AP Hockey Story of the Day: October 23day

Craig Custance has a great (unfortunately insider only) piece on coaching salaries in the NHL, and Mike Babcock’s stand for his fellow coach. It’s a very interesting read.

The biggest reason why hockey is so in need of a catch-all stat isn’t for basic analysis, because combining different metrics isn’t so hard, but it’s so that there’s a baseline for salaries. Being able to say that Bryan Bickell adds 2.4 wins per season above replacement but Joel Quenneville adds 3 would be huge, and would affect salaries in a big way, equivalent to what has happened at the GM level in baseball.

AP Hockey Story of the Day: October 22

Considering that a large part of what I use twitter for is finding great things to read, and then to tweet them out to my followers, I’ve decided to streamline this process a little bit. Considering that some of my analytics work (but don’t worry, not all) will be transferring to Hockey Prospectus, I’ve decided to pick a piece of writing, every day (okay probably not every day) that I believe to be truly great. This could be a work of analytics, something conceptual, it doesn’t even necessarily have to relate to sports, although it most often will. Instead of posting said piece on twitter, I will post in hear under the headline “AP Hockey Story of the Day” and, time-willing, will offer some brief thoughts on the piece.

So long story short, if you like reading the types of articles I tend to tweet out, make sure you either visit the blog frequently, or at the very least keep tuned to my twitter account as I tweet out links to these pages each day.

Without further ado, my story of the day for October 22nd is this piece by Jack Moore of vice, “How Wall Street Strangled the Life out of Sabermetrics“.

Some thoughts:

1. Moore writes something of a bittersweet tale of the birth and, to an extent, death of the public analytics movement in baseball. Morganization, the process that the business world underwent in the early 20th century revolutionizing efficiency, is a great parallel to what took place in baseball ten years ago, and what seems to be occurring in hockey today.

2. The big question is what comes next. How far do hockey teams go in their attempts to keep advanced knowledge out of the public sphere, and has the so-called “Summer of Analytics” in fact set the sport back in terms of public analytical progress.

3. The next big frontier in hockey is determining a valid catch-all statistic. Not because a catch-all in itself is important, but because it’s critical in evaluating performance monetarily. For example, how much does a win cost? How much does a 30-goal scorer cost? How much is a top-end GM worth? With that type of analysis, the market should correct itself even more than it already has. Sidney Crosby will make more money. Stan Bowman will make more money. Eventually, Stan Bowman’s analytics team (if it can continue to distinguish itself from the pack) will make more money.

4. I loved the anecdote about British mathematician G.H. Hardy. The guy was thrilled to be working in meaningless mathematics because his work couldn’t, say, help scientists to build weapons of mass destruction. Sure enough, after his death, Hardy’s work became the foundation for modern cryptography. It had use after all.

The Deployment Dilemma: How Fourth Lines Can Maximize Team Output

The season is finally here, which is great for most of us. But for some young up-and-coming players, it means getting cut from NHL rosters (whether now or following brief tryouts) while players who nobody would argue possess equal skill occupy the league’s fourth line spots. It’s an interesting dilemma, and one that until now nobody has to my knowledge managed to quantify. I’m only going to take the first step here, and speak in very broad generalities, but I hope that this piece will frame the debate over the use of the fourth line a little better, and present some evidence that maybe it’s time for change.

But first, a little perspective. Hockey wasn’t always about toughness or grit. In Canada, hockey’s roots lie in lacrosse, where early Canadians sought to find a winter alternative to their favored summer pastime. They implemented elements of rugby (like the no-forward pass), which certainly brought an element of ruggedness to the idea, but keeping the puck – or in the earliest days, ball – was basically as important as it’s seen to be by analytic types today. In Russia, meanwhile, hockey developed from soccer. Possession there was also critical, and simply speaking the best players played. There wasn’t much need for pests, or rats, or whatever you want to call them. It would have been out of character considering the sport’s origins.

But then the wars hit. First World War I, then World War II. Many of the top hockey players in North America, even those who had been competing in the National Hockey League, went oversees, and the league had to cope with less talent, and declining attendance. It was then that the forward pass was implemented, the blue lines were created, and in order to add some concrete excitement to a dying league, fighting was specifically outlined and legalized in the rulebook. Of course teams, fearing for their survival and suffering from a lack of talent, found guys to come in, play minimal minutes, and fight plugs on other teams. Fighting was a release for both players and fans from war tensions – to be clear, fighting had been around before, it just hadn’t been formally allowed.

