After a lot of thinking, I’m beginning to feel like they’re right, at least to some degree, for a couple of reasons. For one, the talent disparity that we used to see in evidence whenever the Montreal Canadiens played, say, the Kansas City Scouts is largely gone. Yes, at the extremes, there’s still a clear difference between good and bad — anyone who’s seen a Blackhawks-Oilers game in the last two years can attest to that — but on an average night, the difference between two teams is much more granular than it’s ever been. Part of that is due to improved scouting, as teams scour not just the wilds of Canadian junior, but European junior and pro leagues, American college and high-school, and even occasionally (though all-too-rarely) Canadian university hockey. Good players are everywhere, and while you can question the decision-making and efficency of some teams, there’s no question that most of the stones are at least getting turned over, and that there’s talent to be found under every one of them. There’s also the fact that coaching, athletic training, and psychological training are much better now than they’ve ever been. Players get feedback on what they did wrong, can see the video of the error for themselves, and know what to do for next time. Guys can spend a dozen hours or more per week in the gym, building their aerobic base and their strength. Players learn how to deal with hostile crowds, can talk to trained professionals about their confidence and about off-ice issues that can prove to be a distraction. All of this leads to the average NHLer being much more skilled, fit, and resilient than they’ve ever been, and there’s much less disparity between the best and worst in at least the last two categories — and arguably the first, as well — than we’ve ever seen. And then, of course, we have the redistribution of talent brought about by the salary cap, which teams are still learning the ins and outs of five years later. All of this leads to a situation where it’s much more likely that the outcome of a game, for example, can hinge on a fortuitous bounce one way or the other, because on any given night, there’s not that much to choose from, relative to 30 or 40 years ago.

The other main reason is that high-level hockey seems to be a barely-controlled chaotic system, which I think is a product of the way the game’s developed over the last half-century or so. In that time, we’ve seen the introduction of the slap shot, drastic changes to goalie equipment and play style, meaningful east-west play, heavy shot-blocking, composite sticks, and mid-air redirection of the puck as an intentional play, to name just a few things. Many of these changes come in a sort of delayed chain-reaction. Slap shots begat changes in goalie equipment. Changes in goalie equipment combined with the butterfly style led to much more shot-tipping. The evolution of the modern east-west game — not just skating up and down your lanes, but cutting across the ice and creating holes through both skating and puck movement — started by the Winnipeg Jets of the 1970s and perfected by the Edmonton Oilers of the 1980s, made it difficult to play man-to-man defence, especially for the more lumbering brutes of the defensive trade, necessitating more shot- and pass-blocking, from all members of the lineup. Combine these changes with worsening ice conditions — especially in warmer climes and during the latter stages of the playoffs, as the weather gets warmer everywhere — and increased overall athleticism — leading not only to faster players and more violent collisions, but more abuse to the aforementioned ice through the course of a game — and the puck winds up spending much of its time hopping here, there, and everywhere, rolling, flipping, on end, what have you. Sometimes unpredictable things happen like, say, the puck hitting a rut on its way in from centre ice and hopping over a goalie’s glove, or a puck pinballing in off three sets of legs in front of the net. At a certain point, physics takes over and there’s little you can do to predict it.

All of which leads me to last night’s game between the Hitmen and the Spitfires. Sure, it ended 6-2 Windsor, and appeared for all the world, from the boxscore, to be the coronation of the first Memorial Cup repeat in 15 years. If they can abuse the only team that appeared to be any real competition to them going in, what hope does anyone else have? Except when you actually watch the game, it becomes clear that bounces played a huge role in the final outcome. The first Windsor goal came off a Michael Stone shot-block: the puck bounced just under his ankle, in the tiny space that was there, and fooled Martin Jones. The second, just a minute or so later, deflected off the stick of a backchecking Ben Wilson. It’s 2-0 five minutes in, a hole from which the Hitmen never recovered, but it was off two unfortunate bounces. From there, I felt it was actually a fairly evenly-played game, with both teams getting their share of the bounces: a shot that rang off both posts behind Martin Jones and out at one end, a tip by Matt MacKenzie going two inches wide because the puck started rolling mid-pass at the other, and so forth. A ton of close calls that could’ve been in or out, based on ever-so-slight variances in human performance — so small as to be irreproducable — or the condition of the ice or what have you. From the four-minute mark of the first to the 19-minute mark of the third, the balance of scoring was 3-2 Windsor. That was the game I saw, and that game in no way resembled the 6-2 final scoreline.

Sure, some nights a team gets outplayed, full stop…but others, the bounces go the other guys’ way and obscure the balance of play. Maybe I’m being a blinkered fan here, and maybe I’m not lending enough credence to score effects, but what I saw last night was a team that could compete with the best in major junior, that suffered just a couple of breakdowns, but otherwise played an admirable road game without their best forward. If they play Windsor again on Sunday, with Brandon Kozun healthy enough to play, I see no reason to think that they can’t win the Memorial Cup. That doesn’t mean that they will, of course, but it does mean that the gap between the Windsor Spitfires and the Calgary Hitmen is not what yesterday’s score would have you believe.

The Oilers had a lot of things go wrong this year and as much as people like to bring up the cap I’m not convinced that it limited them this year and given that they’re planning to rebuild I’m not sure it limits them next year. However, at the beginning of the season a list was published of the best goalies of the last 3 seasons who were free agents, and what they were signed at. Let’s take a look again.

(Courtesy Copper ‘N Blue)

Notable exclusions from this list on the free agent market were Craig Anderson and… that’s about it.

