2788: How Sportradar Are Revolutionizing Sports with AI

[00:00:00] [SPEAKER_00]: Are you ready to dive into the world of sports technology like never before?

[00:00:06] [SPEAKER_00]: Well, welcome back to The Tech Talks Daily Podcast.

[00:00:09] [SPEAKER_00]: I'm your host Neil and today I'm going to attempt to peel back the layers of the sports

[00:00:14] [SPEAKER_00]: tech union.

[00:00:16] [SPEAKER_00]: And my guest today is the senior vice president of automated content at a company called Sportradar.

[00:00:22] [SPEAKER_00]: His name is Luca and he's been a part of Sportsradar's journey for over nine years

[00:00:27] [SPEAKER_00]: now and is at the forefront of integrating artificial intelligence, computer vision and

[00:00:33] [SPEAKER_00]: machine learning in the world of sports.

[00:00:36] [SPEAKER_00]: But what does this mean for fans?

[00:00:38] [SPEAKER_00]: What does it mean for broadcasters and even the fast evolving world of sports betting

[00:00:42] [SPEAKER_00]: and micro betting?

[00:00:45] [SPEAKER_00]: And also how is AI not just changing but revolutionizing the way we experience and engage with our

[00:00:51] [SPEAKER_00]: favourite sports?

[00:00:53] [SPEAKER_00]: Well, my guest today Luca is here to shed light on all of these questions and dig a little

[00:01:00] [SPEAKER_00]: bit deeper on some of the groundbreaking advancements.

[00:01:02] [SPEAKER_00]: So if you're interested in how computer vision is transforming the sports industry,

[00:01:08] [SPEAKER_00]: well let's kick things off today, buckle up and hold on tight as I beam your ears

[00:01:13] [SPEAKER_00]: all the way to Vienna in Austria.

[00:01:15] [SPEAKER_00]: Where Luca is waiting to talk about all this?

[00:01:18] [SPEAKER_00]: And much more.

[00:01:20] [SPEAKER_00]: So a massive warm welcome to the show.

[00:01:23] [SPEAKER_00]: Can you tell everyone listening a little about who you are and what you do?

[00:01:27] [SPEAKER_01]: Hey Daniel, thanks for having me first of all.

[00:01:30] [SPEAKER_01]: So my name is Luca, Luca Pataki.

[00:01:34] [SPEAKER_01]: I am senior vice president for automated content in Sportradar.

[00:01:39] [SPEAKER_01]: So very exciting stuff that we do.

[00:01:41] [SPEAKER_01]: Actually quite a big AI focus team that focuses on collection of data using AI from sports

[00:01:50] [SPEAKER_01]: videos.

[00:01:51] [SPEAKER_01]: So super exciting topic, super exciting area, lots of growth in general in this space

[00:01:56] [SPEAKER_01]: in the last years and yeah we'll talk a bit more about it as we go through this podcast.

[00:02:04] [SPEAKER_00]: And something I try and do every single day on this podcast is getting people thinking

[00:02:08] [SPEAKER_00]: differently about technology and also thinking about how technology is impacting a world that

[00:02:13] [SPEAKER_00]: they probably don't automatically associate with technology and sports broadcasting.

[00:02:17] [SPEAKER_00]: I would imagine is one of those that you don't automatically associate with AI.

[00:02:21] [SPEAKER_00]: So can you describe the journey of sports broadcasting's evolution with the advent of

[00:02:26] [SPEAKER_00]: computer vision and AI and how technology is changing the narrative and ultimately

[00:02:31] [SPEAKER_00]: the storytelling of sport too?

[00:02:33] [SPEAKER_01]: Yeah, so the interesting thing about computer vision is that actually the way it works

[00:02:40] [SPEAKER_01]: it mimics a bit the human vision system right in ASA.

[00:02:44] [SPEAKER_01]: So it means everything it sees in a video frame it can understand, interpret and create something out of it right?

[00:02:51] [SPEAKER_01]: And why it's so interesting for broadcasting in general for viewing experiences because

[00:02:55] [SPEAKER_01]: basically it analyzes everything you see on the screen and it understands where things are.

[00:03:00] [SPEAKER_01]: And so it means that it can overlay data insight on top like a lot more contextually.

[00:03:07] [SPEAKER_01]: So it sees the players that are on the screen and so it can present something related to that.

