 From around the globe, it's theCUBE with digital coverage of AWS re-invent 2020. Sponsored by Intel and AWS. Welcome back to theCUBE as we continue our coverage of AWS re-invent 2020. You know, I know you're familiar with Moneyball, the movie Brad Pitt starring as Billy Bean, the open age general manager where the A's were all over data, right? With the Billy Bean approach. It was a very data-driven approach to building his team at a very successful team. Why AWS is taking that to an extraordinary level. And with us to talk about that is Matt Hearst, who's the head of global sports marketing and communications at AWS. And Matt, thanks for joining us here on theCUBE. John, it's my pleasure. Thanks so much for having me. You bet. Now we've already heard from a couple of folks, NFL folks at re-invent about the virtual draft. But for those of our viewers who maybe aren't up to speed on that or haven't had a chance to see what those folks had to say. Let's just talk about that as an opener about your involvement with the NFL and particularly with the draft and what that announcement was all about. Sure. We've seen a great evolution with our work with the NFL over the past few years. And you mentioned during the infrastructure keynote where Michelle McKenna, who's the CIO for the NFL talked about how they were able to stage the 2020 virtual draft, which was the NFL's most watch ever, over 55 million viewers over three days and how they were unable to do it without the help and the power of AWS, utilizing AWS's reliability, scalability, security and network connectivity where they were able to manage thousands of live feeds to flow over the internet and go to ESPN to air live. But additionally, Jennifer Langton, who's the SVP of player health and innovation at the NFL spoke during the machine learning keynote during re-invent. And she talked about how we're working with the NFL to co-develop the digital athlete, which is a computer simulation model of football player that can replicate infinite scenarios in a game environment to help better foster an understanding of how to treat and rehabilitate injuries in the short-term. And in the long-term in the future, ultimately prevent and predict injuries and they're using machine learning to be able to do that. So those are just a couple of examples of what the NFL talked about during re-invent at a couple of keynotes, but we've seen this work with the NFL really evolve over the past few years, starting with next-gen stats. Those are the advanced statistics that brings a new level of entertainment to football fans and what we really like to do with the NFL is to excite, educate and innovate. And those stats really bring fans closer to the game to allow the broadcasters to go a little bit deeper to educate the fans better. And we've seen some of those come to life through some of our ads featuring to Sean Watson, Christian McCaffrey, these visually compelling statistics that come to life on screen. And it's not just the NFL. AWS is doing this with some of the top sports leagues around the world, powering F1 Insights, Bundesliga Match Facts, Six Nations Rugby Match Stats, all of which utilize AWS technology to uncover advanced stats and really help educate and engage fans around the world in the sports that they love. Yeah, let's talk about that engagement with your different partners then because you just touched on it. This is a wide array of avenues that you're exploring. You're in football, you're in soccer, you're in sailing, you're in racing, Formula One and NASCAR, for example, all very different animals, right? In terms of their statistics and their data and of their fan interest, what fans ultimately want. So maybe on a holistic basis first, how are you kind of filtering through your partner's needs and their fans' needs and your capabilities and providing that kind of merger of capabilities with desires? You know, sports for AWS and for Amazon are no different than any other industry. And we work backwards from the customer and what their needs are. You know, when we look at the sports partners and customers that we work with and why they're looking to AWS to help innovate and transform their sports, it's really the innovative technologies like machine learning, artificial intelligence, high performance computing, internet of things, for example, so that are really transforming the sports world. And some of the best teams and leagues that we've talked about that you touched on, you know, Formula One, NASCAR, NFL, Bundesliga, Six Nations Rugby and so on and so forth are using AWS to really improve the athlete and the team performance, transform how fans view and engage with sports and deliver these real-time advanced statistics to give fans more of that excitement that we're talking about. Well, let me give you a couple of examples on some of these innovative technologies that our customers are using. So the Seattle Seahawks have built a data lake on AWS to use it for talent evaluation and acquisition to improve player health and recovery times and also for their game planning. And another example is, you know, Formula One, we talk about the F1 Insights, those advanced statistics, but they're also using AWS high performance computing that helped develop the next generation race car, which will be introduced in the 2022 season. And by using AWS, F1 was able to reduce the average time to run simulations by 70% to