The 07/08 Hot Streak, Part I

Oilers management made a series of foolish decisions after the Stanley Cup playoff run of '06. And it never really stopped.

The hot streak at the end of 07/08 was a bright light, though. The kids were going to save us, weren't they?

In the cold light of day we were wrong. Hell, in the warm light of the evening, we should have known better. This post from the spring of '08 was widely pshawed at the time, at least by Oiler fanboys. But history tells us that we had it in a nutshell right there.

The thing is, all the moves of the summer of '08 were widely applauded by the Oiler fanbase. Same as this summer. Let's have a closer look, shall we?

Starting with the fourth line in the back third of the season:

They were terrific. Brodziak centering Glencross and Stortini. Now, as Dennis was quick to remind us at the time, they weren't playing against top-six opposition and they weren't being asked to start in their own end a lot. Still, results be results, and this was a terrific fourth line for the Oildrop. They outscored their opposite numbers by a wide margin over this stretch.
(image cropped from the post linked above)The Oiler numbers are just for the hot streak (about a third of the season), the four players below were the guys with the best on-ice shooting% for the year as a whole. They also happen to be pretty terrific Fenwick# guys, so it is extraordinarily likely that all helped their teams outchance the opposition to a large degree. As it happens, they're all quite famous as well. They are left here for perspective.

Back to point:

* The other two members of the great Oiler 4th line had brutal underlying numbers before Glencross arrived. They had dramatic improvement afterwards.
* In spite of playing mostly with Brodz and Storts, Glencross saw dramatic improvement in his underlying numbers on those occasions when he had a different gig. That's why there is such a wide spread in Fenwick# between the three. The implication is that Glencross was driving the bus, the other two were just riding it. And all three were just plain lucky as a group.
* Without the crazy, Marioesque shooting percentages, that 4th line we reminisce about wasn't all that spectacular. To paraphrase Erik Cole during a hot streak "My scoring chances are crossing the line more now. Before they weren't". Not a great narrative, but wonderful truth.

Now Brodziak can win faceoffs and is a decent PK player, and Stortini can fight, plus he is undeniably a good guy. Still, the Oilers bet on the wrong horse here. Spectacularly so. They had a good player making bad players look decent ... and they let him go.

On-ice shooting% says almost everything about a player's current popularity with radio talk show callers, and explains most of their recent counting number success. Unfortunately, it doesn't predict future performance for shit.

Early on it was suggested that Glencross was asking for huge money and term. It turns out this wasn't the case, or at least wasn't his final negotiating position. He signed in Calgary for a bargain later in the summer.

I should restate that the moves of Lowe and Tambellini, at the time they were made, were very popular with the fanbase. They were the next year, too, And the year after. They still are this summer. I believe it was the middle of the summer of '08 when Tambellini began his second term as Oiler GM. He's in his third term now, we all know that's the critical one.

Next up, the Kid Line. Brace yourself for the same pattern folks. And, by the looks of things, keep bracing yourselves for another couple of years.

Shot Location and Shots AT Goal in the 1972 Summit Series

Sometimes I think we NHL Internet statzis don't give enough credit to the some of the old school NHL coaches and managers.

Below is a scan of the shot locations for the first period of the final game in the 1972 Summit Series. The data was recorded by long time NHL statistician Ron Andrews. It was the property of John Ferguson, an assistant coach for Canada, and was auctioned off, along with the other game sheets for the final four games of the series, last December. Click to enlarge.



I don't know what the shorthand means, nor do I know how this information was used. Surely missed and blocked shots are included, otherwise the totals would be far too high. I also don't know what the Soviets were recording.

And here is a sample of the player summary stats. The SAG column is shots AT goal. So the player seems to be getting credit for shots that missed or were blocked. Hrmmm, maybe we've been giving those Buffalo Sabres folks too much credit. Again, click to enlarge.

The Importance of Quality of Competition

Hockey talk has come a long way in the past few years. It wasn't long ago that the notion of context of ice time, especially quality of competition, was considered to be a nonsense promoted by wacky Oiler fans. Even the pure math folks on the Internet thought it was folly. MC79 would routinely visit a Flames fan message board and argue the point. There was much mocking and derision going both ways.