[00:03:12] [SPEAKER_01]: It means you don't need to necessarily be fast to do it manually.

[00:03:17] [SPEAKER_01]: You'll have a system detect automatically which player is on the screen or what's currently happening.

[00:03:23] [SPEAKER_01]: And so you'll get insights and overlays that are a lot more relevant right?

[00:03:28] [SPEAKER_01]: So that's one aspect.

[00:03:30] [SPEAKER_01]: The other big aspect is that it allows also for advertising opportunities to become a lot more dynamic and contextual.

[00:03:38] [SPEAKER_01]: So you can use again computer vision to overlay ads in specific areas that are relevant for some territory

[00:03:46] [SPEAKER_01]: or just use spaces on the floor of the arena or of the soccer pitch

[00:03:53] [SPEAKER_01]: and you can kind of overlay it with some again graphic statistics.

[00:03:57] [SPEAKER_01]: So it does give I would say a new life to the whole viewing experience from many stakeholders involved right?

[00:04:04] [SPEAKER_01]: From advertisers to fans and all parties involved.

[00:04:08] [SPEAKER_01]: So it really kind of gives a new life to the broadcast and some sports have been a lot more advanced here.

[00:04:16] [SPEAKER_01]: You know something like American football you'd see like for a long time this overlays on the pitch

[00:04:21] [SPEAKER_01]: that show like you know which like how the game is progressing.

[00:04:27] [SPEAKER_01]: You know some sports are a lot more advanced than some not so much but actually everything is moving in that direction.

[00:04:33] [SPEAKER_00]: Just to bring to life some of what we're talking about here for sports fans listening all over the world

[00:04:38] [SPEAKER_00]: whether it be soccer here in the UK or NFL and the Super Bowl coming up over in the US.

[00:04:44] [SPEAKER_00]: In what ways is sport radars computer vision and AI technology enhanced real time data collection

[00:04:50] [SPEAKER_00]: and ultimately what impact does that have on a fan engagement and the viewing experience?

[00:04:56] [SPEAKER_01]: It's interesting right because at the end of the day it's just technology and data is just data.

[00:05:01] [SPEAKER_01]: If you can't make sense out of it at the end then it's not really worth a lot right?

[00:05:05] [SPEAKER_01]: But actually AI and computer vision allow to generate a lot more data which generates a lot deeper insight understanding of the game.

[00:05:14] [SPEAKER_01]: I often like to say that you know what was once enough from viewing experience and fan engagement is not enough anymore

[00:05:20] [SPEAKER_01]: like fans are not satisfied with simple stats and simple explanations.

[00:05:25] [SPEAKER_01]: You need to know more and also if you want to differentiate as a broadcaster you need to kind of have that edge

[00:05:31] [SPEAKER_01]: and what AI and computer vision so particularly obviously I'm focused more computer vision allows is that we can generate a lot more data.

[00:05:39] [SPEAKER_01]: We are talking about anything like 100 times more data that can be collected that actually you can't collect any other way

[00:05:46] [SPEAKER_01]: like you can't collect tracking data you can't collect certain information in any other way than using this tech

[00:05:51] [SPEAKER_01]: and that allows to build a lot deeper insight to understand why the game is going on like this

[00:05:57] [SPEAKER_01]: or even you know explain some things whether it's in between like pauses or just in real time

[00:06:05] [SPEAKER_01]: you immediately have access to I don't know how long someone has ran or how fast they how fast the sprint was

[00:06:13] [SPEAKER_01]: compared to maybe their season average or whatever so it gives a lot more things to talk about

[00:06:18] [SPEAKER_01]: and that kind of enhances this it means for again all the fans that watch it there's a lot more information

[00:06:25] [SPEAKER_01]: and there's a lot more stickiness you need to you know attention spans are also shrinking right

[00:06:30] [SPEAKER_01]: so you need to have these stories that are interesting that kind of grab the attention and keep the fan engaged

[00:06:37] [SPEAKER_01]: and that whether it's you know just the fan watching the game or where is a punter that wants to you know

[00:06:44] [SPEAKER_01]: understand what's happening next so that they can they can you know bet to need so everyone is

[00:06:49] [SPEAKER_01]: interesting in this and definitely want wants more and more information that's how we use it

[00:06:54] [SPEAKER_01]: so we use it generally to enhance the insight that we are delivering to fans at the end