Due to the lack of talent at the time, the dump and chase also became prominent. Many of the “replacement players” didn’t have the talent necessary to get by defensemen with the puck at the blueline, so coaches relied on players’ natural speed and toughness to give up the puck only to retrieve it. The practice became a staple of North American hockey, and while it was somewhat slowed by the end of the war and the return of many original players, the expansion of the 1960s allowed it to develop and thrive once again. Hockey had become watered-down, and dump-and-chase was the safest strategy for those players the coaches didn’t trust to get into the zone safely with the puck still on their stick.

Why is this important? Because there has never been an inherent necessity for toughness, at least not in the way players like Shawn Thornton, George Parros, and other enforcers embody it. Toughness is important for a player so that he doesn’t get phased by failure, so that he can stand up to bullies, so that he can fight through checks, but not in terms of the ability to fight, or to sit menacingly on the bench. The Chicago Blackhawks of the past few years have shown that, if nothing else.

So why is the fourth line necessary, in its current form, according to most hockey people? Thankfully, the dialect over the past few years from coaches has shifted from speaking about “top 6″ to “top 9 forwards”, at least recognizing the importance of talent over physicality to an extent. But why should it stop there? Why shouldn’t we be talking simply about NHL and non-NHL forwards? What are the reasons why the disconnect between “top-9″ and “bottom-3″ forwards still exists? Is this yet another example of the NHL not adapting nearly quick enough to the evolutions in the game of hockey? Or are there still reasons to keep things as is.

I thought about it, and came up with two good reasons why I felt a conventional fourth line might be necessary:

1) Penalty Killing.

Advanced hockey analysis tends to focus on even-strength over special teams for the same reason as it focusses on shot quantity over quality: not because the latter doesn’t exist, but simply because the former is far more easily quantifiable, and thus firmer conclusions can be drawn.

Special teams are very difficult to analyze at this point because the sample sizes are small, and because units play so much time together (against very similar opposition competition) that, unlike at even-strength, it is nearly impossible to determine which individuals are responsible for success or failure.

Many fourth liners are used on the penalty kill, but whether they are truly necessary for that reason is an open question. I didn’t do any numerical analysis on this, but I would guess that – especially as the appreciation for good two-way centers has increased – the need for those specialists is on the decline. Take for example, Max Pacioretty, a player who nobody would think of as a conventional penalty killer, but who last year, thanks to his high-energy, long skating stride, active stick, constant pressure, and improved positioning, was among the best penalty-killing wingers in the game.

I would argue that even at this point, having PK specialists can help a team. Organizations can, however, fairly easily get by without them, as long as the rest of their personnel is arranged in a way to pick up the slack. This is something I might focus on in a future post.

2) Limited ice time.

The other reason that made sense to me why one wouldn’t want bottom 3 forwards treated the same way as others is because they don’t get much ice time. According to this great piece by Garret Hohl (which I will reference more later), fourth liners average 8:03 of even-strength ice time per game. If a team has a bright young player, it’s understandable why they would want them playing top minutes in the AHL, say, rather than under 10 minutes in the bigs. Development, etc. etc. The limited ice time for fourth liners, obviously, makes sense on the surface because it frees up top liners (the big guns) to play more ice time, and thus, maximize their value.

BUT.

But, here’s where opportunity cost comes into the picture. Without numerical analysis, how can you know that the conventional method actually maximizes the use of those top players, and of the team as a whole? Essentially the question is: What is the opportunity cost of demoting talented youngsters in favor of less-skilled veterans, in order to play top players top minutes, in terms of goal differential per game?

Here is my very broad and basic attempt to answer that. Obviously I recognize that the situation changes by team and by year, so further exploration would be necessary before any specific team came to a conclusion on this.

Screen Shot 2014-10-07 at 9.16.15 PM

Here are the relevant columns of the first chart from that piece by Garret, which groups NHL players into buckets based on ice time. The total TOI/G at even-strength (these are all ES numbers) is 46:59, so I’m going to work under the assumption that that is approximately the amount of ES play per game. Any model for ice time needs to work within that parameter.