So let’s cut out the goalies who didn’t play in the NHL this year and look at how many games the remainder played, won, and what was their SV%:

Now, it’s apparent that Deslauriers is off the mark, but not drastically.  Conklin’s number is likely inflated because he just barely crossed the 25GP mark, and as far as everyone else goes, 0.909-0.903 isn’t a huge difference.  It’s also interesting that Biron didn’t even make the list.  Only two other goalies on the list played the same amount as Deslauriers, and those are Roloson and Nittymaki, and they’re anywhere from 4 years to “old as the hills” older than him.

Now let’s take a look at those teams’ combined stats:

• St. Louis: 82GP, 40W, 0.912SV% – 2473SA – $4.3mil
• Tampa Bay: 82GP, 34W, 0.902SV% – 2575SA – $2.8mil
• New York Islanders: 82GP, 34W, 0.901SV% – 2619SA – $8.4mil
• Carolina: 82GP, 35W, 0.903SV% – 2574SA – $3.666mil
• Columbus: 82GP, 32W, 0.900SV% – 2514SA – $2.105mil

So judging by the win and SV% columns, St. Louis cleaned up, though they also had the least SA.

NOTE: There may be some issues with these numbers because of how NHL counts goals.  I’m unsure whether OT goals and SO goals are counted in this measure.

It also bears mentioning that the only teams who got a free-agent goaltender and are actually in the playoffs are Colorado and Philadelphia, and they both backed in. (Ignoring Raycroft, LaBarbera and Danis who each played less than 25 games)

What does all this mean?  If there was a goalie not named Anderson worth spending money on this past offseason, it was Conklin but god knows he’ll never play in Edmonton again.  And while Edmonton obviously did the worst, it did the worst with the only team in the league to play rookies for more than 60 games this season.  Add that to 525 man-games lost and 135 defenceman-games-lost (and 56 Hesky-games lost) and it’s tough to argue about the horribleness of the goaltending relative to what was available.  I think it’s a pretty safe assumption that with half of the injuries Edmonton certainly wouldn’t have gotten first overall pick.

In short, the complaints that people had about the Khabibulin signing and free-agency were blown out of proportion.  Yes, Anderson was a great buy.  Yes, Conklin is actually pretty good.  Yes, Khabibulin cost a decent amount of money.  But when it comes down to it having more cap space wouldn’t have fixed Edmonton’s problems this season, and there’s quite a bit of space free next season.  St. Louis got the best bargain, and they’re also the one of these teams who finished in 17th place overall.  The Islanders got the worst bargain, followed by Edmonton.

No, this isn’t an argument in favour of Khabibulin.  This isn’t even an argument in favour of good cap management.  It’s an argument purely saying that at the end of the day the stats are more or less the same so we just paid a bit more to get that #1 pick, not to mention driving down the prices on their RFA signings this offseason (Gagner, Cogliano, Potulny, Dubnyk, Deslauriers, Pouliot, Brule).  I mean, have you seen Calgary’s cap hit for next season?

Plus, 2 spots on the top 10 saves of the year isn’t bad for a rookie, no matter how dismally the rest of the year went. (Yes, I know they were in the same game. Sidenote: Detroit was on the wrong end of 4 of them? Crazy.)

Unreasonably high and low shooting and save percentages likely do mean something.  What though?

• If a team has an overly high SH% AND an overly high SV% AND are winning the majority of their games by one goal (or two goals if there’s an empty-netter), that team is likely to lose more games going forwards, barring a substantial increase in shots and blocked shots.
• If a team has an overly high SH% OR SV% but not both and win the majority of their games by one or two goals, the team likely will need to shore up their defence or shooting, but not both.
• If a team doesn’t have an overly high or low SH% or SV%, we can’t say anything about them at this time.
• If a team has an overly low SH% OR SV% but not both and lose the majority of their games by one or two goals, the team likely will win more games once the stat has returned to the mean.
• If a team has an overly low SH% AND an overly low SV% AND are losing the majority of their games by one goal (or two goals if there’s an empty-netter), that team’s record is likely to improve drastically.
• If any team is winning or losing by more than 1 goal, we can’t really say anything about them either.

So, looking at Willis’ list, can we say anything about any of the teams with reasonable certainty?

The teams in both highs are Colorado and the Rangers.  Colorado has won most of their games by 3 goals, so they fall outside of the criteria I’ve provided.  They’re enough of an outlier that we can’t say much about them.  The Rangers also have 3 large wins and two 1-goal wins.  While we expect that both the Rangers and Avalanche’s numbers will go down, we can’t really tie that to how the team will do in the future.

The teams in both lows are Minnesota and Toronto.  With Toronto it’s a bit difficult because the two big losses they had were at the hands of the Rangers and Avalanche (Well, and Pittsburgh).  Again, Toronto falls far enough into the margin that we can’t say anything about them at this point in time.  Minnesota is on the edge of acceptable, losing 3 games by 1 goal, and 2 by more.  As such, we should expect Minnesota to improve drastically in the near future.

Atlanta and LA won most of their games by more than 1, so I’m ignoring them.  Edmonton, Calgary, Washington, Philadelphia, and Pittsburgh will likely need to find a way to shoot more or play better defence to maintain their record.  Columbus is outside of the 1-goal radius, so they’re ignored.

On the low end, the Islanders have lost most games by one goal, so expect them to start winning more games any time now.  Florida is outside of the criteria, so again, ignored. Nashville seems to switch between 1-goal games and blowouts, so we can’t say much about them.  I’m putting them in the “can’t say much” pile.