[00:07:00] [SPEAKER_01]: and to improve overall that experience

[00:07:04] [SPEAKER_00]: another huge topic right now is the personalization of just about everything whether it be music film shopping

[00:07:10] [SPEAKER_00]: and yeah I'm curious how is AI enabling personalized experiences for sports fans

[00:07:16] [SPEAKER_00]: what does that mean for the future of sports consumption do you think

[00:07:19] [SPEAKER_01]: yeah so I think there's like AI in general has a massive impact on personalization right because it allows to basically

[00:07:27] [SPEAKER_01]: treat that every consumer individually understand what they are doing and how they're engaging with sports

[00:07:33] [SPEAKER_01]: like even just how they consume sports like what sports they watch what sports they you know what sort of

[00:07:40] [SPEAKER_01]: especially they like to share on social media and so on so you can build a better understanding and then

[00:07:45] [SPEAKER_01]: offer more personalized experience even if it's as simple as we offer you these sports to bet on because we know that you like those sports right

[00:07:53] [SPEAKER_01]: but so in AI there is personalization is absolutely massive but even computer vision offers a lot of interesting things

[00:08:00] [SPEAKER_01]: computer vision is very big in terms of generating like highlights so short form video content and again here it can help like identify what is actually relevant to you as a consumer and then you know offered a person

[00:08:15] [SPEAKER_01]: personalized clipping for you or personalized highlight for you at the same time I mentioned earlier personalization in terms of advertising a bit so that's extremely interesting for advertisers because you know who wants this mass advertising that just goes the same to everyone right if I can have something more personalized

[00:08:33] [SPEAKER_01]: whether that's to the territory or age group or something I mean in theory computer vision can help you basically produce like I don't know 50 different streams and almost every consumer could get could get a different one and that doesn't just mean from the perspective for ads it could also be like what stats appear like who are we following as a player and you can be even more futuristic and you can think like these 3d data can help rebuild things in virtual space so as a

[00:09:03] [SPEAKER_01]: fan maybe I'm just interested to look at something from my perspective and not from someone else's perspective right so I get a call complete personalized experience so there is like AI is massive in terms of personalization and generally AI but also computer vision from this visual perspective like anything that is visual can be personalized because that technology helps us to do that but just in general

[00:09:25] [SPEAKER_01]: AI it's it's the power of being able to process a lot of data very fast and so you can then return back to the consumer something that's very very made for them right.

[00:09:38] [SPEAKER_00]: It's incredibly cool what you're doing here and this is just scratching the surface can also elaborate on the capabilities of computer vision in mimicking human vision particularly in terms of accuracy and speed when analyzing sports events.

[00:09:52] [SPEAKER_01]: Yes so I mean for us at sport there obviously the speed and accuracy are the two key things.

[00:09:59] [SPEAKER_01]: In in betting space it has to be real time it has to be super accurate those are two important things and we also understand that patterns the trends are moving in direction of even more life you know almost like micro life experiences right.

[00:10:12] [SPEAKER_01]: And if you want to then have that competitive edge where you know you are building more inside you are building experience which are faster so like micro events then you need to use these technologies and actually computer vision works similarly to like human vision system and brain system.

[00:10:31] [SPEAKER_01]: The thing is that you know we still need to focus on certain areas and our brain is extremely powerful of course and here we are still often more advanced than machines because sometimes that cognitive aspect of understanding what will happen and logically putting things together is still like very much exclusive to human mind

[00:10:50] [SPEAKER_01]: but computer vision can process a lot of things at the same time and actually if you look at the image that there's a lot of pixels in that image you can process every pixel at the same time and so you're able to in that same or faster speed generated a lot more inside

[00:11:05] [SPEAKER_01]: and you never get tired right so you potentially don't make a mistake sometimes or is something because you can look at everything at the same time.

