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Originally Posted by butterfly
Yeah, I just hope they release the raw data so anyone with time and interest can analyze it. It would help us further discern what's valuable in order to prevent and score goals.
Do they only track speed and identify the player, or can we tell where the puck and everyone is on the ice at any time?
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They have data for all players, plus puck
So they can start to actually measure things like traffic and see how significant they are
(so if you create a pyramid or ‘shot cone’ by drawing a line from puck position to the corners of the net, and count people in that area, it adds context with regards to the challenge for the goalie, which current models lack)
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Traffic grades out higher when players are within one foot of the straight line between the puck and the chip in the goalie’s sweater (which is being called “possible vision obstruction”).
Then they’re considering how much defensive pressure a shooter is under. They can do that by looking at the six foot radius around each player's jersey chip, and seeing how much (or how many) defensive player chips are interfering with an attempt. To me, this is an area current chance data hasn’t had a chance to fairly evaluate.
Here's an example of a fairly low stress play on an unpressured shot that gets saved – like it’s a really unimpressive clip, I get that – but it has a sneaky high projected goal rate just due to the amount of bodies the goalie has to look through.
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Thing is, they should be doing next level data analysis with machine learning - the conclusions they will be able to draw will likely be based on having the vision to articulate the problem plus the computing ability