It's not that way now, though. This is thanks largely to hockey play-by-play man Jim Hughson. Not only does he frequently talk about the match-ups on the ice, he gets them right. And nobody has done more to promote the notion on the Internet than Gabe Desjardins, this through the QUALCOMP numbers at his terrific hockey statistics site.

I thought it was time to look at just how much of an impact QUALCOMP had on a player's results. To do that I'm going to split the 09/10 NHL season in half, and look at change of results for the players from one half to the next, and compare that to their change in QUALCOMP.

Desjardins' QUALCOMP is similar to what is shown in this post of a few weeks ago. The head to head EV shifts table from that post is replaced with head to head 5v5 ice time, and that scoring chance +/- list is replaced with on-ice/off-ice +/- rate. That's his measure of player value. Plus Gabe uses only one iteration. Then he subtracts the result from the original and voila ... QUALCOMP.

It would be a bitch to gather all the head to head and on-ice/off-ice data. But once you had done that, calculating QUALCOMP is just three or four lines of code in most programming languages. Simple stuff, really.

The quality of competition metric I will use here is a bit different. Gabe's QUALCOMP only compares players to their teammates, I need a global number. Also, Gabe doesn't given season and quarterly splits for his data. And I'll need both here.

For those that care; I use Fenwick Numbers for the player value (our best proxy for player scoring chance +/-) and total shots at net by either team, in lieu of head to head ice time. Zone start is also factored into the opponent's value. I also run several iterations, in this case about 30. This is because good players tend to play a lot against good players in this league. So, for example, you run the numbers for Zetterberg and realize that he played a bunch against the other team's best outchancing players. So he's even better than his Fenwick suggest. Everyone who played against him deserves larger props. you bump his value a smidgen and run the numbers again. Same for everyone else in the league. Rinse and repeat until the results stabilize.

I chose guys that played regularly in both halves of the season. That's 412 players, about 14 per team. Obviously far fewer for teams like the Oilers, who were devastated by injury and illness this past season.

The results:

Comparing the first half of the season o the second half.
The relationship of change in Vic's Qualcomp to change in Fenwick ratio:
Pearson's r = .37
variance in player results change: 13,186

Just to keep our lives simple, we'll pretend that the data is distributed normally, so r² * total variance ~= variance attributable to Vic's Qualcomp.
variance in player results change attributable to Vic's Qualcomp: 1,853


Now Pearson's correlation doesn't mean a whole lot unless we understand the role of chance in the game.

Some of that change in players' Fenwick% is down to chance alone. We see that in the games, and it's explicit if you've been following any of the scoring chance recorders on the web.

If we had access to a million parallel universes the element of luck (chance variation) would evaporate, and Pearson's r would wander up to about .71 and stabilize. But we don't.

We do have access to the first quarter of the season and the last quarter of the season, though. That works out to about half the average ice time per player, and the element of chance would be double in that sample.

So we run that:
Pearson's r = .20
variance in player results change: 23,024

Subtraction yields the variance component attributable to luck in the first study and he non-luck element:
luck component variance: 9,837
non-luck component variance: 3,349

THE FINAL TALLY:
Vic's Qualcomp explains 55% of the change in player's Fenwick results that is unaccounted for by luck.

It would be larger if my model were better. For starters, scorer bias and score effects in the games could be accounted for.

On a team by team basis, Vic's qualcomp has a strong correlation to Desjardin's QUALCOMP, usually around r = .8. And these measures are built from completely different bricks. They are both built with reason, that's the only thing they have in common.

My methodology, crude and simple as it is, did weed out most of the injury effects, they are obviously huge for some players as well. Linemate quality is obviously going to account for a big chunk of the remainder, I think, though that covaries negatively with quality of competition (when you get better linemates, more often than not you're also going to be playing against better opposition).

Bottom line: If you ignore quality of competition, you do so at your own peril.

Next season I'll show the change in Vic's Qualcomp over season halves. The top 100 players in qualcomp change will, collectively, see their Fenwick results (or scoring chance results if we have them) move the same direction as their quality of competition. Nothing can stop it. If you can find a denier who likes to wager, prop them 3 to 1 odds that most of that Top 100 will see their results go the way of their Vic's Qualcomp. Or Desjardins' QUALCOMP for that matter.

The odds on that wager are about 400 trillion to one in your favour. It's unlosable. Props any higher than 3 to 1 will just scare off the punter, though.