[00:11:15] [SPEAKER_01]: So it allows us to be really fast we have a couple of systems in production where we do you know data collection based on computer vision those systems run those systems run at 20 to 40 milliseconds and that's how fast they deliver data and actually even the streaming so the whole new viewing experience streaming that includes this

[00:11:35] [SPEAKER_01]: real time overlays based on computer vision comes out at 200 milliseconds so it allows to create a lot more data a lot faster so that within one second we can have like different sort of opportunities for bet thing on smaller micro markets and actually it allows us to kind of go from the point where

[00:11:56] [SPEAKER_01]: we offer something to the customer say like you can now I don't know how many bounces off the table will there be to the point where we can conclude this and say there was like 10 bounces off the table everything like within 20 seconds and means the system needs to process the play has finished and you know you have your resolution

[00:12:16] [SPEAKER_01]: so absolutely speed accuracy and and it's very consistent right so you know these systems are trained on a lot of data and they make decisions very consistently right so of course they sometimes make a mistake but I like to say they make kind of objective mistakes right you can't they are not really predictable

[00:12:35] [SPEAKER_01]: and they are normally very rare and that's where you train on more data and so it's very consistent output and you know very fast always at the same time.

[00:12:47] [SPEAKER_00]: And you mentioned betting there and I must admit on a Saturday afternoon I am guilty of having a traditional accumulate a bet and I know outside of that the micro betting markets are just huge now and the things that put in people's bets on it.

[00:13:00] [SPEAKER_00]: I often think about the technology that makes all that possible because it needs to be so quick and also have such low latency so how is technology transforming that sports betting landscape especially with regards to those micro betting markets and of course that demand for ultra low latency data because it's one of those things that maybe a lot of people take for granted but there's a lot going on under the hood right.

[00:13:24] [SPEAKER_01]: Yeah absolutely so it's the trend that goes towards that like shorter attention span and everything needs to be faster and maybe a you know a punter doesn't want to sit down for the whole game and wait until the end to get the result you want to kind of get engaged for a few minutes and step out and then get in again and you don't you don't need the whole game experience there's different fans right.

[00:13:46] [SPEAKER_01]: And so this definitely allows that those markets you can't do them any other way than using a I across the whole sort of life cycle of such bad from the data collection that has to be extremely fast to the you know calculating the probabilities and odds offering that and then resolving or resulting the bet at the end.

[00:14:09] [SPEAKER_01]: You know we've recently did this for table tennis and they're like believe it or not you know you have a better number of bounces in every rally like is it going to be over under a certain number.

[00:14:21] [SPEAKER_01]: And table tennis is already extremely fast sport and then every rally last anything between 10 to 30 seconds so everything from data collection to probabilities to resolving this bet and then to the to giving it to the customer that has to happen within then that's 20 to 30 seconds.

[00:14:38] [SPEAKER_01]: Time frame so it has to be really fast and that's only really possible with this with these kind of technologies.

[00:14:47] [SPEAKER_01]: And because it's also the end not just about kind of the microbed but it has to have the whole experience has to be kind of connected we the way how we look at it is that the whole micro betting experience is probably a bit different to classic live betting experience because streaming also becomes really important like you know it's it's very important.

[00:15:08] [SPEAKER_01]: For the punter for example to kind of OK you can bet on number of bounces off the table but it's also nice to see those bounces actually you know to have this immediate validation.

[00:15:18] [SPEAKER_01]: So that's why again streaming here with overlays of those bounces is really important but you need to do everything really fast right to give that experience back.

[00:15:27] [SPEAKER_00]: You've blown my mind I had no idea table tennis batting was such a huge industry and obviously we make it sound so easy in a podcast conversation today but what are the biggest challenges that you faced at sports radar when deploying things like AI and computer vision across a variety of sports.

[00:15:47] [SPEAKER_00]: Any challenges you can share and how you're able to overcome them.

[00:15:50] [SPEAKER_01]: Yeah I mean the biggest challenge challenge generally in computer vision is the data to train the models on right and actually this space has advanced a lot.

[00:16:00] [SPEAKER_01]: So five six years ago it would be very difficult to generate big enough data set to then train your model son.

[00:16:06] [SPEAKER_01]: Now you have a lot of sort of transfer learning and pre trained models basically like a lot of models available that are already kind of pre trained on big data sets or not every company needs to build those data sets.

[00:16:19] [SPEAKER_01]: So the secret source at the end is in the data set right and that's what you trained your model on and that's usually that takes iterations and that takes improvements and the challenges usually come from not having enough data or you know like what in this sense you'd say like either

[00:16:37] [SPEAKER_01]: you have too much representative data or two liter representative data and that's for space like sports batting where accuracy is really important.