Vancouver, Boston have lost by more than one for the most part, so they’re outside the criteria.  Detroit and Chicago have been in many 1-goal games, so expect their records to improve soon.

Phoenix and Buffalo are outside of the criteria because they’re in the top and bottom in SH% and SV%.  They really could go in either direction or no direction at all.

So, to sum up:

• Teams who we can say with reasonable certainty that their records will improve in the near future: Detroit, Chicago, New York Islanders.
• Teams who will need to improve in their shooting or team defence to maintain their current records: Edmonton, Calgary, Washington, Philadelphia, Pittsburgh, Columbus.
• Teams who should improve, but that won’t necessarily affect their record: Vancouver, Boston, Toronto, Florida, Nashville.
• Teams who should do worse, but it might not affect their record: Atlanta, LA, Colorado, New York Rangers.
• Teams who should see their record drastically improve: Minnesota.

Now, obviously these criteria mean a hell of a lot more with a larger sample space, and while intuitively we’d think that Toronto has to get better, this small sample space doesn’t come anywhere near indicating that.

And that’s my nitpicky 2 cents.  Feel free to pick at my methodology in the comments

First, let’s consider the age argument. It would seem that the primary concern here is that Khabibulin should be primed to fall off a cliff any year now because previous generations of player did, which is awfully nice to know but really quite irrelevant, especially considering the fact that this team just got a near-career year out of a 39-year-old ‘keeper. The fact of the matter is, players understand and implement nutritional and training principles better now than they have at any point in the League’s history, and are in better overall physical condition than at any point since the game’s very earliest days, when multi-sport professional athletes playing hockey in the winter and lacrosse or rugby in the summer were common. Put more succinctly, I believe that 40 is the new 35, and that we will continue to see more players put up serviceable numbers well into their late 30s. (As an example, Brendan Shanahan put up nineteen consecutive 20-goal seasons, his most recent at age 39, and scored 40 goals as recently as age 37. Until this most recent half-season, he’d been averaging over 18 minutes per night for as far back as Hockey Reference has numbers, about ten years.) I don’t think it’s valid to presume that players today will follow the same progression curve that their forebears did, because they operate fundamentally differently, showing up to camp in elite physical condition instead of playing their way into it. We’re still several years away from having a sufficient amount of data to predict when the modern NHLer takes that irrevocable nosedive into athletic senescence, but as it stands right now, I would postulate that playing a 36-year-old goaltender for a significant number of games (i.e. more than 50) should not present a real problem, so long as he’s stayed in shape to this point.

Comparing Khabibulin to his team

The other argument revolves around his mediocre-to-bad save percentages while a member of the 2005-08 Chicago Blackhawks. Above is a table showing Khabibulin’s points percentage, save percentage, and goals-against average as compared to the team average for his entire career, with the Chicago numbers blocked off separately. (Ironic aside: one of his worst regular-season performances, at least relative to his backup, came in his Stanley Cup-winning season of 2003-04.) In 2005-06, I don’t think anyone would deny that he was at best not helping matters, and at worst a big part of the problem, but at least in terms of save percentage and goals-against average, he outperformed the team average (that is to say, he was better than his backup) in all three years. At the very least, this tells me that Khabibulin was far and away the best option on the team for all three of those years. Could there have been better goalies on that team? Sure, probably. However, I would suggest that the raw numbers, which have been cited repeatedly as a problem, would be influenced by the quality of the team. I know, the accepted wisdom of the Edmonton Eulers is that individual players don’t have a significant impact on a goalie’s save percentage, and that may be so, but I would counter by saying that we understand, and even expect, that a goalie is going to have a sub-.900 SV% on the penalty-kill. You’re down a man, defensive coverage is stretched to the limit, and breakdowns will inevitably result in high-percentage chances and goals. Would it not be logical, then, to extend the same consideration to bad hockey teams? That’s not to say that we should forgive that abysmal .886 in 2005-06, of course, nor is it to say that universally, better teams will have better goalie numbers (see: the 2005-06 Oilers), but that all other things being equal, the same goaltender will probably put up worse numbers on a worse team. It’s no surprise to me that Khabi’s SV% increased in each of the next three seasons, because the team itself got better each year. The larger change from 2007-08 to 2008-09 (.909 to .919) could also be due in part to the fact that Joel Quenneville was a bit more concerned about defensive responsibility than his predecessor, Denis Savard, in addition to the overall improvement in the play of the team. You can argue that there were better options out there that should have at least been considered — leaving aside the usual caveat that no one wants to play in Edmonton anyway — but that doesn’t necessarily mean the option that the Oilers ultimately went with was a poor one.

When I started this article, I hadn’t planned on it turning in to the Nikolai Khabibulin Show, because to be honest, the real question marks for me are behind him. Let’s start with Jeff Drouin-Deslauriers, the designated backup for this season. To be blunt, I don’t have much faith in him; never mind the statistics, he looked shaky in his first-star turn at Madison Square Garden last November, when he withstood a siege in the final forty to squeak out a 3-2 shootout win, and he’s only looked worse from there. I can see that he’s trying to play something of a hybrid style, more akin to that of Martin Brodeur than most other modern goalies, but let’s be honest: JDD is no Marty. Aside from relative talent level, of course, part of the problem is the fact that Deslauriers spent much of his early pro career being jerked around by the Oilers. They pulled the plug on their own minor-league team after his rookie year, and shared affiliation with others for a couple of seasons, forcing him to play behind other teams’ prospects — an even greater problem for goaltenders than skaters. They finally got him a minor-league team he could start for in 2007-08, but then made him spend most of last season in the press box, because three-goalie rotations are traditionally the mark of a successful hockey club. Whatever abilities he had have been at least somewhat squandered and suffocated by the terrible arrangements the Oilers made over the last few years, to the point where I think his ceiling is now much lower than it was when they drafted him seven years ago. He just didn’t get enough net time as a young man to build up both the skills and the confidence to take the next step, and confidence is an important thing for a goaltender more so than any other position, certainly based on my own limited experiences in net. Maybe a new goalie coach and a greater opportunity with the NHL club will help him to some degree, but at this point, he’s a career backup, and I wonder even then if he’ll be able to hold off future prospects as they mature into NHL-ready goalkeepers.

