Let Robots Do the Scheduling: John Stewart, co-Founder and CEO of Fastbreak.ai

:: 01:33

All right. John, I think it's fair to say that you're somewhat of an entrepreneur, serial entrepreneur. I would even throw in there. Was that true even when you were a kid? Were you the lemonade stand on the corner kind of guy?

:: 01:48

I wasn't the lemonade stand on the corner type of guy, but I did. I love to work. Always have loved to work. So I started my first job was when I was 12 years old, mucking out horse stalls.

:: 01:58

Oh, that's as far from what you're doing now as one could possibly imagine.

:: 02:04

Fair enough. But it is, you know, it's good from a work ethic standpoint. Sure. Really lets you appreciate when you can easier work. And then my next job was as a dishwasher at a pizza restaurant. So I did, in fact, work my way.

:: 02:16

When you are going up to the dishwasher at the pizza restaurant, you know, you started low.

:: 02:21

Yes. But my first entrepreneurial sort of experience was buying and selling comic books. So I figured out how to make money doing that. foray into entrepreneurship were you like the keeping them in the plastic sealed bags kind of guy or absolutely i was yeah okay keeping them in conditions bags with backs and i did a whole business out of trading them back and forth yeah i was able to get one of my sons into trade you know sports cards my honor he loves that and i did have enough my one son nick when he turned 18 i did still i still had about

:: 02:35

you like the keeping them in the plastic sealed bags kind of guy or absolutely i was yeah okay keeping them in conditions bags

:: 02:41

i was yeah okay keeping them in conditions bags with backs and i did a whole business out of trading them back and forth yeah i was able to get one of my sons into trade you know sports cards my honor he loves that and i did have enough my one son nick when he turned 18 i did still i still had about Oh, man, 4 ,000 comic books that I turned over. Stuff from the Silver Age of Marvel. So some that are pretty valuable.

:: 03:05

from the Silver

:: 03:10

I would think so.

:: 03:11

think so. You've got to keep those in some place where they're really safe. When did the technology thing really start to get its hooks into you, right? Because we're talking about mucking out horse stables, working as a dishwasher, selling comic books. Was technology always something that was riding shotgun along with these, or did it come to you later?

:: 03:29

No, it was. I always... Well, actually, it was my love of planes. So I was fascinated by airplanes,

:: 03:35

So I

:: 03:37

was fascinated by airplanes, wanted to figure out how to design them, build them. So engineering was the field I went to. I'm actually a mechanical engineer, did work in the aerospace industry. And I'm a pilot even today. I still fly myself to quite a few places. So it was really my love of aircraft, the design of aircraft, fighter jets, wanting to be involved in that industry. And that really moved me towards technology. So I went to WPI, Worcester Polytech, mechanical engineer by degree. I worked as an engineer in the aerospace industry for a while. And that was actually my first company. I formed an engineering services firm for the military, space and defense industry in 2003.

:: 04:09

an engineering

:: 04:14

I sold that in 2009 before moving into software.

:: 04:17

So then software, you developed your own company there, Map Everything, sold that to Salesforce. Kind of the quintess, I mean, am I getting that right?

:: 04:27

Close, Map Anything, Everything. But yes.

:: 04:31

Come on, there's an engineer's attention to detail right there. Get the name of the company right, Almy, for Pete's sakes. Sold that to Salesforce. Kind of the quintessential success story in that regard. When did sports start getting on your radar? When did you start thinking that there was an opportunity to apply your skills that you developed in that capacity for that vertical?

:: 04:57

Well, credit to where credit's due. That would be my co -founder, Chris Grower. So when I was running Map Anything, we were a field sales, field service, schedule and ride optimization company. One of the issues was that a new routing and scheduling engine hadn't been designed and built in, I don't know, since the 90s. It was Israeli Army for logistics. Legacy, legacy stuff. Legacy, legacy stuff. Nothing off the shelf would work for the problem. And I started researching this area of science, came across an individual introduced me to Chris.

:: 05:17

Army for

:: 05:31

And Chris at the time was working in -house on building it, having built the in -house system that the NBA currently uses. And Chris had a passion for sports scheduling for a long time. Now, he is a doctor's PhD in optimization research and commentatorial mathematics. Smart, smart guy. And, you know, also sort of a renaissance man, plays the violin, was a professional tennis player. Jeez. Yeah, I know. Right. Makes us all feel a little.