[00:16:47] [SPEAKER_01]: Every sort of outlier the end can matter and it means like you know money for someone right so yes it has the data is one of the biggest challenges in the past also processing was because there was just maybe not enough processing power but this is not really anymore an issue

[00:17:06] [SPEAKER_01]: and it's getting better and better or more processing power is available.

[00:17:11] [SPEAKER_01]: So yes still I would say the biggest data the biggest challenge is the data and sometimes the time like we cover so many sports is difficult to do them all at the same time and every sport is a bit challenging like people would say table tennis for example it is more contained sport

[00:17:26] [SPEAKER_01]: like you know two players on each side of the table so you can imagine it's a little bit easier from that perspective but it's super fast the ball is probably the smallest and the fastest of all of the sports.

[00:17:36] [SPEAKER_01]: So you need to have pretty powerful camera there and in soccer you don't have this issue but you have a lot of players that cover each other and so how do you make sure that you detect them all and you know when they include each other and so on so every sport has its own challenges

[00:17:53] [SPEAKER_01]: and then you know data is an overarching challenge for all of them I would say.

[00:17:58] [SPEAKER_00]: Wow if I ask you to look ahead into the future I'm curious how do you see AI and computer vision further revolutionizing the sports industry and already new possibilities that you could see emerging in the months and years ahead.

[00:18:10] [SPEAKER_01]: I mean I think definitely AI will stay and grow to be really important piece like across all areas of sports I think where you know that means like sports performance so for athletes and coaches and you know everything from grassroots up there is more availability of this and data

[00:18:31] [SPEAKER_01]: is becoming really important for all the players and they are seeing how they can also you know build something some edge for themselves like be better athletes improve performance.

[00:18:41] [SPEAKER_01]: So definitely there in officiating like there's a lot of computer vision ready like video assistant referees there's a lot of computer vision in that like pretty powerful system has changed the sport already and I think it's going to continue to change the sport.

[00:18:57] [SPEAKER_01]: In data collection for sure because I don't see the world where there is less data needed I think there's everyone is hungry for more.

[00:19:07] [SPEAKER_01]: So there will be AI everywhere I do agree with many that say that AI is almost as big of an invention as electricity maybe we don't yet know but I think it will impact our lives a lot and in a lot of positive ways and yeah I think it's going to definitely is definitely here to stay and to grow.

[00:19:27] [SPEAKER_01]: One area that I see still growing more is the same immersive experience like virtual spaces.

[00:19:34] [SPEAKER_01]: I think we are still relatively at the beginning we had spotted already do quite a bit in that area so using them really 3D data to recreate you know sport sport event and again in real real real time life this was still grow like immersive experiences made the verse.

[00:19:52] [SPEAKER_01]: And so on so there is no I don't that's super exciting for me I like this a lot I like the technology space of sport and how it can actually help the sport on all sides.

[00:20:06] [SPEAKER_00]: And I question I've got to ask of course as we continue to see AI everywhere increasing use of AI in sports in particular are there any ethical considerations that you take into account particularly concerning data privacy and the integrity of sports.

[00:20:22] [SPEAKER_01]: Yeah so I mean like with any technology rice you have to it's important you use it for good and you use it in the right way.

[00:20:30] [SPEAKER_01]: And especially when it's this sort of emerging technologies that become very accessible is very easy to jump on something without really understanding it well and then you know things maybe go a bit south right.

[00:20:41] [SPEAKER_01]: So for us I think these are really important aspects I would say on the integrity piece first when you look at tracking data and computer vision and what it can help it actually can also even further improve the whole integrity aspect because it gives you that understanding of the game.

[00:20:58] [SPEAKER_01]: So you can see like the patterns of play and you can that helps you understand if there's something that's going out of the usual pattern.

[00:21:05] [SPEAKER_01]: So we definitely see this can actually further help our integrity efforts which is already really important piece when it comes to data itself.

[00:21:14] [SPEAKER_01]: I would say there is of course certain lines that you shouldn't cross and you know that's when it comes to kind of data privacy aspects.

[00:21:25] [SPEAKER_01]: Such data types probably include like biometric data right like I think you know that's where I believe you know you need to be very considered we focus just on sport event data right so we are thinking about what are the.