The prospect he should be worried about now is Devan Dubnyk. No, a .906 SV% in the AHL isn’t entirely confidence-inspiring, but as I noted with Khabibulin, I don’t think SV% is a number that can be considered entirely without context. The 2008-09 Springfield Falcons were, in a word, fucking awful. In fact, they had the worst record in the AHL last season at 24-44-12 with a -70 GD. I’ve already mentioned Rob Schremp as one person who had a bad year on that bad team, but I think Dubnyk is, frankly, much more likely to rebound into an NHL player at this stage of his career. Certainly, a sub-.910 SV% is kind of to be expected given the number of injuries and ECHLers inflicted on that team. There’s no guarantees, of course, but I have a lot more faith in him without even seeing him than I do in Deslauriers. As for judging his play personally, well, I’ve never seen the kid play, or if I have, it was at a pre-season game several years ago, of which I no longer have any recollection. My thinking is that for 2009-10, Dubnyk should focus on being The Guy in Springfield and putting up good numbers, so that he comes into camp in 2010-11 ready to wrestle the backup job from Deslauriers. While I think he’s probably the better goaltender, certainly in the long term, I can’t imagine he’s ready for the NHL job this year. I have to hope that he will be soon, though; as unconcerned as I was about Khabibulin’s age now, when his final year rolls around, there has to be a succession plan in place, and frankly, I’d rather he be succeeded by the kid that was developed properly in the minors than the kid that wasn’t.

Statement: A lot of people are all up in arms about JDD, and want him traded, shelved, or both.  A lot of that has to do with his AHL SV%.

Fact: JDD played more minutes and had a much better SV% than Schneider did this year in the NHL (.901 – .877)

Fact: JDD had a much worse SV% in the AHL than Schneider did (the previous year: .906 – .928)

By the numbers, we expect Vancouver to be better than Edmonton, though that may be skewed by Luongo.

We know Edmonton AHL teams have been much worse than the Manitoba Moose over the relevant seasons.

Questions: Does SV% by itself tell us anything of any real merit? Is JDD the lost cause many think he is? Is Vancouver (aside from Luongo) actually better than Edmonton?

Bonus Question: Can we reasonably consider anything that happened in the games after being mathematically eliminated as statistically relevant in any question? (How well JDD plays, whether or not having Lubo on the roster would have needed to make a 7 pt difference, etc..)

Recently, the prolific Jonathan Willis posted a study suggesting that hitting actually had a negative correlation with winning, a result that seems counter-intuitive, to say the least. However, his analysis looked only at teams on the margins, the five highest- and lowest-hitting teams in each of the last nine seasons, without accounting for the twenty in the middle. The purpose of this study is to complete this analysis by examining the relationship between the hit statistic and points for all 30 teams in each of the last eight seasons. Additionally, I will look at the cumulative relationship between hits and points in the four seasons before and after the lockout, keeping the two periods segregated due to changes in play style and point awarding after the 2004-05 lockout.

My hypothesis, before performing the analysis, is that I do not expect there to be a strong correlation between the two variables in any one given season, though it is plausible that there will be a weak correlation in one direction or the other in the multi-year analysis. My reasoning is that last year alone, there were good teams that hit (Boston), bad teams that hit (Tampa), good teams that didn’t hit (Detroit), and bad teams that didn’t hit (Colorado), just showing up in the margins, and that doesn’t account for all the teams in the middle that are likely to run the gamut in terms of the hit statistic. While hits are useful in separating players from the puck, Big Hits are also just as likely to put you wildly out of position, and when you miss that Big Hit, then you’re not only out of position, but the guy with the puck is 20 feet behind you before you even start to turn around. Furthermore, while hitting is a good way to gain puck possession, you still need to put the thing in the net, and there’s a whole pile of important factors affecting that which have nothing to do with hitting.

Methods

The hit and point data will be culled from the NHL.com statistics portal, then accumulated and analyzed with SPSS v16.0 using a Pearson linear regression analysis with a significance threshold of p < 0.05.

Limitations

The question Willis seemed to be asking was whether hitting and physical play had an effect on winning. I do not believe the data available can tell us this for two reasons. One, the hit statistic is subject to recorder bias, due to both home rink effects and a lack of a uniform definition of what a “hit” is, precisely: scorekeepers tend to use the “I know it when I see it” definition, which isn’t very scientific. Until repeatability can be established, there’s a limit to what one can say about physicality using the hit statistic, though I would submit that for the purpose of this study, it is a sufficient proxy. Two, there are a large number of confounding factors that affect the outcome of any individual game, many of which cannot be consistently and repeatably quantified, despite the efforts of hundreds of video-game developers over the last twenty years. Without being able to account for everything else, it is all but impossible to establish causality. The most we can say with the data on hand is whether there’s a possible relationship or trend between recorded hits and earned standings points.

