24 May 2009

What Constitutes an Elite Playoff Performance?

When I did the Wings/Ducks series over at Cycle Like Sedins, I did a post examining Chris Pronger's reputation as a Wing-killer.  This post was missing a couple of things, in retrospect.  It lacked a comparison of Pronger's stats during his time as a Wing-killer versus his career playoff averages, and more important, it lacked context in terms of what constituted a good playoff performance.  So I'm going to attempt to gather some information here to use as a sort of gauge for a future series of posts on other well known Wing-killers, to see if there was any sort of improved performance against the Red Wings, or if the reputation that some players have is more myth than reality.  As these posts will involve looking at some older box scores, where a lot of rate information is not available, I'm going to keep it pretty basic on what constitutes success, at least for now.  Points per game (PPG) and +/- will be the primary metrics here.  Obviously, neither of these stats is perfect, but hopefully, they'll give us some sort of context for looking at other player's performance.  

As most of the players, teams, and situations I am interested in have been in the Dead Puck Era, which also coincides with my becoming a hockey fan, I'm primarily interested in what the numbers are for this period of time.  I'm setting the Dead Puck Era as having started with the 1994 playoffs, where the Devils were a serious contender for the Cup (and won the next year).  Getting the extra year in there should also hopefully widen sample sizes, allowing me to come up with more accurate numbers for what constitutes a good playoff.  If I want to look at things further back, I might have to update this, but for now, I think it works.   

(Includes Forwards, Defense, and Goalies)
All data as of May 25, 2009 14:00 MST

≥1.35 PPG = 2 players in this range (2 players at this range or better)
1.34 - 1.15 PPG = 6 (8)
1.14 - 0.95 PPG = 17 (25)
0.94 - 0.75 PPG = 40 (57)
0.74 - 0.60 PPG = 95 (152)
0.59 - 0.50 PPG = 76 (228)
0.49 - 0.40 PPG = 87 (315)
0.39 - 0.30 PPG = 149 (464)
0.29 - 0.20 PPG = 159 (623)
0.19 - 0.10 PPG = 183 (806)

Now, for a bit of a picture for defensemen specifically, let's exclude the forwards (and the goalies too, I guess).   

All data as of 25 May 2009 14:00

≥1.0 PPG = 1 player in this range (1 player at this range or better)
0.99 - 0.80 PPG = 0 (1)
0.79 - 0.70 PPG = 6 (7)
0.69 - 0.60 PPG = 10 (17)
0.59 - 0.50 PPG = 15 (32)
0.49 - 0.40 PPG = 24 (56)
0.39 - 0.30 PPG = 59 (115)
0.29 - 0.20 PPG = 52 (167)
0.19 - 0.10 PPG = 92 (259)

For the curious, the one huge outlier here is Brian Leetch, apparently, whose PPG average is actually right in line with his career average.  Should be interesting to compare specific performances against these numbers.  I haven't updated Pronger's numbers as a Wing-killer, but I do remember that prior to 2009, in his time as an elite defenseman in the NHL, Pronger was averaging 1.0 PPG against the Wings in the playoffs.  That's pretty impressive for a forward, much less a defenseman.  

17 May 2009

Home Ice Advantage - Conclusions

In my last post, I explained my preliminary guesses of what we would see in the data collected by this spreadsheet.  First, I expected to see the home-ice winning percentage (HIW%) peak in the first round, due to home teams having more advantageous matchups, and that the HIW% would go down as the playoffs moved on.  Secondly, I expected the Eastern Conference to have a higher HIW% than the West, in large part because of the difference in styles between the conferences.  I anticipated that the more conservative, defense-oriented style of the Western Conference would lead to more upsets, as its easier to beat a better team in a 1-0 or 2-1 game, than it is when you get into a shoot out.  

Well, I was right on the decreasing HIW% through the Conference portions of the playoffs.  That one was pretty easy though.  I was completely wrong on the conference HIW%'s though.  The Eastern Conference HIW%'s were pretty dismal though, dropping by round from 57.7% in the quarterfinals to 46.6% in the Cup finals.  I can only come up with a couple of explanations for the unexpected Eastern HIW%'s.  

The first obvious explanation is that in the West, teams travel much further.  Every Eastern team plays in the Eastern Time Zone,  but the West plays across Eastern, Central, Mountain, and Pacific.  This creates jet lag, which may lead to worse performances for travelling teams.  Eastern teams do not have to deal with this, and so the visiting team doesn't enter the game at a disadvantage due to fatigue from all this travel and jet lag.  This may indicate that home ice advantage is not necessarily the product of something the home team or the home team's fans are doing, as much as it is a product of making the visiting team travel to you.  