After examining this chart, I took a look at average ES ice time for rookie forwards in the NHL who played in at least 50 games last year. That number was 12:06. If you took out the three who played less than 10 minutes per game, that number would be 12:44, but the important fact I took away from that examination was that a number of teams were content with rookies averaging anywhere above about 11 minutes of ES ice time.

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If somebody as talented and young as Tyler Toffoli can play 11 minutes at ES per night and a smart organization like the LA Kings can be okay with it, then the same can be said for just about anyone, I think. Presuming they’re NHL ready.

So the next thing I did was to assemble a list of young forwards who were either cut this training camp in favor of less talented NHL veterans because there was no space in the “top 9″ for them, or had been in danger of it. I crowdsourced this to Twitter, and what follows is the list I decided upon.

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The list of players isn’t actually very important, as long as you’re willing to accept that some young player who may miss out because they don’t fit a fourth line role could potentially have a CF% of 50.25%, as well as the rest of the production you see above.

Disclaimer: The 54.12% offensive zone starts isn’t relevant to this illustration, but I will note that that number does confound the results somewhat, so it’s something for future examination. The conventional fourth liners likely – although not necessarily – have far lower OZS%s, and therefore their CF%s are bound to be lower. I don’t think that renders this study useless, but it’s something to be taken into account.

So with this list of eight rookies, I essentially made a 5th bucket, of AHL/NHL tweeners, one might say, for comparison. I took the conventional bucket format, and weighted shot and goal differentials, in unison with save and shooting percentages, to find an expected GF%. The numbers were slightly off – I’d expect from rounding with the data collection – but here’s what I found:

Screen Shot 2014-10-07 at 9.33.46 PM

That bolded number is the expected goal differential per 60 minutes of even-strength ice time. What I did next was see whether there was a TOI arrangement that allowed for the following things:

1) The fourth line, now composed of young skilled players, to play at least 11 minutes

2) None of the other lines to play as little as the fourth line

3) To keep every line happy

4) To improve expected goal differential

5) Obviously, not to surpass ~47 minutes of even-strength ice time per game.

Here is what I found:

Screen Shot 2014-10-07 at 9.33.30 PM

If one plays the first line 12.5 minutes (rather than 14.42), the second line plays 12 (rather than 12.83), the third line stays the same, and the fourth line plays 11 minutes, then the expected goal differential can be improved upon. The actual amounts don’t matter all that much, since the numbers are vague overall, but the point is that it could be done.

What about the fact that your top players are now only playing 12.5 minutes at even strength? Good, now they’re a) Less tired at the end of games, b) Less tired at the end of the season, c) Less injury prone. Or, taking it in another direction, they can now play more on the power play where their skill set is maximized, and even in some cases take more responsibility on the penalty kill, since the fourth line specialist is now extinct. Max Pacioretty, for example – somebody who has been injured somewhat frequently during his career, and who plays both power play and penalty kill – would certainly thrive under such an arrangement.

Conclusion.

So if you didn’t read all that, what is there to take from this piece? Essentially, based on quite rudimentary research and analysis, it appears as though the opportunity cost of cutting youngsters in favor of more established, low ice-time grinders, is very large, and ultimately isn’t worth it. Teams, by and large, would be better off playing their top-12 players overall, and more evenly distributing even-strength ice time.

 

2014-15 NHL “Why Not” Ranking Predictions

Predictions are pretty dumb since, as I’ve written about 100 times, hockey is a game of probabilities. That said, since I now have a space to write about whatever I want, and since I’ve been doing an awful job lately filling it with words, here is my view on what is most likely to go down here. Feel free to argue in the comments or on Twitter.