Results

Table 1 shows the pre-lockout data for the 30-team era, spanning 1999-2000 until 2003-04, where r is the Pearson correlation coefficient and p is the significance.

Table 2 shows the post-lockout data, from 2005-06 to 2008-09.

While performing the analysis, I noticed an interesting trend: as I went further back in time, the League average number of hits recorded steadily decreased, then hit rock bottom in 2002-03, before abruptly climbing back up again. The data for this appears in Table 3 below.

While this would not affect any individual-season correlations, it could potentially alter the correlation of the cumulative data. Because of this, I reran those correlations using a percentage of league average hits, with the corrected values appearing in Table 4, below. (Note that because the pre- and post-lockout point-percentages were internally consistent, they were not adjusted.)

Conclusions

It seems abundantly clear from this study that, rather than there being a negative relationship between hitting and winning, indeed there’s actually none at all, a result that contradicts the prior work by Willis and call into question the way conventional hockey wisdom is often cited. I choose that phrase because conventional hockey wisdom has never been “just hit someone,” despite what a certain Conn Smythe quote might suggest. I think most coaches and analysts would tell you that the key to the game is less about knocking guys about, and more about picking your spots and making the most of the opportunities created. Obviously, a bad hockey team that hits a lot is still a bad hockey team. Maybe they don’t convert hits to turnovers, maybe they don’t transition well, maybe they just can’t put the puck in the net; at the end of the game, they still lose more often than not. On the other hand, a good team that hits a lot does all of these things pretty well, and so on. (As an aside, it’s also worth reiterating how problematic the hit stat is, in light of the results uncovered in Table 3. Say what you will about the fluctuating incidence of physicality in hockey, I have a very difficult time believing that the entire NHL decided, en masse, to lay 1,000 fewer hits than average in 2002-03. Certainly, I would advise caution in interpreting any results obtained using hits as a factor.)

I think the important thing to pull out of all this is that changing to a more or less physical brand of hockey likely won’t dramatically affect the outcome of your season. If a team wants to truly get better, then they need to succeed more at the fundamentals of the game — skating, passing, and shooting — and become more adept at reading the play and knowing when to take which action. Being better at those things will naturally put you in better positions to lay hits, if that’s your game (and it needn’t necessarily be), and allows you to take better advantage of the opportunities said hits create. I would suggest both to those who believe that physicality should be a top priority, and those who feel it’s unnecessary, that the truth of the matter is that what you really want are good hockey players, and everything else will follow from that.

The first thing that must be distinctly understood is that goaltending, more than any other position, requires both speed and power in movement. While goalie pads have gotten much lighter and less absorbent since the leather pads of yesteryear gave way to sleek, modern synthetics, over the course of a game, those things still get soaked in sweat and snow from the ice, and get heavy as hell, requiring a lot of force to move. On top of that, you have to move them very quickly: goaltender response times are often on the order of hundreds of milliseconds. This creates a number of problems, which I’ll deal with in turn.

First, force generation and speed of contraction are inversely related, on a roughly hyperbolic curve. This means that the faster a muscle contracts, the less force it can generate. This makes sense when you think about it: if you contract your biceps as fast as you can, you might be able to make a hell of a smacking noise, and cause something to move by transferring momentum, but you aren’t going to be lifting much. Conversely, when lifting a very heavy weight, you can only lift it very slowly. While goalie pads are much lighter these days, there is a base amount of force needed to move them, which limits how quickly a goalie can move. Since the force produced by a muscle decreases the faster it moves, and a goalie usually wants to move as fast as he can, in order to move a given object quickly (glove, pad, stick, etc.), he really needs to exert himself.

Second, a goalie’s movement must be precise. In order to get a glove on a puck, Dwayne Roloson has to time his arm movement so that his hand is in front of the puck as it arrives. If his hand is more than a couple of centimetres off course, he has to quickly readjust. Further, there’s positional recovery to consider: when Carey Price makes a kick save, he can’t just let his leg continue until it reaches the end of its motion, as Roloson could with his glove: he has to slow his leg down in a hurry and push himself back into position. This slowing and readjustment requires activating antagonist muscles (muscles with the opposite action to the “agonist” muscles; for example, the hamstrings are antagonists to the quadriceps) in a coordinated fashion, and adds to the energy demand of the save. Dr. Syme likens it to holding a dumbbell in hand and trying to retrace the path of an Etch-A-Sketch drawing: it takes a lot of energy to move a load around a tightly defined path.

Unfortunately, it’s not a simple matter of making a fast movement, for a couple of reasons, but in order to get to them, we’ll need to take a step back and look at some fundamentals of muscle physiology.

There are two basic kinds of muscle fibre: Type I, or slow-twitch, and Type II, or fast-twitch. Remembering what was said above about speed and force generation, we can say that Type I fibres are primarily useful for generating force but not quick movements, while Type II fibres are for quick movements and force generation; these are the ones we rely on for really fast, powerful movements. Slow-twitch fibres generate their energy mostly through oxygen-consuming aerobic processes, which deliver a steady stream of chemical energy in the form of adenosine triphosphate (ATP) which reduces their susceptibility to fatigue, while fast-twitch fibres generate their energy through glycogen-consuming anaerobic processes, which generate ATP in short but large bursts¹, which make them much more vulnerable to fatigue. You’d think at first glance that, because the Type II fibres don’t directly consume oxygen, that you’d be less out of breath after using them, but the glycolytic processes that generate the fibre’s energy come at a cost, generating several unwanted by-products, including lactate and acid. You know that “stitch” you get in your side when you run for a long time? That’s how you know you’ve gone into anaerobic territory. Anyway, in order to get rid of those products, you need… oxygen! So in the end, you still wind up breathing heavily. It makes sense, if you think back to the gym again: when you’re lifting that heavy weight, you may only lift it, say, six times, instead of lifting a light one ten or twelve times, but you still wind up sucking wind pretty badly.

