Have things changed, or it's too soon to change, or they're still pretty much the same now? How does all the revolutions on the, uh, you know, all the AI technology, everything, does that make people want to share more or share less? So what's the situation there now?

Yeah.

It's-- It is a difficulty that has been, I mean, certainly like a regret of mine, I guess, for, for tennis analytics in general, that there is this perception within sport industry that, um, making the state-of-the-art data, which at the time that, that I started working for, for Tennis Australia, which was my first role in sports, the, the state-of-the-art was, was tracking data.

And there's the perception that if that were to ma-- be made open, that organizations would lose their ability to, to benefit from the commercial potential that that data has.

But I actually think it's the opposite.

If you do see like examples of other sports that have been more willing to share, particularly with the academic community, that they have seen much more advance in the kind of questions and methods that are getting applied to that data.

So, um, I had mentioned before about the XY Hoops group.

So even if two teams are playing against each other purely based on these algorithmic, uh, determinations, uh, that-- I don't think that's gonna really take away from the sport because, uh, you know, you have different sets of players, different skills, different random factors that are gonna happen in the actual implementation of the play that, um, you know, still you're going to have, I think, an enjoyable experience and I think, uh, it's not gonna necessarily, uh, entirely determine the outcome.