:: 05:54

Jeez.

:: 05:57

So lazy. A little short.

:: 05:59

little short. So he, you know, it was one of the recruiting tools I used, which was to say that, look, you know, come join me at Map Anything. Help me build the next generation routing the scheduling engine that we would need for these large scale field service field sales problems. And then one day we'll take a look at actually building a software company around sports scheduling. So it's like,

:: 06:19

So it's like, let's put that one on the shelf for a little bit to focus on this. And then once that domino falls, we can move on to that more passion play.

:: 06:29

Or Passion Play, exactly. So, no, I always thought we would spit it out of Map Anything. Instead, Salesforce bought us in May of 2019. I had a three -year non -compete, but in that time, I spent a lot more time with my kids. They're youth travel sports. I have five boys. Oh,

:: 06:43

sweet mother.

:: 06:45

Yeah, exactly. From ages 23 down to 14.

:: 06:51

There are people listening to this right now who just flinched in their chair or pulled their earbuds out of their ear to be like, oh, my gosh.

:: 06:59

But all of them play travel sports and still are with my two youngest. I've got a lacrosse player still. And so I realized that this was as big an issue for youth as it is professional. But when my non -compete was up, Chris approached me and said, look, let's do this thing. We formed the company Fastbreak. That was July 7, 2022. Now, from my perspective, putting sort of the investor's cap on, the businessmen's cap on, love the idea of doing it. But holistically speaking, professional sports is really not that big of an ecosystem.

:: 07:33

It's really not. It's hard to scale if you're just looking at pro sports.

:: 07:36

Correct. So even from day one, our vision was always, you know, we'll use professional sports to really work out and develop the AI technology. Then we'll bring it down market with the brand gravitas of having all the pro sports leagues and apply it to youth, which is what we're rapidly doing right now. So, you know. Again, if you look at it, by the time you get to 100th largest sports league, and at that point, I think you're maybe dealing like with power slap and professional pillow fighting.

:: 08:05

You know, you're sub 5 million in revenue, right? And there's a huge drop off in revenue by the time you get to the 20th largest sports league. And so, you know, from a business scale standpoint, I think of scale businesses as a business that can get itself to 100 million in revenue, something that's public company possible, let's say. You really do need to tap into the youth marketplace. which currently I know a lot of people who listen to your podcast probably saw that Times article recently, front page, youth sports is a $40 billion industry. Actually, they got the number wrong. It's actually 70 billion. It's bigger than that.

:: 08:36

actually 70 billion. It's bigger than that. Yeah.

:: 08:38

Well, they weren't including travel in that, but when you include travel in that, it's a 70 billion composite marketplace is what Americans spend on. you know, their kid's sports. Never underestimate what a parent is willing to spend on letting Johnny chase his NBA dream, right? I got to be honest with you,

:: 08:53

I got to be honest with you, John. This is the first example I've ever heard. I think I've ever heard of an entrepreneur saying the goal is to get the big pro teams as not so much the end goal, but the start goal. Right. Because, but to your point, like once you've got them, it was, but was it hard to break into them? I mean, those major professional sports leagues can be pretty insular. And so I'm interested in how, from a sales perspective, you were able to access those top tier content and top tier partners.

:: 09:37

So of that top 90 sports professional sports leagues, we have 50 of them currently about 50.

:: 09:43

No, you are the market leader.

:: 09:45

So the way we did it is this. Obviously, because of Chris and Tim, my other co -founder, Tim Carnes, we already had a relationship with the NBA. And so that was sort of the easy one to get back in the door. You know, Chris and Tim had basically built that entire system. And so the credibility was already established. And at the time, they were a known quantity at that point.

:: 10:04

time, they were a known quantity at that point.