So now we’ve established that by using glycolytic fast-twitch fibres, goalies wind up breathing heavily anyway, but what about “not simply making a fast movement?” Well, muscle fibres are activated, or recruited, in a specific order with increasing demands for power. Smaller motor units — collections of muscle fibres activated by a single alpha motor neuron — of slow-twitch fibres are activated first when the demands for power are low, because of their size and fatigue resistance; only after that, when we require more power, are the fast-twitch fibres activated. So in order to make that fast movement, a goalie has to be “set”: they need to tense up to a degree, co-activating their slow-twitch fibres so that they can more readily recruit their fast-twitch fibres when the time comes. For example, hold your arm out limply beside you and try to flick your hand out at something; now, try tensing the muscles in your arm then flicking your hand out to the same point. It should be faster, because your slow-twitch fibres are already recruited, so there’s already tension in the muscles, allowing you to get right to the quick movement. Order of recruitment is an important consideration, not only because it affects reaction time, but because it affects energy consumption: activating those slow-twitch fibres does consume energy faster than standing relaxed, and require greater replenishment. As an aside, it may also help explain why goalies who face a lot of shots tend to have higher save percentages than those of similar talent who face very few: not only is there the mental “readiness” element, but there’s also the muscular “readiness” element. Ender supports this notion from his own experience by saying, “as the muscles ‘cool’ they seem to stretch, so the more time you have between shots, the more it seems that it involves more energy to begin the motion.” Of course, the body would be poorly designed if there weren’t workarounds to the order of recruitment problem: reflex arcs try to deactivate the slow-twitch fibres while activating the fast-twitch ones, to reduce energy consumption and improve speed in cyclical motions, such as running; whether this particular process is relevant to the task at hand is a bit of an open question.

Somewhat related is the idea of stability. Stability on ice is difficult at the best of times, but when you have five hundred kilos of players flying at you, sticks flailing at a loose puck, it becomes imperative. Recall Newton’s third law, stated axiomatically, “to every action there is an equal and opposite reaction.” In order to throw out an arm or a stick for a save, the goalie needs some sort of contact point with enough friction to keep them from sliding away. Thinking of it another way, when in a post-whistle scrum, players need to keep their skate blades pointed in such a way that they don’t push themselves backwards at the same time they push their opponent. (Or thinking of it yet another way, consider the Magic School Bus’s frictionless baseball game.) Anyway, stability starts at this point of contact, usually the skate blades, and works its way up from there. Because stand-up goalies have gone the way of the rover and the two-line offside, where this really comes into play is during those goal-mouth scrums, when a goalie has to hold his ground against the onslaught. If, for example, a keeper has braced himself against a post, in order to keep from being knocked into the net, he’s going to have to activate muscles all the way from his calves, through his “core” muscles, the abdomen and back muscles, to his arms and neck if need be. Of course, during any movement they will need to do this, whether it’s holding off a scrum at the goal mouth, reacting to a shot from the blue line, or just moving around the crease. In any case, because the goaltender is (quite intentionally) not moving very far, and focusing more on force generation, they will be relying on the slow-twitch Type I fibres.

All this brings me to another topic which has to be considered when looking at energy needs: when a muscle is tensed, the blood vessels which supply oxygen and other nutrients can be occluded, causing them to move to anaerobic energy generation much sooner than blood oxygen levels would otherwise suggest. Another action that might cause unneeded anaerobic activity is called the Valsalva manoeuvre, in which one exhales against a closed airway. While it can be useful in certain circumstances to, say, “pop” one’s ears, when performing physical activity, it will cause a spike in blood pressure, followed by a compensatory drop in cardiac output, which eventually sorts itself out over the course of a few seconds. In physical activity, it’s most commonly encountered as a result of poor breathing technique while lifting weights, but it could also occur when playing goal, and trying to fend off crease-crashers.

We’ve now pretty much exhausted the ways a goalie can wear himself out. True, we haven’t discussed the limited skating a goaltender does, but to be honest, there’s not really anything novel to say about it. Instead, I’d like to turn our attention to recovery, which has a couple of different components. First, as previously stated, goalies make extensive use of the glycogen-burning Type II muscle fibre. Glycogen is a polysaccharide (long-chain sugar) form of glucose stored in tissue, particularly muscle tissue, for future use. This glycogen is consumed as a goaltender goes about his job, and after the game, it must be restored. After a good bout of exercise, it can take at least 24 hours to fully restore glycogen levels, depending on the extent of the consumption. If a goalie’s had a busy night, with a lot of shots, a lot of pileups, and even overtime, his glycogen stores are going to be very low; maybe not as low as a marathon runner’s, but a lot lower than the average weight lifter’s. Unfortunately, I was unable to pull up any specific numbers related to this; I can only go off what I can cull from my first-year exercise physiology textbook.

