Tracking the match at 50 Hz

12:09>> This is this is fascinating. So if I'm if I'm understanding you both correctly, there's a there's an initial there's almost like two layers to this, right? The initial layer is taking you know multiple pieces of context which is being identified as the threat threat metric and that's being taken every frame meaning basically every some time period you know 500 milliseconds a second what it might be >> it's 50 Hz the tracking data that we have. So 50 Hz. Okay. Incredible. And then so you use that as sort of the base and then that change over time and sort of basically a little bit of an algorithm on top of that is how we then create what we sort of define as momentum which is a combination of all

12:50these contextual layers combined. Yeah. Exactly. And how they are sort of eb and flow over a time period. That is that is very interesting. And I think one of the things um Juan especially you brought up there as well is um that there are so many points by which the data can be captured, right? So can you guys actually talk a little bit more about between passes, player movements, other match events which have to be tracked in real time which is an incredible processing challenge independent of just the actual data analysis challenge. But is it you know computer vision? Is it optical sensor data? like how does this sort of uh mesh of sensors really work

13:33together? >> So I'll give you for for momentum first and foremost it's purely tracking data. There is no event data in it whatsoever.