:: 10:06

Known quantity. Plus, it was good timing because, as you recall, in 2022. they wanted to do this thing called the in -season tournament and the legacy system that they were using in -house was not designed to do the in -season tournament so we were able to apply our technology to help them solve that problem and that was sort of got us kick -started as a result of working the nba as well as some of the legacy you know relationships that chris had you know he used to do the some of the college conference schedules at his sort of kitchen table I'm not going to say pen and paper because it's all computer algorithms, but we were able to establish a foothold there. Now, it is very insular and it's where we have relationships. We won over like the NHL. We just won over because the NBA was using it. We were able to prove, you know, prove a very similar problem. They literally have a very similar problem. One additional college conferences, the bigger leagues, though, it became an acquisition strategy. I've purchased four companies, two of them in the pro sports space. One of them was Optimal Planning, and Optimal Planning had the relationship with the NFL and Major League Baseball, and they had half of Major League Soccer. We won the other half of Major League Soccer, so that was Major League Soccer, and then there was Major League Soccer Next Pro.

:: 11:21

And then over in Europe, really hard to build a footprint. We bought the market leader over there, so we've consolidated expertise as well. Working for the company directly or through the relationship through acquisition. We have 11 PhDs and scheduling experts on staff that work on these problems, on the engine that we - We've got 11 PhDs on the podcast as well.

:: 11:41

we - We've got 11 PhDs on the podcast as well. They're the ones who've helped me put this entire show together, John. It's an impressive thing.

:: 11:49

Oh, thank you.

:: 11:50

You did it. But I guess that's kind of the pieces that have to fall into place for you, isn't it, right? It's the established relationship with the NBA. And let's - Face it, I mean, if you're going to start with a pro league on a technology endeavor or something new, the NBA is not a bad place to start, right? I think that's kind of the brand that they've established from themselves from a business operations standpoint. They're very innovative.

:: 12:15

innovative. Very, very innovative. And they're very technology forward. Their leadership there understands how technology plays in. They're always ahead of the curve in terms of marketing the league, marketing the stars. They're super impressive from that regard. Really have a good mind for strategy. The main guy we work with is Evan Walsh. He's responsible for some of that strategy and very ahead of the game at all times when it comes to trying new technologies. And they understand it's a competitive marketplace. There's a lot of content out there to consume now. There's a reason why it seems like there's another new sports league popping up every other day. And so you're in competition. I believe power slap and pillow fighting were brought up earlier as key examples.

:: 12:55

I believe power slap and pillow fighting were brought up earlier as key examples.

:: 13:00

By the way, for those people who on your podcast who think I made those up, they should go to YouTube and Google power slap. They are not made up.

:: 13:05

They are not made up. And the power slap makes me flinch every time I watch it.

:: 13:11

The one that makes me laugh is that pillow fighting example.

:: 13:17

But, you know, so they know there's like we're in a tension economy now. That's what it is. And competition for the live eyeballs and which, you know, credit to them that they're not resting on their laurels. Right. They're always trying to innovate. They're always trying to try something new. So a lot of respect for the way that that league operates.

:: 14:14

Can you explain, John, just why scheduling for sports organizations, both pro all the way down to youth in your perspective, why is it so fraught? Because I saw in a Forbes interview, you said scheduling in general is the art of equally managing disappointment. You want to make sure everybody equally hates you. Why is that the case? Why is it so hard?

:: 14:39

Well, depending on the level. of sports there's different reasons for that but we can start at the highest level and work our way down right so going back to professional yeah the reason the scheduling is so fraught is that it's one of the biggest drivers on viewership viewership is the drivers on the value of the meteorites deal and understand that professional sports leagues are not sports leagues they're meteorite content creators yeah so that's the driver so there's

:: 15:05

yeah so

:: 15:06

that's the driver so there's You know, these leagues that we've worked with, they spend weeks, months sometimes trying to optimize for their customers. And their customers are not you and I. Their customers are ESPN, ABC, CBS, Fox. And so they really are concerned with making sure that they're delivering, you know, in the optimal amount of eyeballs. Because, look, every 10 years or every seven years, a new meteorites conversation starts. that's what really drives those those increases so a lot of time and thought and consideration is put into that right it's not it's why on christmas day or on thanksgiving you're not seeing the 28th and 29th ranked teams on those showcase things the schedule is built around what are going to be the most attractive i events to generate the most potential eyeballs right increasing media rights values along the way and then after that you have to take into consideration

:: 15:44

it's not it's why on christmas day or on thanksgiving you're not seeing the 28th and 29th ranked teams on those showcase things the schedule is built around what are going to be the most attractive i events to generate the most potential eyeballs right increasing media rights values along the way

:: 16:03

way and then after that you have to take into consideration You know, so obviously you've got your eyeballs and then you take into consideration, you know, fairness of schedule, rest patterns, things that are to keep the league competitive because the leagues are not competitive. People will get bored. No one likes being in a situation where anyone's disadvantaged so that they're always going to have a losing start to the season or that loses viewership as well. So it becomes second order function of not fair competitiveness is you lose eyeballs. So you have to sort of keep. All of that in mind.

