Quote:
Originally Posted by CorsiHockeyLeague
This seems like the issue is defining a "better player". The model developer is saying, look, we have thousands and thousands of shots of data. X% of shots in this area near the slot result in goals, Y% in shots over here on the half wall result in goals, and we can see, compared to a replacement level defenseman, where players playing against Darnell Nurse take their shots from, and how many they get. We can adjust that rate by looking at where they get those shots when he's playing with teammate A, B, C, D by looking at their own individual results when playing with or without Nurse on the ice. We can do the same for opposing players, normalizing by how good they are at getting high danger shots, and the volume of them, against other competition league wide. We can then factor in things other data we have access to, such as turnovers, possession exits, completed passes out of the zone, to factor in how those affect the frequency and dangerousness of chances given up by his team when Darnell Nurse is on the ice, again adjusted according to how good his teammates are at those things and how good the competition he plays against is at securing turnovers and preventing controlled zone exits. And taken together, all of those things tell you a lot about whether Darnell Nurse is good at playing defense or not.
I gather that what you are saying is that those things can't actually tell us much that's useful about whether a player is good at defense. If so, I guess that's where we'll have to disagree. I think those things (particularly shot volume, shot location and the ability to get the puck out of the zone in transition) are the most important skills and outcomes when it comes to keeping the puck out of your team's net. I base that view on a large amount of analysis that has been done over many years by a wide variety of analysts.
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I think that number of variables and the number you can't measure (coach system, goalie preferences, etc) is what leads to the concern with models.
I think these models are all good and a step up from what we've had before but their is still a ton of learn and some things that will be impossible in hockey just because its extremely fast and fluid compared to other sports.
Back in the early days of baseball metrics - two of the big conclusions they had was don't pay for relievers and defense doesn't matter much. Now you've got teams like the Rays who are extremely focused on defense and relief pitchers because its the cheapest way to be competitive. Its always a moving target with these models.