Ryan O'Hanlon

So you're limited, like there's no scouting benefits to data in international soccer.

While that's kind of the main benefit of data analysis in all sports is like figuring out who's actually good at the sport.

So that doesn't apply as much here.

And so I think with the data for the games in particular, I think there's a very real question about how actionable or useful any of that data will be.

Because of one, what is the data exactly?

Two, how able is anyone at any of these federations to quickly model this data in any real way connected to being predictive?

And then three, like the World Cup, as much as we hate to admit it, it's very small sample size in an incredibly random sport.

So extracting signal from noise, I think, with 2000 data points would be very difficult as well.

Yeah, I think, you know, coaches have a very interesting place in soccer where they're kind of viewed as these all powerful figures, but also soccer coaches have the least amount of power of any coach in any sport because the half starts and then it ends.

You're allowed to make subs, but you can yell from the sidelines, Ryan.

Yes.

And I feel bad for whatever wing player is playing on the same side of the field as his coach's bench.

You know, it's always better to be on the other side where you just can act like you can't hear what he's saying.

But I think like I have a hard time seeing how any kind of.

data in like, let's say a 30 minute span, right?

Half's 45 minutes, something happens over 30 minutes.

I have a really hard time envisioning how AI can, what is it going to tell a coach that would allow the coach to essentially change his team's formation?

I guess that would be the main way that you could change up, that a coach wouldn't already see.

Or how would we know that that information is not just random chance by like the bounce of the ball,

versus like a structural issue with the team.