:: 16:32

you have to sort of keep. All of that in mind. Right. We can't have the Sacramento Kings playing six night games back to back to back to back to back.

:: 16:40

Exactly. And, you know, exactly right. And you can't, you know, I'm a massive Charlotte, you know, Carolina Panthers fan along with the Hornets fan. And, you know, you wouldn't want, for example, the Panthers to get a murder's row of, OK, go play Kansas City, then play, then Dallas, like right down the line. You know, it creates a situation where it's, you know, these murder row situation is something that the leagues are cognizant of.

:: 17:03

yeah so you're but you're never going to make everybody happy right everybody's always going to find something wrong with the schedule so it's all about balancing that level of displeasure correct so and on the pro level it's all about the eyeballs right yeah you step down a level of college let's talk about college for a second look i think we all acknowledge that college sports is now professional sports where everybody's on a one -year deal whether it's the coach the ad the players and so ultimate free agency ultimate free agency

:: 17:13

so and on the pro level it's all about the eyeballs right yeah you step down a level of college let's talk about college for a second look i think we all acknowledge that college sports is now professional sports where everybody's on a one -year deal whether it's the coach the ad the players and so ultimate

:: 17:30

free agency ultimate

:: 17:32

free agency For them, there's a funny saying for college coaches. I've had even college coaches tell me this. There are good coaches and bad schedules. That's all there is. They're all very sensitive to how they get off the season, their win -loss record, how much rest they have before they play. Are they playing? Do they get the unfortunate of playing three teams in a row that are coming off buys? Things like that. That's rest pattern disparity. their jobs literally depend on that, right? In a way, even I think more so than the professional level. So there are same thing. And there's motivations there. And that's from Power 5. You go to a second tier or third tier conference. Well, it's cost of actually the program. It's logistics.

:: 18:22

It's logistics.

:: 18:23

Logistics. Flying people from one coast and back and forth or crossing time zones is expensive. And believe it or not, not every sport into the college level is a money sport. They don't get paid for every sport.

:: 18:36

Very few of them, actually.

:: 18:38

You know, women's field hockey, not to pick on that, it doesn't make them money. And you know what? And neither does men's volleyball, but they still have those sports. And, you know, so logistic costs become an issue.

:: 18:52

When we start having this conversation, we start talking about competitiveness and logistics and balance and coaches input. That is a, well, use the word, that's a lot of inputs. That's a lot of variables going into creating a very, very complex format for these teams to play. So can you, I'm almost terrified to ask this question. Can you talk about the development of the technology in as layman terms as you possibly can? Like, was it fair? Did it come together fairly simply? Did you have so many variables that it was like, oh my God, we need to like wait for the next development of AI to help produce this. Like, what was that process like?

:: 19:35

Some of what we're doing is applying techniques from other industries that have done for a long time, whether it's manufacturing floor optimization or even in our prior life where it was traveling salesperson, traveling service technician type problems. And so those general principles do apply to what would be a multi -variable optimization problem.

:: 19:58

Right.

:: 19:58

So, you know, with regard to sports, what makes it interesting is. What we tell people is we have hard constraints and soft constraints. And a better way to think about it is you've got a rule and you've got a preference. Rules may never be violated, no matter what. This is something that has to be.

:: 20:14

This is something that has to be.

:: 20:16

Has to be, right? A rule would be arena availability. If the arena is not available on that day, it simply can't have something. There's no plane in the parking lot.

:: 20:24

There's no plane in the parking lot.

:: 20:26

No plane in the parking lot. Exactly. So that's a rule. On the flip side, you've got a preference. A preference is just something you'd like to. to see happen or would not would prefer not to see happen yeah minimize tuesday night games minimize tuesday night games exactly now the ones that are preferences can have you know i prefer this one more versus this one and the way we express that is we can say with a penalty score as an example if i say that minimize tuesday nights is a 1000 right and i've got minimize thursday nights is a 500

:: 20:36

minimize tuesday night games minimize

:: 20:38

tuesday night games exactly now the ones that are preferences can have you know i prefer this one more versus this one and the way we express that is we can say with a penalty score as an example if i say that minimize tuesday nights is a 1000 right and i've got minimize thursday nights is a 500 You might infer correctly that that one on Tuesday nights is twice as important as the one on Thursday night. So we use scoring as a way to indicate, you know, basically preference. Weights and balances.