Atlantic:

1. Tampa Bay

2. Boston

3. Montreal

Metropolitan:

1. Pittsburgh

2. New Jersey

3. NY Islanders

Wild Card:

1. NY Rangers

2. Columbus

—————

3. Detroit

4. Washington

5. Toronto

6. Florida

7. Philadelphia

8. Ottawa

9. Carolina

10. Buffalo

 

Central

1. Chicago

2. St. Louis

3. Dallas

Pacific

1. Los Angeles

2. Anaheim

3. San Jose

Wild Card

1. Minnesota

2. Nashville

————–

3. Colorado

4. Vancouver

5. Edmonton

6. Winnipeg

7. Phoenix

8. Calgary

 

Stanley Cup Pick: Chicago over Pittsburgh. The one we’ve wanted for a while, entertainment-wise.

On Zach Parise, Players Using Analytics, and Healthy Skepticism

There’s a show called Modern Family in which a couple adopts a child named Lilly. The show plays up the little girl’s typical curiosity, as at varying points she’ll go into a phase where she just asks “why” continually until her parents get fed up. For some reason I thought of that while reading this piece by the Star Tribune’s awesome Minnesota Wild columnist Mike Russo this morning. Parise has always been one the players I have most admired because I think he blends the old school abilities to work hard, go to the net, block shots, and play in all situations, with the more new school skills at puck handling, entering the offensive zone with control, and most importantly, scoring goals. I may be Canadian, but even I could appreciate how cool his game tying goal in the 2010 Olympic Gold Medal Game was (and let’s just not forget how that game ended).

Anyway, simply by asking “why,” Parise was able to figure out that his attitude towards the dump and chase needed to change. I wrote yesterday about why I think it’s important that players understand and embrace analytic concepts, rather than simply heading future analytic-minded coaches’ advice. And I think Parise is a good example of why. In his first season in Minnesota, he made this comment.

“We went to the Finals dumping and chasing. We did it more than anybody. And we scored a lot.” And for players who don’t understand the probabilistic nature of hockey (hint: most surely don’t), that attitude is pervasive. You can win while dump-and-chasing, just like you can win without taking a lot of shots. But that doesn’t mean it will continue or that there aren’t problems.

“I just got kind of, not brainwashed, but my last couple years in New Jersey we were so adamant about dumping the puck in,” Parise says in Russo’s article. And so does every player. They grow up learning to play a certain way, and unless they’re lucky enough to pass through Kyle Dubas and Sheldon Keefe’s Greyhounds program, they likely never get what they’ve learned challenged. And the older you get, the harder it is to unlearn.

So let’s be Lilly for a moment, and consider the type of scrutiny that could lead a player to challenge his or her own views:

I’ve been told to dump the puck nearly exclusively in the neutral zone.

Why?

Because that’s the way it’s always been done.

But why?

Because you need to get the puck deep.

Why?

Because by getting the puck deep you can skate hard and go regain possession in the offensive zone.

But didn’t you already have possession? By carrying the puck in wouldn’t you be giving the puck up just to go get it again?

Well sure, but if you try to carry the puck in you might give up possession and cause a turnover.

But isn’t dumping it in essentially a turnover anyway?

Well kind of, but it would be a turnover in a less dangerous place.

But if you gain more possession, shots, and chances from carrying the puck in, isn’t it possible that you earn more net goals by carrying the puck in as much as possible, even if sometimes it results in dangerous turnovers?

And that’s where reading something like this, or any of the shorter summaries around the web, can come in handy for players. You don’t need a background in math, or even heavy reading skills, to understand the concepts or the conclusions. They’re hockey concepts after all.

Players don’t need to spend their time figuring out hockey’s yet to be unearthed inefficiencies, but they do need to have an open mind and a healthy skepticism. As do we all. Always ask “why,” and if you can’t find a satisfactory answer, change your approach until you find one.

On whether analytics are useful to players

There have been some interesting (let’s be honest, ridiculously annoying) quotes recently on the acceptance of analytics amongst coaches and players. “Of course coaches should use it,” the popular refrain goes, “but I don’t think players themselves can take much use from it directly. Well this interview between FanGraphs and Oakland A’s outfielder Brandon Moss suggests otherwise. Give it a skim and take note of how Moss’ awareness of in what situations and under what conditions he has success influences choices he makes with regards to his technique and strategy. Sure, it’s easy to say that coaches should look at the numbers and then relay general concepts to the players, but with that approach you’re opening yourself up to the same problems in acceptance as you are bringing general concepts to GMs without numbers to back them up.