improve the car's aerodynamics, reducing the downforce loss and create more wheel-to-wheel racing to bring about more excitement on the track. And a third example similar to F1 using HPC is Ineos Team UK. So they compete in the America's Cup, which is the oldest trophy in international sports. And Ineos Team UK is using an HPC environment running on Amazon EC2 spot instances to design its boat for the upcoming competition. And they're depending on this computational power on AWS, needing 2,000 to 3,000 simulations to design the dimensions of just a single boat. And so the power of the cloud and the power of the AWS innovative technologies are really helping these teams and leagues and sports organizations around the world transform their sport. Well, let's go back, you mentioned the Seahawks, just as an example of maybe the kind of insights that you're providing. Let's pretend there's an outstanding running back and his name is Matt Hearst. And he's at a college, this is pretending California someplace. What kind of inputs are you now helping them? And what kind of insights are you trying to, are you helping them glean from those inputs that maybe they didn't have before and how are they actually applying that then in terms of their player acquisition and thinking about draft player development, deciding whether Matt Hearst is a good fit for them, maybe John Walls is a good fit for them. But what's that process look like? So the way that the Seahawks have built the data lake, they built it on AWS to really, as you talk about this talent evaluation and acquisition, to understand how a player, for example, at John Walls could fit into their scheme, that taking this data and putting it in the data lake and figuring out how it fits into their schemes is really important because you could find out that maybe you played two different positions in high school or college and then that could transfer into the schematics that they're running. And try to find, I don't wanna say a diamond in a rough, but maybe somebody that could fit better into their scheme than maybe the analysts or others could figure out. And that's all based on the power of data that they're using, not only for the talent out evaluation and acquisition, but for game planning as well. And so the Seahawks building that data lake is just one of those examples. When you talk about player health and safety as well, just using the NFL as the example too, with that digital athlete, working with them to co-develop that for that composite NFL player, where they're able to run those infinite scenarios to ultimately predict and prevent injury and using Amazon SageMaker and AWS machine learning to do so is super important. Obviously with the Seahawks for the future of that organization and the success that they see and continue to see and also for the future of football with the NFL. Roger Goodell talks about innovation in the National Football League. We hear other commissioners talking about the same thing. It's kind of a very popular buzzword right now as leagues look to ways to broaden their technological footprint in innovative ways. Again, popular to say. How exactly though, do you see AWS's role in that with the National Football League for example again or maybe any other league in terms of inspiring innovation and getting them to perhaps look at things differently through different prisms than they might have before? I think again, it's working backwards from the customer and understanding their needs, right? We couldn't have predicted at the beginning of 2020 that the NFL draft will be virtual. And so working closely with the NFL, how do we bring that to life? How do we make that successful? Working backwards from the NFL saying, hey, we'd love to utilize your technology to improve player health and safety. How are we able to do that, right? And using machine learning to do so. So the pace of innovation, these innovative technologies are very important not only for us, but also for these leagues and teams that we work with. Using F1 as another example, we talked about HPC and how they were able to run these simulations in the cloud to improve the race car and redesign the race car for the upcoming seasons. But F1 is also using Amazon SageMaker to develop new F1 insights to bring fans closer to the action on the track and really understand through technology the split second decisions that these drivers are taking in every lap, every turn, when to pit, when not to pit, things of that nature. And using the power of the cloud and machine learning to really bring that to life. And one example of that that we introduced this year with F1 was the fastest driver insight. And F1 worked with the Amazon Machine Learning Solutions Lab to bring that to life and use a data-driven approach to determine the fastest driver over the last 40 years relying on the years of historical data that they store in S3 and the ML algorithms that built between AWS and F1 data scientists to produce this result. So John, you and I could sit here and argue, two guys that really love F1 and say, I think Michael Schumacher is the fastest driver of all time. It was Nicky Loud and it was Schumacher, right. Right, it's Lewis Hamilton, who's great. Well, it turned out it was Arten Senna and Schumacher was second and Hamilton's third. And it's the power of this data and the technology that brings this to life. So we could still have