:: 21:11

Weights and balances. Weights and balances.

:: 21:12

and balances.

:: 21:13

Right. And then you can probably say, OK, if I'm going to have a preference, this preference is way more important than this preference. So we can sort of balance it out that way.

:: 21:21

And you can even do what we call it would be a nonlinear. Right. That's a linear approach, which is to say every time you violate one of those preferences or. Now its score goes from 500 to 1 ,000 to 2 ,000 because computers will simply say, well, I'll violate this one twice for every once I violate that one. So there is a balance that you have to basically design into the system. Now, here is the problem.

:: 21:44

Oh, my God. We're just getting to the problem now?

:: 21:45

just getting

:: 21:48

Human beings will say this is something, you know, someone may say something, but their actions will indicate something else, right? So there's a bias there, and that's where some AI comes into play. So something that you might tell me is really, really important, if I give you an eye test, what might come out of that eye test is, eh, not so much. So a lot of the AI that we do is around actually training our models with human input. You know, is this a better trip than that? So is that like a qualitative scoring on the part of somebody looking at the schedule to be able to evaluate it?

:: 22:17

know, is this a better trip than that? So is that like a qualitative scoring on the part of somebody looking at the schedule to be able to evaluate it? Or does it sound like a little bit more deeper than that?

:: 22:27

That is a subjective opinion of,

:: 22:32

say, a person in a league, right, that has actual qualitative, it may be four qualitative points or maybe 14 qualitative points. But what we're using to do is doing this sort of eye test method. is we're training the model and we're taking the human bias out of it. Because again, their choices will be a reflection of how they feel, but there's actual things behind it that make up that composite. And by doing that, we can actually train the model what they actually want, right? There's again, there's things that they say that can never happen. And then there's the things that they're actually willing to live with and accept. And so that's the careful balance that you can actually, you know, sort of get human machine to think like a human.

:: 23:17

The last thing a machine wants to do is think like the bag of cats that's going up between my ears. Were the leagues open to this process from the standpoint of comfort level, turning it over to a machine to develop this? Did they want more human oversight input into it? Or is it just depends on the league? Well,

:: 23:36

I think the leagues, you know, so our system, if you will, still requires the league to get input from all the stakeholders,

:: 23:41

still requires

:: 23:42

league to get input from all the stakeholders, whether it's the arena. Availability, the immediate rights partners with either the contractual obligations or their preferences, the team requests, and the ability to define all these rules around TRIP. So that part is all done by the human being. So they're setting up the problem.

:: 23:46

arena.

:: 24:03

And then our solution, our solver, if you will, we don't just solve for a schedule. Here is 20 schedules. All meet the rules. but then various level of your preferences. And then that gives the lead the opportunity to interact, move things around, interact with it while we're resolving, and then they can finalize it. So, or repair it, if you will, if something, you know, basically they just have to repair a certain section of it. So it's sort of a pre -process, solve, post -process system.

:: 24:23

interact with

:: 24:36

So there is still interaction. So they're not really giving up that much control. We're just doing the hard part of, we're hearing everything you say. We're interpreting some of that. And here's your options. Here's your vanilla, chocolate, strawberry, butter of a can.

:: 24:51

Which one feels like it's going to be the best flavor for you?

:: 24:55

Exactly. It's all ice cream. It all tastes good. Now you tell me which one tastes better.

:: 24:56

tastes good. Now you tell me which one tastes better. Every podcast that can have an ice cream analogy is instantly a good podcast right there. So thank you for that, John. I mean, the client roster, like we've talked about, it's about as robust as it gets, particularly at the professional level. We've got the NBA, WNBA, NHL, MLS. Serie A, Premiership Rugby. I mean, so this is now an international company working with leagues and teams all over the place.

:: 25:04

So thank you for that,

:: 25:21

and teams all over the place. Can you talk about some of the results that they've started to experience by adopting Fastbreak AI into their operations? And were there some that were more challenging to put into place than others based on how they operate?

