Monday, May 2nd, 2016

Tyler and Dave


Tyler Dellow is one of my favourite bloggers. I’ve read him for years. If pressed to explain why when I don’t hold much truck with hockey analytics, I say something like this, “He’s got an interesting point of view and he writes well. I don’t think the data he uses has anywhere near the validity that he thinks, but at least it is different. Like most fans, I’m beyond tired of the usual narratives most of the mainstream media attach to the players and the teams. I take different bullshit over the same old bullshit.”

In a recent post Tyler is all over some comments Dave Nonis made about the use the Leafs make of hockey analytics. (They don’t make much of them at all. Mirtle has more.) Tyler begins with:

For reasons I’ll never understand, they never really have a coherent advocate of hockey analytics on these panels – at most, you get some sort of a nebbish character who’s intimidated by hockey people. At worst, you get a guy who knows less than nothing about the topic on the panel, saying things that mean nothing. The result tends to be pretty useless to a listener, I think – you don’t get a discussion about the insights that can be drawn from and flaws of hockey analytics, you get silly criticisms leavened with ignorance.

No doubt, but to be fair to the nebbish character it is difficult to concisely state the chain of logic that leads to the insight without stumbling over problematic premises. And to be fair to Dave Nonis, there is no single big flaw in that quant’s logic. It is an accumulation of smaller problems so Nonis can’t make a coherent case either. The result is the quant throws out something that is incoherent to most fans and the Dave Nonis character seizes on one of the small problems and blows it all out of proportion.

Nobody is well served. The nebbish character does not put Tyler’s case very well, and Dave Nonis does a bad job explaining my position, which goes something like:

Corsi is not much different than the plus minus, a statistic that has been around for a long time. It uses attempted shots as a proxy for goals. The problem with the number is that credit for the goal (or attempted shot) is arbitrarily spread among all the players on the ice and the individual player statistic is hopelessly polluted by the quality of the team and the player’s role on the team. There is very little real evidence that Corsi actually measures individual player quality any more than the plus minus does. The narrative quants attach to the number – that it indicates whether or not the player drives “puck possession” – is nonsense.

Even if Dave Nonis thinks there might be something to examining Corsi numbers at the team level, there is very little he can do with the data. The only way to improve the shot differential is to become a better team and he’s already trying to do that. He’d surely prefer more shots in every game, but in the meantime he can take some comfort from the fact that for some inexplicable reason the Leafs have been a far better team when they are outshot for the past four seasons.

Most of the advanced stats are about shots, which are an outcome, not part of a process. To say “A team needs to get more shots (or give up fewer) to win more games” isn’t really different than saying “A team needs to score more goals (or give up fewer) to win more games.” It is usually true, but it isn’t helpful. No matter how the game’s shot statistics are parsed, none of them describe or measure the process that produces the shot or the goal. They do not describe hockey.

Hockey is a team game. On offense, players have to coordinate their play to exit the defensive zone with the puck, move quickly through the neutral zone, enter the offensive zone, and move the puck around the zone until somebody has a chance for a shot. A team that does those things well will get shots and goals. Defense is precisely the opposite. Players coordinate to mount a good forecheck to prevent easy exit from the zone, to harass and slow the play through the neutral zone so the defense can hold the blueline and force a dump-in. A team that does those things well will be hard to score on.

The Edmonton Oilers are not a lousy hockey team because their Corsi numbers suck. They are a lousy hockey team because it is easy to move the puck against them, and they do not get out of their own end very well. Their transition game isn’t good enough in either direction. When they do generate speed through the neutral zone or gain control in the offensive end, the young stars on the team can make some hay, but the Oilers don’t do either nearly often enough.

That is an opinion. It is unsupported by data, because there is no data that measures the parts of the game that either lead to a shot or prevent one.

According to Mirtle:

So while other teams like the Minnesota Wild have made enormous strides towards improving their even strength play at least partly because of their use of analytics and a buy-in from coach Mike Yeo, Toronto isn’t close to attempting a similar, data-driven shift in ideology any time soon.

I don’t think there is any evidence that the strides made by the Wild have anything to do with their use of analytics. Yeo is pretty vague about it, sounding pretty much like the Canucks on the subject. (Very important to leave no stone unturned, they say. We look at everything.) Nonis would probably be better off with his critics if he pretended he thought it was important stuff.

Me, I think the Wild improvement is mostly due to stronger goaltending and better players playing better. Yeo’s willingness to accept more risk defensively might have something to do with it, too, but teams make that kind of choice all the time. If there is an advanced statistic that informs that kind of reward vs risk assessment I have not seen it.

A Billy Beane approach is paying off in Minnesota? I call bullshit. Different bullshit, to be sure, but bullshit all the same.

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