Of course, not every player will have any interest in looking at numbers, and they don’t all have to. There will soon enough be companies – like there are in basketball – hiring themselves out to players, rather than teams, for individual analysis. Which side am I better at driving the zone towards? Do I shoot better glove high or stick low? Do I allow too big of a gap against charging forwards?

This is all info that players who learn about analytics can derive instantaneously, and cutting out the middle man – while in some cases irritating coaching staffs – can lead to big payoffs.

So yes, analytics are useful to players. And soon enough, many will be using them directly.

On whether descriptive, non-predictive stats really have use

As many of you know, I love reading about baseball and soccer analytics. I think that in baseball’s case, having the “first mover” element means that later-adapting sports like hockey can look to copy many of their concepts and ideas, even if the sports are quite different. Soccer, meanwhile, is quite a similar game to hockey – just a slower version – and therefore many of the more specific practices translate quite well.

Soccer is at an interesting point though because they, unlike baseball, are uncovering new statistics (courtesy of companies like Opta) while also just now figuring out which of those statistics are meaningful. You can get an idea of how far behind analytics in soccer is by the fact that its main predictive statistic: Total Shots Ratio – which is essentially the soccer version of corsi – is actually based on corsi.

Anyway, I was just reading this article by Mike L. Goodman (seriously, what would we do without Grantland these days?) and I was drawn to one particular paragraph, which discussed a concept that I think hasn’t completely been fleshed out – and may not be for some time – when it comes to descriptive vs. predictive statistics, and their merits. Here’s the passage:

“Arguing against the box score (and counting numbers) argues against using statistics for descriptive purposes. While traditional baseball stats are not particularly predictive of what will happen, they are very descriptive of what has happened. Try describing how the Baltimore Orioles played over the last week without using statistics, or try explaining how good Clayton Kershaw is. Stats that are increasingly becoming discredited in baseball don’t fail to describe how good or bad performance has been; they fail to explain the whys of that performance and, consequently, whether or not they would continue.” (Bolding my own)

Goodman claims that statistics that are descriptive but not predictive still have value in answering questions like “how well has team X played over the past week” or “how good is X player”. But is that really the case?

Let’s take an example that hits close to home for hockey fans. PDO. It doesn’t stand for anything but I like to think of it as “Percentage-Driven Output”. It is shooting percentage + save percentage, and if that number is significantly higher than 100, you’ve probably been lucky, and vice versa. Why? Because there has been no proof that in most cases maintaining that is sustainable. Goodman, based on this article, would say that a number like goal differential, which incorporates both fairly sustainable (shot differentials) and not very sustainable (shooting success) elements, is useful in determining which teams are good or have been good, even if they don’t predict which teams will be good in the near future.

But does that really make sense? On the one hand, we want to recognize past accomplishments, whether or not they are repeatable. Think Justin Williams and his game 7 prowess. But on the other hand, if it’s understood that success (or failure) isn’t sustainable, then is it really fair to use that success in descriptions as “good” or “bad”?

Let’s look at this another way. Goodman says that conventional stats like RBI or goal-differential are “descriptive of what has happened.” On the surface, this is true. But if they don’t give  an accurate description of why things have happened, then what what good does it do? In the end, it just adds to one of the bigger roadblocks to analytics acceptance that there is: belief that we understand the past, when we don’t.

Consider these quotes from two renowned authors and thinkers in the fields of psychology and statistics.

“The core of the illusion is that we believe we understand the past, which implies that the future also should be knowable, but in fact we understand the past less than we believe we do.” – Daniel Kahneman

“The illusion that we understand the past fosters overconfidence in our ability to predict the future.” – Nassim Taleb

It may seem harmless to say, “Albert Pujols had 4 RBI last week, so he was clearly at his best,” it is in fact misrepresenting not only the future, not only the player’s true talent, but also the past.

I wrote at the beginning of this post that I thought this was a concept that both hadn’t been completely fleshed out, and that I thought might not be for some time. That is because although I think this argument is persuasive, I’m not sure it’s the only one. As I wrote in the link I posted earlier on, I think unsustainable streaks of magic have their worth, and deserve to be celebrated. It’s unclear to me, though – and I believe still is deep down in the minds of even the most adamant analysts – how these two views can be reconciled.