The other factor to consider is tissue damage, particularly muscle damage. The idea here is that, as you make use of various body parts to perform an activity, you cause microscopic stress damage to them in the process. For the most part, this is no big deal, because everyday activities just don’t do enough damage to be relevant: it heals quickly enough not to matter. When you heavily exercise, however, you start to really feel it. Heavy weight lifters, for example, will only do a small number of reps per set, and will wait several days between exercises on a given muscle group, for precisely this reason: too many reps at a submaximal level (i.e. a weight below the one-rep max, or 1-RM) will still cause enough cumulative damage to rupture a tendon or pull a muscle, so the tissue must be given time to regenerate. Of course, causing minor muscle damage is, ironically, the whole point of weight lifting, for without that stimulus, the tissue would never get stronger. Anyway, when a goalie plays, he will put stresses on his muscles, tendons, ligaments, and bones, and will need to recover from them afterward. If he’s working hard enough to exhaust or nearly exhaust his glycogen supply, chances are good that his muscles are going to be pretty shredded, and that he’s going to be a bit stiff in the morning, no matter what shape he’s in. Given that that’s the case, he needs time to heal up, and while no one muscle group has been worn out as much as our theoretical weight-lifter’s, they are all worn out enough that 24 hours’ rest probably isn’t enough, and that going back out there the next day for more than light exercises (i.e. practice) places the keeper at greater risk for injury. I imagine this is why you see so many more goaltender injuries than you used to, particularly groin injuries: the groin muscles are needed to pull the legs together, and are greatly abused by butterfly goalies. The wholesale movement to that style over the last 20 years, combined with the increased intensity and frequency of games since the Original Six era, when goalies played every game but teams travelled overnight by train instead of in the middle of the night by plane, would naturally result in a greater incidence of overuse injury.

From this, it’s clear that there are a number of compelling reasons why a goaltender should’t play in back-to-back games if it can be avoided: fatigue, dehydration, tissue damage, and fuel consumption all cause a player to be less than 100% for at least a day. As Dr. Syme said near the end of our conversation, “they don’t have the fuel in the tank and they’re not in as good of shape as they were the previous day.” As a result, they are far more susceptible to injury and poor play, a risk that coaches often aren’t willing to take.

Special thanks to Dr. Syme, as well as Bruce and Ender, for their contributions to this article.

¹ Strictly speaking, there are several subtypes of Type II fibre, which use varying degrees of oxidative and glycolytic processes, and act at correspondingly different speeds, but for the purpose of this article, we’ll consider all the fast-twitch fibres as a single group.

Last week, Ender jokingly suggested to me that maybe the Oilers’ losing was a good thing, because preseason success seemed to be a harbinger of regular season failure, and vice versa. It was a fun thought, and certainly, one look at the 2006 preseason should tell you where that idea comes from. On the other hand, it seemed a bit illogical: surely there shouldn’t be any relation at all between pre- and regular season results, should there? I mean, the good teams will probably still be good, and the bad teams will probably still be bad, but there’s a lot of room for slosh in a sample of only 5-8 games: the Oilers have started many a season firing on all cylinders in October and November before coming back to Earth in January, while the Flames have started all three post-lockout years with their skates tied together, and made the playoffs every time, winning the division in 2005-06.

It wasn’t an idea that I gave much further thought to until Tuesday night, when the Oilers got clubbed 4-0 by the Flames, and did so while looking pretty much like total shit the whole way through. So I decided to see if there was anything to this idea, and grabbed the last three years’ preseason data, fired that into Excel with the regular season standings, and checked to see what came out of the wash.

Part 1: Visual Inspection

Taking a page of sorts from LittleFury, I made the top 10 teams in the preseason, by points percentage, green, the next ten yellow, and the final ten red with white text. The teams are sorted according to the NHL’s own standings. The results are below.

While there is somewhat of a trend for good teams to clump a bit at the top, and bad teams to clump a bit at the bottom, there’s all kinds of spread here. There’s top five preseason teams in the bottom five of the regular season standings, and vice versa. You could maybe say that 2005-06 “looks” less messed-up than the rest, but I don’t think you can say that with any conviction, and I don’t think I can even honestly say that I see it, since I was spoiled by doing the second test before I got around to making those highlights.

Part 2: Linear Regression

After that, I did a quick linear regression to find out if there was any linearity to the data, and if that linear trend pointed in a given direction. The figure below shows plots for the three seasons, and trendlines for the same, as well as a line for the pooled data of all three years.

That would be a big, fat nothing. There’s a very small but significant (p = 0.016) correlation between preseason and regular season results in 2005-06 (R² = 0.19), which as I noted before, you might almost be able to see in the raw data if you squint really hard at the table, but the other two years are below 0.04, with no significance whatsoever (p >> 0.05 for each of them), with the three-year pool clocking in with an R² value of 0.07 (I ran out of time to check the significance, but I’d lay down money it’s not). Between that number and just looking at the scattershot nature of the data, it seems fairly obvious that there’s no real connection between preseason and regular season success.

I was going to do further statistical testing, but (a) it seemed pointless by this juncture, and (b) I couldn’t find anything that worked quite the way I needed it to other than — you guessed it — linear regression. So there we stand.

Limitations

It’s somewhat ironic that the greatest limitation of the study — the small sample size of the preseason — is also one of the reasons why there is a difference. I mean, five to eight games can easily deceive you in a way 82 can’t. While there’s all sorts of problems with even a full-season sample, it’s not nearly as problematic as a stretch that comprises 6-10% of a season. I said what I needed to say on this at the top of the post, so we’ll move on.