[00:21:40] [SPEAKER_01]: What's the data about the sport event itself that can help improve the experience whether that's like sports performance for players where we do a lot in basketball whether it's fan engagement and we do work very closely with federations to make sure that all the data privacy aspects are considered

[00:21:56] [SPEAKER_01]: and that we are you know doing what actually ultimately helps everyone like whether that's athletes or or you know fans or coaches or whoever.

[00:22:07] [SPEAKER_01]: Yeah but as I said like you need to every technology you need to think about it and do it smartly and not jump on it just because it's sexy and interesting but actually because you are doing something with it that actually at the end makes an experience better for everyone involved.

[00:22:24] [SPEAKER_00]: Well absolutely love chatting with you today you blow my mind in so many different areas and I've learned so much listening to you and I hope everyone listening has to and I'm going to see if there's anything we can do for you now because some of the biggest names in business and tech

[00:22:38] [SPEAKER_00]: of either be guess or listen to these podcasts so is there a person you'd love to have a private breakfast or lunch with who would that person be and why he or she might just be listening to this and be lovely to see if we can make something happen for you what would it be.

[00:22:52] [SPEAKER_01]: I think I'll go straight to the top Neil so I don't know but let's see maybe maybe so I actually in my years at sport that like last sort of seven years I grew quite a lot with together with my team and I always try to think like how can I be you know a good mentor to them a good coach a good

[00:23:12] [SPEAKER_01]: leader one thing that I would like to kind of hear more is you know how do you take your company like really well or your team really well through like a change and I always kind of admired Apple actually and I would love to have lunch lunch with their CEO team cook because I don't think

[00:23:33] [SPEAKER_01]: I think there were a lot of people who weren't sure how things will go after Steve Jobs but actually I feel the company did really well and that transition was actually pretty successful and I'd love to hear that personal story of personal and professional story and see what I can learn from it so I went straight to the top Neil I don't know I hope he's listening.

[00:23:55] [SPEAKER_00]: I do too let's see what we can manifest together here I'll put that out into the universe is out there forever now so hopefully someone somewhere is listening and can pop as pop you in their mind of Tim Cook see what we can make happen and for everyone listening just wanting to find out more information about the work you're doing there contact you or your team well do you like everyone to check out.

[00:24:17] [SPEAKER_01]: Usually I'm quite active on LinkedIn so best to contact me there and yeah happy to chat about this it's super exciting area we see a lot of movement across the industry.

[00:24:28] [SPEAKER_01]: And it's always nice to share experience.

[00:24:32] [SPEAKER_00]: Well as I said I've learned so much from you today from the evolution of sports broadcasting in the age of computer vision and AI and AI everywhere revolutionizing better I mean betting I think a lot of people don't realize that AI could be the answer to a $7 billion micro betting potential absolutely breathtaking figure

[00:24:50] [SPEAKER_00]: so I urge anyone listening to check out your site and connect with you personally but more than anything just thank you for joining me today and just let me know if Tim Cook gets in touch but thanks for joining me.

[00:25:02] [SPEAKER_00]: Thank you for having me.

[00:25:07] [SPEAKER_00]: A huge thank you to Luca from Sport Radar there I mean we've churned through that intricate world of AI computer vision and their transformative impact on sports broadcasting fan engagement and even the sector of sports betting.

[00:25:21] [SPEAKER_00]: And from understanding the little nuances of micro betting markets to the ethical considerations of using such advanced technologies in sports I think we covered a lot of ground and as we close I'm left pondering one final question.

[00:25:37] [SPEAKER_00]: With the rapid advancements in AI and technology how do you envision the future of sports entertainment evolving and what are the potential implications for the average sports from this is where I want to put the microphone in your direction.

[00:25:51] [SPEAKER_00]: And try and keep this conversation going and learn more about your vantage points what you like what you don't like what excites you what you're afraid of and everything in between.

[00:26:03] [SPEAKER_00]: You've heard from me you've heard from Luca this is your chance so email me tech blog writer outlook dot com Twitter LinkedIn Instagram just at Neil C Hughes if you are a long time listener or lurker and never emailed or never messaged or never connected.

[00:26:18] [SPEAKER_00]: This is your true calling to change that I'm the easiest guy in the world defined I will reply to you as long as it's not an instant sales pitch and you just want to connect with me and please do just that.

[00:26:29] [SPEAKER_00]: But that's it for today so I'll return again bright and early tomorrow but thank you for listening as always and until next time don't be a stranger.