 

 

 

Controlled Situation Corsi: Patrice Bergeron, David Krejci, and the Set Play

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I wrote last week about the Bruins’ struggles following offensive zone faceoff losses. Obviously, Shawn Thornton played a part in that, but a fourth line can only get so much ice time, and obviously there was a bigger issue. When I looked over the numbers from the past few years, it became clear that David Krejci and his linemates, who received a large portion of the offensive zone starts, were hurting the team the most in those situations. Considering Krejci’s new 6 year, $43.5 million contract, and the ongoing debate over whether he or Patrice Bergeron is truly Boston’s number one center, I decided to look briefly (update: not so briefly) at the breakdown of their numbers and where such struggles might be coming from. First of all, here are the numbers.

Screen Shot 2014-09-09 at 5.45.55 PMThe chart was built to hold formulas, rather than to be clear to readers, so allow me to explain. These cells represent Bergeron’s and Krejci’s corsi for (or shot attempt differential) percentages, respectively, in the 21 seconds following defensive zone faceoff wins, the 37 seconds following defensive zone faceoff losses, the 29 seconds following neutral zone faceoff wins, the same for losses, and then the 37 seconds following offensive zone faceoff wins, and the 21 seconds following offensive zone faceoff losses. Why those specific numbers of seconds? It is after those amounts of time that Tyler Dellow found that the effects of faceoff locations and results were nullified. The final column shows open play corsi, which is essentially zone start and faceoff result-adjusted corsi, except with a slightly more limited sample size.

We could easily just examine these totals from the past four seasons, but considering we are trying to evaluate for the present and future, I wasn’t satisfied with weighting these seasons equally, so I borrowed the Marcel forecasting system, courtesy of at various points Tom Tango, Eric Tulsky, and most recently garik16, weighting the most recent seasons more highly than those further in the past. Here were my results.

Screen Shot 2014-09-09 at 5.46.27 PMAs you can see, the impact isn’t huge, but I wanted to be sure that we weren’t focussing on problems from years ago that have since been resolved. Anyway, it’s clear from these numbers – and the knowledge that Krejci doesn’t play against tougher competition or with significantly worse linemates – that Bergeron is the better possession player. The areas in which Krejci struggles compared to Bergeron are following neutral zone faceoff wins and following offensive zone faceoff losses. Considering, however, that the league average CF% following neutral zone faceoff wins is just over 60%, the takeaway from those results is clearly that Bergeron is a god among men, rather than that Krejci is horrible in those situations. Following offensive zone losses, however, is another matter. The average CF% in the 21 seconds following offensive zone faceoff losses in 2013-14 was 56.71%, so it’s clear that that is an area in which Krejci’s line needs to improve.

I dug into the video to try and find out why.

And I didn’t find much. Whether it was Bergeron or Krejci, the B’s would be aggressive and rightfully so, sending the two wingers to pursue the puck. Sometimes they would get to the puck in time, and sometimes they wouldn’t. I didn’t see anything that indicated a particular flaw in tactics or technique. Until I did. Maybe.

Screen Shot 2014-09-08 at 7.59.39 PMOn certain occasions, Milan Lucic, the LW, would line up directly behind Krejci, at the top of the circle. The hope from such a play would be that Krejci would win the faceoff straight back, and that Lucic would have an immediate chance for a shot on goal from the high slot. Unfortunately, when Krejci lost the faceoff, this would happen.

The two forecheckers would be far too late arriving. A zone exit would be practically a certainty. This play was used fairly regularly last season from what I saw. There were two conclusions I drew from examining this admittedly small sample of plays (I watched offensive-zone faceoff losses from every 10th Bruins game last season).

1. Krejci and Lucic weren’t in sync on these set plays.

Obviously, after watching just under a dozen of these, it is hard to tell whether I simply got a poor sample or if there was a legitimate problem, but from what I saw, there were a few too many faceoff wins that ended up like this.

Besides bad luck, I notice that Lucic sets up a little bit too far to the left. Considering Krejci’s right handedness, and therefore his stick positioning when he makes contact, it is inevitable that even with a fairly clean faceoff win, the puck will trend right, at best winding up in Lucic’s skates. It would take the cleanest of faceoff wins, consistently, for Lucic’s positioning there to work, and very few players can win faceoffs that cleanly that consistently.