A second problem here is that I only have three years’ worth of data here. Obviously, pre-lockout data would complicate matters, due to the differing rulesets, but if I had to guess, I’d say that it probably wouldn’t make that much of a difference — the mean points percentage would drop a smidge, but otherwise the trend, or lack thereof, should probably be about the same — but even aside from that consideration, it’s not easy to find pre-season results, especially the further back you go. Yahoo! has 2003-04, but I would rather have all the data from the 30-team era rather than just the one year. The net effect of all this is that I can’t definitively say that the significant trend from 2005 is the outlier and the clouds of nothing from 2006 and 2007 are the reality, because it’s two years of one and one of the other, and because I haven’t run anything prior to 2005, but it passes the smell test, so I’m gonna go with it, at least for now. I’m not sure why 2005 was so special: it was power-play city that year, so that could be a reason, though I’m not sure why special-teams play would be any more significant, or any more likely to carry forward, than final results. It’s something that’ll require further study, though again, I’m not sure how to get a hold of that data.

The final and most galling limitation is the Bettman point. Yes, the sometimes-two-sometimes-three-point system rears its ugly head again, because it kept me from running a chi-square test on the data, which I kind of wanted to do as a third check. Since the chi-square test checks the distribution of the experimental data against a model prediction (in this case, the preseason being the “model” and the regular season beng the “experiment,” with the null hypothesis obviously being that the preseason predicts the regular season), I needed the two columns to have the same sum, which was not, of course, the case. I did a bit of fiddling with the numbers, including “percentage of points awarded,” but I couldn’t get anything that really worked well, so I eventually abandoned the pursuit, which is too bad, because it really would’ve completed the set.

Interpretations

Now that we’ve got all that out of the way, what can we actually say from this? Put simply, the preseason has no bearing on regular season results. You could argue that, depending on how a team played its last couple of preseason games, it might be an indicator of how the early season goes, but even that seems like a pretty sketchy proposition, when you consider what all goes into a preseason record.

For starters, there’s the rosters. Specifically, the rosters that frequently have little more than the minimum required number of NHL veterans (eight) in the first half, when coaches are usually more interested in development and scouting than winning. You cannot reasonably judge a team of 23 NHLers based on the work of up to 13 guys who might never see a minute of meaningful NHL time, and if they do, it likely won’t be in the tenure of the current coaching and management crew, given how long those guys tend to last in most NHL cities. This is also why I really couldn’t be bothered when the Oilers rookies went 0-2 in their own tournament, yet beat both the U of A Golden Bears and the ACAC All-Stars. It doesn’t involve players who will actually be deciding the games that matter, so why sweat it? Even later in the year, there’s enough non-NHL players involved that it’s hard to take the results as being indicative of anything; kind of like the last 20 games of the 2006-07 season.

Related to this is the schedule. The preseason frequently starts with crazy stretches like four games in five nights or five in six, to say nothing of the stuff they’ve been doing in Europe the last couple of years. Teams will often play split squads during those stretches, with minimal overlap between sub-teams, and certainly none over more than two consecutive nights. One team might have more vets than the other, and be an “A” team of sorts, while the other has more kids and scrubs, a “B” team. A-Teams, as a general rule, will clobber B-Teams, though on any given night, anything can happen. The results of both the A- and B-Team will be combined, since they’re all wearing the same shirts, so you have no cohesive whole to make your comparison with, and frequently less-than-fair competition to generate the results against in the first place. Granted, you don’t exactly have a cohesive whole during the regular season, either, with trades, signings, callups, reassignments, and injuries all tweaking the roster throughout the years, but it’s at least mostly cohesive, unlike the preseason, when most of the roster can change from one night to the next.

Next, there’s coaching. As noted above, training camp is a time for development and scouting. Coaches will do crazy shit like playing 19-year-old sophomore scorers on the penalty-kill, or break up established lines and add kids and minor-leaguers to the mix, for the sake of seeing what these guys have got, and if anything good comes out of the wash. I guess it’s the Yukon Cornelius approach to talent evaluation: you never know when you might accidentally strike gold while randomly throwing your pickaxe in the air (see: Thoreson, Patrick; Gagner, Sam). Anyway, when lines are out of whack, kids are playing tough minutes, and guys who don’t normally kill penalties are out there doing just that, you get results that are in no way indicative of how the team is actually going to play when the games count. How Craig MacTavish coaches against the Florida Panthers in September is nothing like how Craig MacTavish coaches against the Minnesota Wild in March.

Finally, we have the players themselves. Guys get rusty over the summer, and need time to get the system back in their heads and the chemistry back with their linemates. They’re probably going to be going for a slow burn, to ease their way back into things, so they don’t hurt themselves by doing too much, too soon. Coaches don’t want key players to get hurt, either, something the Oilers have learned from past experience, and something the Penguins are learning now with Gonchar gone for most of the year. Sure, players are going to want to be at 100% by the time the season starts, but if they play their first preseason game at 60% or 70%…does anyone really care? Obviously, if you lay an egg like the Oilers did on Tuesday, no one’s going to be too thrilled with it, nor should they be, but it’s hardly a sign of the Apocalypse on Ice. Also, much like during the regular season, you have to trust that after a horrible effort, the professionals will be able to get their shit together and do it right next time.

Conclusion

So what does all this mean for the Oilers, in the end? Absolutely nothing. Maybe they’ll be good. Maybe they’ll struggle out of the gate, then turn it around. Maybe they’ll be Godawful. No one can know for sure until the games are played, though we all have our ways of making educated guesses (and speaking of, I guess I have more work to do this weekend). What this post should prove, however, is that preseason results shouldn’t be one of those ways, or at the very least should be used with extreme caution, since you could probably throw darts at a chart of the 30 teams and be just as likely to pick out the final results from that as you would from the pre-season table alone.