed, as of December 21, the Kings enjoyed a 0.947 team Sv% and a 1.022 PDO, which explains a lot about how difficult they were to beat. But partly it was due to the team’s tremendous effectiveness in limited chances against; LA’s 25 shots and 46.6 Corsi attempts against per 60 5-on-5 minutes were tops in the Western Conference, and second league-wide only to New Jersey and their narcoleptic home scorer.

Nevertheless, from December 23 until the Olympic break, the Kings hit a rough patch that saw them win just six times in 22 contests. Their goaltending during this stretch was a very healthy 0.936 at evens, but their shooting luck utterly vanished: in these games, LA scored on just 3.3% of their 5-on-5 shots. Combined with a lackluster power play, this extended spell of cold shooting ended their chances of challenging for the Pacific Division title. Upon returning from Sochi, their luck began turning around, and with the deadline addition of Marian Gaborik, the Kings shot over 8% and won 15 times to finish out the campaign. Nevertheless, only Buffalo finished 2013-14 with a lower even-strength Sh% than LA’s 6.6%, and only four teams (none of whom made the postseason) scored fewer than the Kings’ 198 goals.

All of which makes their run to the Cup, and the manner in which it occurred, look even more unlikely; if anything, LA’s 2014 championship should serve as a reminder of how unpredictable hockey can be in short series. Facing another strong puck-control team in round one, and without the benefit of home-ice advantage, the Kings’ possession numbers didn’t help them against San Jose. By Fenwick or Corsi differential, possession in the series was essentially a draw; by 2-period SF%, the Sharks controlled almost 53% of the possession (obviously, the numbers are noisy in such small samples, so none of them is necessarily “correct”). Of course, we all know the real story of that series: behind 15.3% shooting and 0.921 goaltending, San Jose leapt out to a 3-0 lead before the PDO tables abruptly turned. In the final four games of the series, LA shot 10.1% and got 0.957 play from Quick, and a historic comeback was completed. A somewhat similar story played out in the next round, where the Kings faced the Anaheim Ducks for the first time in a postseason series. As expected, LA controlled the bulk of the possession; more surprising, however, is that they got the better of the PDO battle against the NHL’s highest-scoring team in 2013-14. The Kings were very fortunate to take Games 1 and 2 in Anaheim, tying the series opener late in regulation on a fluky goal from Gaborik before winning in overtime, and taking the second contest despite being outshot 37-17. Interestingly, most of LA’s possession advantage in the series came from their play in Games 3-5. All of which they lost. Their possession advantage in their two elimination games against the Ducks was far more modest, but a team that was snakebitten all throughout the regular season scored on 15% of 5-on-5 shots, and got 0.938 play from Quick. With that burst of PDO, the Kings were through to the Conference Finals, and a rematch with the team that eliminated them in 2013. To call the Hawks-Kings series a classic is, if anything, an understatement, but unlike their 2013 meeting, puck luck didn’t desert LA this time around. As in round one, the Kings played to a draw in puck possession over seven games with Chicago. Quick was inconsistent throughout the series, and was a big reason that a 3-1 advantage turned into a Game 7 overtime for LA. The difference, once again was shooting luck. Keeping in mind, again, that LA had the second-worst Sh% in the league this season, the Kings shot 10.4% against the Blackhawks; in a tightly-matched series, that was the difference. After three seven-game series in the West playoffs, a five-game series against the Rangers probably felt like a relief. The Cup Final offered a few more unlikely surprises, such as Quick outdueling Henrik Lundqvist. Similar to the Anaheim series, the Kings’ overall possession advantage was driven to some extent by their play in the game they lost (Game 4 was a 2-1 New York win despite LA’s 41-19 shot advantage). Three of the Kings’ victories against the Rangers required 14 periods of hockey to sort out; in the fourth, they were outshot 32-15. Nevertheless, they played excellent hockey throughout the Final, and got goals when they needed them.

As far as the immediate future, the Kings are a cap team, which means that they’ll have decisions to make this offseason. Their two highest scorers, Anze Kopitar and Jeff Carter, are under contract for a while; unfortunately, so are Dustin Brown and Mike Richards, who combined for just 68 points in fairly easy minutes, and will each make almost $6M a year for a long time. Richards, who was demoted to fourth-line duty late in the year, could be the target of a compliance buyout. Despite his reputation as a shutdown center, Jarret Stoll was unremarkable (Corsi Rel -1.2%) against weak competition, and will make $3.25M for one more year. It will be interesting to see what LA does with Gaborik, who is now an unrestricted free agent. On one hand, Gaborik was outstanding in a Kings uniform, scoring almost a point per game in the regular campaign and exploding for 14 goals in the playoffs; on the other hand, he’s 32 and notoriously brittle, he’s been traded off of two teams in the past two seasons, and he may not want a big cut from the $7.5M salary he made on his last contract. All-Universe defenseman Drew Doughty is signed for five more years, as is Slava Voynov; the 24-year-old Voynov is skilled offensively, though he had the worst Corsi Rel % of all Kings blueliners not named Robyn Regehr (who will make $3M in Los Angeles next season despite being the team’s worst defenseman). Willie Mitchell and Matt Greene are UFAs and are unlikely to return, as the Kings’ dollars are likely to be better spent on extensions for defenseman Alec Martinez and Smythe winner Justin Williams, as well as new deals for pending RFAs like Jake Muzzin, Tyler Toffoli, and Jones. But those are worries for another day. For the time being, Kings fans will doubtless enjoy the satisfying end to a very interesting season, and look forward to being one of the NHL’s best again in 2014-15.

Other season wrap-up posts: Buffalo, Florida and Edmonton, Calgary, Winnipeg and the NY Islanders, Vancouver, Toronto, Ottawa, New Jersey, Washington, Carolina, Nashville, and Phoenix, Tampa Bay, Detroit, St. Louis, Dallas and Columbus, Philadelphia, Colorado, San Jose, Pittsburgh, Boston, and Minnesota and Anaheim.

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