2. Bergeron is a faceoff god and Krejci is a merely above-average.

Bergeron can certainly win clean faceoffs, but his mastery is such that even when he doesn’t do so, he can still recover the puck and put it in a place where his teammates can make something happen. Notice here how Bergeron gets the puck out of the scrum to Marchand (stationed further inside), who makes a heads up play, recognizing he doesn’t have the puck and shuffling it over to Krug, for a solid chance.

So is the play worth it?

Bergeron’s mastery of faceoffs is critical to the decision-making surrounding this play because losing the faceoff is a free zone-exit. If I were the Bruins, I’d be examining every one of these situations from every game (rather than every 10th game) to determine for both Krejci and Bergeron a) the CF% and scoring chance % in the seconds directly following a faceoff win with the play implemented, b) the same with the play not implemented, c) the CF% and scoring chance % with the play following a faceoff loss, and d) the same without the play. You get the idea. The reason is that by using Bergeron and Krejci’s faceoff percentages – 58.6 and 51.2, respectively in 2013-14 – one can determine the expected value of each offensive zone faceoff with and without the play, and thus come to a conclusion as to its effectiveness.

Inevitably, considering the nature of the play, that expected value is bound to be far higher for Bergeron than for Krejci, even if they were both equally adept at pulling it off after faceoff wins. For now, it is clear that Krejci’s numbers following faceoff losses suffer as a result of this play, and one can only guess as to whether that gap is made up following wins. My guess would be not.

On Martin Brodeur, “GOAT”, and Longevity

There was a report published today that the Montreal Canadiens have, or had, or might have had interest in Martin Brodeur as a backup goalie to Carey Price. I’m shady on the details not because I’m journalistically ignorant, but because I don’t care. Brodeur is, frankly, no longer an NHL calibre goalie, the Canadiens are set (or, I guess, already over capacity) in net, and to be quite honest none of this has anything to do with why I’m writing this piece.

I’m writing on Martin Brodeur because Joe Posnanski answered a mailbag question about Derek Jeter today that reminded me of a topic I had been meaning to write about for some time: Longevity.

There are many who claim that Brodeur is the greatest goaltender of all time because of his 688 wins or 124 shutouts, and then there are those who retort that wins are a highly flawed, team dependent stat, and that save percentage is far more important than shutouts. These people point to guys like Patrick Roy or Dominik Hasek as those who put up sparkling save percentages during shorter careers, and end up right at the top of era-adjusted save percentage lists, rather than 10 or 20 rows down.

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For the longest time, I was completely pro-Roy and anti-Brodeur when it came to the GOAT debate – which was logical having grown up in Montreal, and also having cheered feverishly for the 2001 Colorado Avalanche as the bandwagon of my youth. But my attitude on the matter has started to shift. I still believe that at his best, Dominik Hasek was the greatest goalie this league has ever seen. This graph, courtesy of Chris Boyle, shows Hasek’s save percentage at each age, relative to league average. The numbers speak for themselves. Hasek only made his NHL debut at age 26, but he was outstanding right up until his age 38 season, when most goalies are already golfing six days a week.

Screen Shot 2014-09-09 at 11.53.06 AMI also still believe that Patrick Roy, all things considered, was the greatest of all time. To me, he had the right mix of peak performance and consistency, individual and team accomplishments, to fit the bill. But I’ve come around on Brodeur; I’ve elevated his status in my mind from “overrated reputation-riding team free-loader” to “overrated, but still pretty remarkable.”

After all, this is a guy who (has) played at least 30 games in 19 different seasons, and 29 games in a 20th. His save percentage was above .900 for all of them, and while in this era .900 isn’t exactly the benchmark of the elite, considering that nobody else has ever done that, it’s something.

Screen Shot 2014-09-09 at 11.34.17 AMSo what’s the bottom line? Just like how Derek Jeter will ultimately be remembered for being a very good baseball player for a longer period of time than just about anybody else, Brodeur will be able to say that he was an average or better goalie for longer than anybody else (except maybe Roy, who quit while he was ahead), and who at times was very very good.