a fun argument as fans around this, but we actually have a data-driven result through that to say, hey, this is actually how it ranked based on how everything worked. You know, this being such a strange year, right? With COVID being rampant and the major influence that it has been in every walk of global life, but certainly in the American sports. How is that factored into in terms of the kinds of services that you're looking to provide or to help your partners provide in order to increase that fan engagement? Because as you've pointed out, ultimately at the end of the day, it's about the consumer, right? The fan and giving them info they need at the time they want it that they find useful. But has this year been put a different point on that for you just because so many eyeballs have been on the screen and not necessarily in person? Yeah, 2020, as you know, a year unlike any other, you know, in our lifetimes and hopefully going forward. You know, it's not like that. But we are able to understand that we can still bring fans closer to the sports that they love. And working with these leagues, you know, we talked about NFL Draft, but with Formula One, we in the month of May developed the F1 Pro Am Deep Racer event that featured F1 driver, Daniel Ricardo and test driver, Tatiana Calderon in this Deep Racer League. And Deep Racer is a one 18th scale, fully autonomous car that uses reinforcement learning, a type of machine learning. And so we had actual F1 driver and test driver racing against developers from all over the world. And technology is really playing a role in that evolution of F1, but also giving fans a chance to go head to head against the Daniel Ricardo, which I don't know that anyone else could ever say that, yeah, I raced against an F1 driver head to head, you know, and doing that in the month of May really brought forth not only an appreciation, I think for the drivers that were involved on the machine learning and the technology involved, but also for the developers on these split second decisions these drivers have to make through an event like that. That's really cool. Yeah, it was great and well-received and the drivers had a lot of fun there. You know, and the National Basketball Association, the NBA played in the bubble down in Orlando, Florida. And we work with Second Spectrum, they run on AWS. And Second Spectrum is the official optical provider of the NBA. And they provide Clippers Court Vision. So it's a mobile live streaming experience for LA Clippers fans that uses artificial intelligence and machine learning to visualize data through on-screen graphic overlays. And Second Spectrum was able to rely on AWS's reliability, connectivity, scalability, and move all of their equipment to the bubble in Orlando and still produce a great experience for the fans by reducing any latency type of video and data processing. They needed that low latency to encode and compress the media to transfer and edit with the overlays in seconds without losing quality. And they were able to rely on AWS to do that. So a couple of examples that even though 2020 was a little different than we all expected it to be of how we worked closely with our sports partners to still deliver an exceptional fan experience. So, I mean, first off, you have probably the coolest job at AWS, I think. I mean, so congratulations. I mean, it's just, it's fascinating. What's on your want to do list then in terms of 2021 and beyond then about what you don't do now or what you would like to do better down the road? Any one area in particular that you're looking at? You know, our strategy in sports is no different than any other industry. We want to work backwards from our customers to help solve business problems through innovation. And I know we've talked about the NFL a few times, but taking them for another example, with the NFL draft, improving player health and safety, working closely with them, we're able to help the NFL advance the game both on and off the field. And that's how we look at doing that with all of our sports partners and really helping them transform their sport through our innovative technologies. And we're doing this in a variety of ways with a bunch of engaging content that people can really enjoy with the sports that they love, whether it's, you know, quick explainer videos that are short two minute or less videos explaining what these insights are, these advanced stats. So when you see them on the screen, you can say, oh yeah, I understand what that is at a conceptual level or having blog posts from a Will Carlin who has a long story to history in Six Nations and in Rugby or Rob Smedley, a long story to history in F1, writing blog posts to give fans deeper perspective as subject matter experts. Or even for those that want to go deeper under the hood, we've worked with our teams to take a deeper look at how some of these come to life, detailing the technology journey of these advanced stats through some deep dive blogs. And all of this can be found at aws.com slash sports. So a lot of great, rich content for people to dig into. Oh, it's great stuff indeed. Congratulations to you and your team because you really are enriching the fan experience of which I'm one of, you know, hundreds of millions are enjoying that. So thanks for that great work. And we wish you all the continued success down the road here in 2021 and beyond. Thanks, Matt. Thanks so much, Sean.