Another explanation would be the differences in environment you see when you move between cities.  The Western conference has a much wider variance in terms of climate and environment that teams must go through.  As a personal experience, having moved from the flatlands of Michigan to Denver, CO, I can definitely attest to the effect of higher altitudes on someone who isn't used to it.  Of course, a professional athlete is in much better shape than myself, but some effect has to exist there.  Moving across greater climate differences may also be a part of this effect, at least for a couple of teams like the Avalanche.  

Another possible explanation that I can think of, but I'm not sure I believe in, would have to do with the West's focus on defense-oriented hockey in conjunction with getting the last line change at home.  The idea would be that when you're talking offensive-oriented hockey, matchups become somewhat less important, meaning that having the last change on home ice would be less important.  If you're playing a defensively conservative style, having the last change may be more important to help you effectively shut down the opponent, meaning home ice becomes more important.  I'm not sure how much I believe this, but I can see how it might have some sort of effect.  

One possible conclusion for the SCF HIW% data in particular is that because the East does not have as high of a HIW%, more upsets are occuring, allowing lesser teams to occasionally overcome better ones.  If this is allowing lesser teams into the Cup Finals than the West allows, then we are simply seeing the result of a more effective "weeding out" of weaker teams in the West over the East, creating a Stanley Cup Final where the Western representative is stronger than the team that managed to sneak through a less demanding East.  However, this would lead me to expect the West to have won more Cups over this time period than they actually have.  

These conclusions seem to point to the West as being the stronger conference, in large part because the Western teams have extra obstacles to overcome, making the gauntlet they face to reach the Stanley Cup a bit harder.  More analysis, particularly on a team-by-team and series-by-series basis, could probably confirm some of these conclusions, or at least support some of them.  Perhaps I'll take a look at that sometime in the future.  I'm definitely open to other ideas and arguments about any of this information, so feel free to pile on in the comments.  

16 May 2009

Home Ice Advantage - Examination

It's generally known and acknowledged that over the long term, all things being equal-ish, the home team will win slightly more games than they lose.  Off the top of my head, I would imagine the home-ice winning percentage would probably be somewhere between 55-60% in the playoffs.  I was going to compile this data for another post I was going to do anyways, where I was mostly only interested in straight league-wide winning percentages anyways, but as I began compiling the data, I began to wonder about what trends might be seen in the data, on a per round basis, and more interesting, on a per-conference basis.  

My personal expectations were to see a higher than average home-ice winning percentage in the first round, for the obvious reason that in the first round, you usually see the biggest mismatches in terms of good teams versus bad teams.  Thus, the good team (who has home-ice advantage) should usually win, meaning they will more likely collect those wins on home ice.  n subsequent rounds, I expected to see this drop to a level more in line with the average, or maybe even slightly below average, if the average was pulled up too far by the large number of first round games, in which home-ice advantage would be more apparent.  

As for a per-conference viewpoint, I wasn't entirely sure how this would work.  I have only been watching hockey for the last 14 years, which also has coincided with a general rise in power in the Western Conference versus the Eastern, as well as a definite distinction in styles.  However, this spreadsheet goes back 22 years.  I expected to see the Eastern Conference have a slightly higher home-ice advantage, at least in the earlier rounds, based on my own anecdotal observations that the West plays a considerably more tight-checking and defensively-oriented game than the East over the time period of my being a hockey fan.  I'm guessing that the conservative style of the West is more condusive to the occasional upset, than attempting to offensively out-gun your opponent.  Over time, I figured this should lead to seeing more upsets in the West, lowering the home-ice winning percentage for the West.  The success (at least in the West) of such teams as the 2003 Ducks and 2006 Oilers would seem to support my theory, at least on the surface.  

All data is through the 2009 Conference Semifinals.
HIW% = Home-ice Winning Percent

Total Playoffs
NHL HIW% = 56.0% (1043 wins / 1864 games)
Western Conference HIW% = 57.3% (533 wins / 931 games)
Eastern Conference HIW% = 54.7% (510 wins / 933 games)

NHL HIW% = 57.6% (586 wins / 1017 games)
Western Conference HIW% = 57.5% (295 wins / 513 games)
Eastern Conference HIW% = 57.7% (291 wins / 504 games)

NHL HIW% = 55.5% (272 wins / 490 games)
Western Conference HIW% = 57.0% (138 wins / 242 games)
Eastern Conference HIW% = 54.0% (134 wins / 248 games)

Conference Finals
NHL HIW% = 51.5% (124 wins / 241 games)
Western Conference HIW% = 55.9% (66 wins / 118 games)
Eastern Conference HIW% = 47.2% (58 wins / 123 games)

Stanley Cup Finals
NHL HIW% = 52.6% (61 wins / 116 games)
Western Conference HIW% = 58.6% (34 wins / 58 games)
Eastern Conference HIW% = 46.6% (27 wins / 58 games)

I expected to see HIW% decrease as the playoffs continued, because you would see less one-sided matchups as the playoffs went on.  In the West, this effect was slight, dropping only only from 57.5% to 55.9%.  The slide in the East was much more dramatic though, from 57.7% down to 47.2%.  I really have no explanation for this.  Figuring this out might be a little tricky.  