Staying healthy, keeping a starting job, winning trophies, winning Stanley Cups, none of those things are easy. Marty managed to accomplish them all over a long period of time, longer than the Dominator. And that’s worth something. So no, Martin Brodeur wasn’t the greatest goalie of all time, and he certainly wouldn’t be near the top of my list of starters for a one-game playoff, but he survived for a long time in a league where so many don’t, and his reward was the most games played, wins, and shutouts in the game’s history. And that’s nothing to scoff at. 

On P.K. Subban and the NHL’s Marketing Gaffe

I was chatting with a friend yesterday and the discussion turned to hockey. Now this was somebody who has worked in a professional sports front office in analytics, has met with a number of commentators, coaches, managers, and players in the sports world. It’s safe to say ESPN is glued onto his TV screen for major live sports. The guy knows sports, and he happens to be of a minority group. “The Calgary Flames,” he told me, “were always a team I liked because of Jarome Iginla. He’s great, and he’s black!” “Oh,” somebody else chimed in, “well what about P.K. Subban of the Montreal Canadiens?” “Wait, there’s another black star in the NHL now?” was the response.

I was shocked and yet somehow not surprised.

This was a player who was not only potentially the best defenseman in the National Hockey League, not only African-American (or Canadian, if you’d prefer), but also possibly the most marketable player in league history. Subban has style, he has spunk, he’s modest (at least on camera) but still bold and confident. He’s generous and seems wise beyond his years, but still has a youthful charm and unpredictability that draws cameras – and certainly fans who have heard of him – to his Ice Bucket Challenges and charity signings. 

Yet here was somebody who should be learning to love hockey through the star who most closely resembled himself. And he had never even heard of him.

The way I see it, the league has two excuses for not shoving its stars down our – or rather Americans’ – throats on a more frequent bases.

1. It’s a team sport, so the teams should be emphasized more than the players. My response? Just because Sidney Crosby can’t win a Stanley Cup on his own – NO, HE CAN’T, CERTAIN MSM – doesn’t mean he can’t be promoted and idolized. He’s not LeBron James, but to Americans he doesn’t have to be. He just needs to be Sidney Crosby, rather than…you know…”who?” 

2. Hockey’s stars, unlike those of other sports, have dull personalities and spout cliches and are therefore harder to market. My response? This is true. Crosby and Steven Stamkos are fairly dull. Patrick Kane looks like a choir boy. Drew Doughty should be a member of 30 Seconds to Mars. Alex Ovechkin speaks another language. It’s not easy, and I’m sympathetic to that. But Subban is like a gift from the hockey gods. It doesn’t matter whether he does or doesn’t have character issues away from the cameras. In public, he is the most marketable hockey player in the world (if he were American, it would be of all time), and it’s time that the NHL took advantage of that.

So how to do that, well I have a couple of ideas?

1. Rig the NHL cover vote to get him on the cover. Believe it or not, that game isn’t really catered to hard core hockey fans who actually want realistic action. Casual fans love it, and keep in touch with the game by playing it. But Patrice Bergeron? Meh. He’s one of the most underrated players of this generation, but he’s quiet, French-Canadian, white, and unimposing. He simply doesn’t do much for the NHL brand. Subban would.

2. Commercials featuring Subban on major networks. Let’s face it, commercials for hockey on NBC Sportsnet don’t do much, because the people who watch NBC Sportsnet are already watching hockey. But imagine a well-made commerical featuring P.K. Subban – his camera antics, his post-season heroics, the chip on his shoulder – on ESPN, or if that wasn’t possible, FOX, or CBS, or ABC. The point is to acquire new hockey fans, not to pander to current ones. “Hey hockey fans, don’t you dare forget about those playoffs coming up, history will be made and all!” is great, but mostly meaningless. Showing the greatness of hockey to outsiders, particularly on sports networks, pulls in fans.

I wrote about one race problem the league may still have yesterday. This might be another minor one. It’s unacceptable that the league wouldn’t use P.K. Subban (and guys like Evander Kane, and maybe even more importantly, the American Seth Jones) to try and attract a young generation of African American sports fans. It’s becoming cool to like hockey again, after all, so now is the perfect time to strike. Don’t waste god’s recent gift to hockey; embrace it.