00:28:15 · Monica Ellingson
[00:28:15] S1: It really varies year to year. We usually bring around, you know, 15 to 20 people. We brought a pretty big team this year because we had a a large scope. And, you know, it's extremely important that we're there on-site, you know, with... Well, alongside with our clients, with our partners, with USTA. You never know. There are things that happen at a live event that, it's extremely important that you're there in person to triage. I know that we have so many so many ways right now where we can collaborate virtually, but it's, extremely important that we're that we're there alongside them. I mean, this is... They have three weeks of the year to nail these events, and they work all year round to make sure that it's success... It's a it's a success, so we need to be there with them. But, you know, although on-site, it's only about 15 to 20 people, I have a very large team working remotely who are, you know, monitoring the apps in terms of performance. They are, you know, certainly addressing, any issues that come up. And more importantly, just looking at the scale, we go from a very low volume of users up to where we have over 14,000,000 users. And this is a huge spike that we see as soon as things start going live during fan week on day one and ensuring that the infrastructure that we have in place can handle that volume of traffic and that the digital platforms remain secure. So looking at the overall cybersecurity behind that and, you know, ensuring that, you know, the fan experience always stays stable and the data... The USTA's data stays secure.
00:29:58 · Ian Dallimore
[00:29:58] S0: Yep. And again, I'm just a bit of a... An advertising data junkie, but, like, that has to be the coolest thing ever, especially your entire team and the hard work you guys put in to watch it just, like, trickle along. Then the day... The weeks leading up and then the week of, it just probably spikes and it just stays up there.
00:30:15 · Monica Ellingson
[00:30:15] S1: Yeah. It's it's a little bit of an adrenaline thing. I mean, you you can't work in live events if you, you know, if you're not a little bit of an adrenaline junkie. For sure. You know, because, you know, we work with USTA year round, all of our partners year round. So, I mean, the event ends and people say, oh, you must be going to take some vacation. I'm like, no. I... Like, it just... It keeps going. It's impossible to, you know, stay on top of the year round delivery schedule that we have, you know, if we just let our guard down. You know, we have to continue to be innovative. We have to, you know, continue the evolution of, alright. So we just finished, you know, this one event. What went well? What could have gone better? What what were the epiphanies that we had during the event for, you know, interesting experiences that we wanna roll out next year? What are what are what things do we want to enhance? And then ultimately, you know, what are the new really big, shiny, innovative objects and features that we want to roll out for next year? So this is something that, you know, we are already, you know, in this process of post mortem and scoping out what, you know, the US Open twenty twenty seven looks like. And, you know, meanwhile, we've already kicked off development for Wimbledon, kicked off development for The Masters, and it just goes on and on. So, you know, it's it's... There's never a downtime.
00:31:37 · Ian Dallimore
[00:31:37] S0: I'd love to be inside of your brain. It's probably just like, let's go. Just constantly. It... But but, I mean, again, going back to it and and asking, like, a more detailed question. You know, we as we as fans now, we expect data. But what is it against staying with with tennis? You know, fans are so interested in things like ball speed, serve quality you had mentioned. So I'd love you to kind of elaborate that. And then even match momentum. Like, I think about the sports that I don't understand, and then you watch the momentum change. I think about watching World Cup and watching FIFA, like watching the changing of tides and watching what happens. Like, helps you... Your mind to understand a sport that maybe some people aren't familiar with. So then you become a passive fan. And then because of the data that you guys are providing, like at the US Open, you then start to understand it and then you embrace it and then you become a fan, which is why probably you guys have that partnership or they have that partnership with you guys. But what is it like serve quality as data point?
00:32:36 · Monica Ellingson
[00:32:36] S1: Well, serve quality is a brand new stat that we created this year. And, you know, the serve is definitely the most important stroke in tennis and there are so many different physical components that go into it. So, you know, it's the positioning of your feet, the loading as you... It's almost like a spring that, you know, loads and then springs forward, you know, trying to get that momentum, the energy from your lower body moved up all the way through the wrist snap. And so it's a difficult stroke to understand because of all these physical components. You know, I've... I have a a coach that I've worked with for a really long time for my tennis game, and I'm not a very good server. I don't have the patience to get out there and practice and what have you, but it's like, okay. You know, move your feet this way. Okay. Now now spring into the into the court. Now snap your wrist this way. And it... Just all these different pieces. It's a it's a difficult stroke to, you know, to be able to master. So to better understand it, we... For the first time, we gathered biometric data. And so if you look around the stadium, there are cameras that are typically, these are used for serve speed as well as the automated line calling, which they've had at the US Open since the pandemic times. And we're using those same same cameras from Hawkeye to gather biometric data. And so we gathered that biometric data, and then we used IBM Bob, which is one of our AI development tools and created a model for the different serve... The criteria that go into a serve. So created the criteria for the serve and then, you know, married that criteria for the actual effectiveness of a serve with the accuracy of the serve. And that came up into a serve quality score. But still as a fan, you're looking at that and you say, oh, serve quality 73%. What does that even mean? So we then use GenAI to create our natural language processing to be able to create a summary of the different criteria that went into that serve score. So what are the what are the physical components about that player serve that contributed to their serve quality? And that was what we bubbled up into the app. So it was a simple score with a couple of sentences describing why.
00:35:03 · Monica Ellingson, Ian Dallimore
And, you know, it was key that we kept it simple that way, you know, because it's, you know, not every fan is gonna gonna wanna dig deeper into that. But, you know, we just started this. I mean, literally in June, I saw a proof of concept for serve quality. We created a three d model of the court, the player, and the ball motion as well as part of this. And I said, hey. Well, you know, people have been doing this for kind of a while now in terms of, you know, visualizing the court, the movement, the motion on the court. But what can we actually... What insights can we pull from that? And within a matter of weeks, we had the serve quality score. We had the overall fan experience. We were able to test that and get... Enroll that into the digital platforms, which we released in August. So that's an extremely fast timeline timeline that we were able to go from proof of concept or idea all the way to launching the product. [00:36:04] S0: Yeah. Definitely shout out to your team on that because that is a... That could have been an easy like, okay, let's let's continue to test this beta internally and then let's launch it. But, yeah, that's that's fascinating. Do you ever do you ever try to use the same mechanics? You probably don't have the cameras and whatnot, but, like, on your own serve to be like, hey, coach. I got this.