The SCF winning percentages seem to reflect two things in these results.  First of all, the West has been the better franchise in most head-to-head matchups for a significant amount of time in this study.  Of the 22.5 playoff seasons we're looking at here, the West has won 12 cups, or 12/22 (54.54%).  The West has not won a lot more Cups than the East, but in those Cup wins the West has completed 4 sweeps of the SCF, versus only 2 for the East.  Secondly, whatever the reason is for the Western HIW% being higher than the Eastern HIW%, this may hold true in the SCF, giving the West a significantly higher HIW%.  

I'm working on some conclusions to draw from this data, and should have those conclusions up soon.  Feel free to offer what thoughts you have on this data in the comments.  I think the Eastern Conference data is particularly interesting.  

15 May 2009

Home Ice Advantage - Preliminaries

I just uploaded a spreadsheet to Google Docs, taking a good look at home ice advantage trends throughout the playoffs.  My spreadsheet reaches back to the 1987 playoffs, which was the first season the NHL went to a playoffs consisting of four best-of-seven series.  I have the data broken down into numbers by round, as well as splits between the Eastern and Western conferences for each round, along with totals for each round, each playoff, and for the total time period.  For the finals, I just called games hosted by the Eastern representative as the Eastern home games, and the same for the West.  You may notice that the 1988 finals has 3 games played in the West, and 1 in the East.  This was due to G4 in Boston being stopped for a power outage, with a tie score, and they resumed G4 in Edmonton, in what should've been G5.  

There's a few things I plan on doing with this data, but for now I thought I'd just stick the spreadsheet up along with my methodology, which I believe should be just fine.  After tonight's game 7's, I could definitely stand to crash.  I should be able to get some conclusions about this data up in the next couple days, as well as use it to support a couple of ideas of mine.  Plus, having it up and easy to grab makes it easy for me to play with it at work too.  

Data for this chart was compiled in large part from Wikipedia's list of NHL seasons, and for the two missing years, I had to compile the data from hockey-reference and the Hockey Summary Project.  

Per the Hockey Summary Project: The information used herein was obtained free of charge from and is copyrighted by The Hockey Summary Project. For more information about the Hockey Summary Project please visit:




14 May 2009

Whats In A Name?

Did you know:  Almost every single good name for a blog has been taken?  Its true.  And most of those blogs haven't been updated in years.  I'd been trying to come up with a name for this blog for a little while now, and I finally got it last night.

Last night I was in the shower after playing hockey, and I was checking out this sweet bruise on my arm from this douchebag's helmet after I decked him.  I was mentally comparing it to other bruises I've taken from blocked shots, and the thought occurred to me that sacrificing your body is perhaps the greatest part of this game.  

Anyone who has played the game knows that you show off your bruises like badges of honor.  A big bruise on your belly is like a big flashing neon sign that says "My heart is THIS big!"  Football is the only other US sport that can rival hockey in terms of pure physicality, but even in football, you don't see guys deliberately sacrificing their body on the same level.  There is nothing in any other sport to match the blocked shot.  More than anything else in the game, laying down in front of a rubber bullet exemplifies the commitment and the heart that makes hockey great, on every level from youth to adult recreational right on up to the NHL.  

Naming a blog after one of the single most admirable aspects of the game has gotta be a good start, right?

Welcome to Sacrifice The Body!

Thanks to James O'Brien giving me the blogging bug (I hear its contagious), here I am, with my very own blog.  Allow me to introduce myself.

I'm Joe.  I lived in Michigan all my life, until 2008, when I moved to Colorado, in an attempt to find a place where the weather didn't suck and the economy was half-way decent.  For sports, the only ones that count for me are football and hockey.  As a Michigander, I'm obviously a Wings fan, though I do root for other teams, and more than anything, I am a fan of hockey in general (though not necessarily the NHL).  Further, hockey and the NHL in general are far more interesting than just another blog about how great the Red Wings are (or for the rest of you, how much they suck).  

As such, my general intent with this blog is to discuss the NHL in general, though I will certainly be doing certain things that are more Wing-centric.  In fact, one of the series of posts that I'm planning as a Wing-centric thing is actually looking at the performances of renowned Wing-killers like Adam Deadmarsh and Chris Pronger, so I think even you Wings-haters will find something here to read.  

If you looked through my own bookmark folder of hockey blogs, you'd find a lot of sites that do statistical analysis.  I certainly won't be approaching levels of super-advanced statistical analysis like Tyler over at MC79Hockey, but I'd like to think I can do something along the lines of some of the things James Mirtle does, or even some of the stuff the guys at Battle of California do in between cartoons.  That's not to say that everything here will be heavy on the numbers, but I'd definitely like to do some of that.  

We'll see where we go from here.  Hopefully you'll come along for the ride.