:: 25:37

There definitely were some that are more challenging. There are certain things I can say, certain things I can't. the type of customers yeah we'll tell you you know here's a good example national rugby league they just recently came on for those unfamiliar in australia the nrl is basically the nfl here although they do have an afl which is australian football league which is an insane sport it is not for the faint of heart it is not your viewers should all youtube a clip on australian football league

:: 26:00

not for the faint of heart

:: 26:01

is not your viewers should all youtube a clip on australian football league It's nuts.

:: 26:09

NFL players look at that and say, not a chance. Exactly.

:: 26:14

But NRL, you know, they had a very complicated situation about, you know, these five day rest patterns. And we showed them, you know, before they signed an agreement that we're able to eliminate them. And that's a big thing from a fairness of play, injury, all that stuff. So I think that's a good example of it.

:: 26:26

And that's

:: 26:31

think that's a good example of it. I think we can just get them more of what they want because. The other methods before us, whether they were consultants or some commercial off -the -shelf software for optimization, they were never actually able to achieve more of the things they want. Now, here's the rub. As the media rights deals have gone up in value, as you can imagine, if you're paying more for something, you're going to have more requests. So balancing these requests has become more and more complicated. And I think what we're able to do...

:: 27:01

think what we're able to do... And where they really see the benefit is that they're able to meet all those requests and still produce good quality, fair schedules.

:: 27:12

Right. So the balance is going to be there the entire time. So you've now established, I mean, it's clearly gone beyond establishing yourself as the big dog in sports scheduling. And now that you have this proven product that, I mean, is obviously still continuing to grow, as we talked about, there's a lot more places to be able to take this. Are there other aspects of team operations that you're eyeing that you feel like are ripe for AI to change the way leagues are operating?

:: 27:42

Sure. So at the league level, we're doing a lot with the viewership prediction now. We have a new technology coming out next year. You can license and maybe it's not widely known or maybe it is, but you ever turn on a brand new flat screen television set and then you sit there and go next, next, next, next, next, next.

:: 28:01

Just did that two weeks ago. Did you ever read what's in those agreements? Generally, yes, every letter.

:: 28:10

Well, then you know that the hardware providers are collecting what you watch in 15 -second increments. And we license data like that. And using that data, we're actually able to build a very good prediction viewership model,

:: 28:11

then you know that the hardware

:: 28:22

a very good prediction viewership model, a viewership prediction model. Now, where this matters is the sports leagues. it's another tool for them to use during the scheduling to actually figure out how they can optimize for that attention or those eyeballs. So that's something that we've been working on for a couple of years now that we bring to market next year. There's a lot of interest in that at the professional level. And then at the team levels, because we have access at the league, we can get to the teams. We're actually releasing a suite. We're working with some NBA clubs right now. They go into beta next month. on sort of a schedule optimization for the back office operation for NBA clubs. And that's stuff like, you know, practice, you know, the segments they do on the day -to -day, their travel schedules, all of it. So sort of automating and using the same type of AI scheduling to be as efficient as possible for them. So that's, you know, that's also at the pro level. And then we've done some interesting things recently specific to certain sports. We did a project for the Jockey Club. The only reason I'm bringing it up is they posted our presentation on YouTube. So I guess it's public knowledge. But we showed... Well, there you go. Yeah.

:: 29:30

Well, there you go.

:: 29:32

For those of you not watching the video,

:: 29:33

those of you not watching the video, there was maybe a casual eye roll on the part of John right there.

:: 29:39

So basically what we showed for the use of our technology that we can have an influence on the handle, which is gambling, by reducing the overlap. for races as a knob to pull so you know reducing the overlap by three percent of all the you know systematically looking at every course race that goes on in this country at the same time we can actually optimize that schedule adjust it in these windows to make sure that no one's really overlapping or at least reducing the overlap by about 20 percent that drives a three percent increase in handle And if we're talking about 3 % increase on the handle for horse racing,

:: 30:15

we're talking about 3 % increase on the handle for horse racing, pretty soon you're going to be starting to talk about some pretty sizable numbers.

:: 30:22

It's $360 million plus or minus $30 million. So there you go, kids. This is math.

:: 30:30

Math does it again.

:: 30:33

That's a really interesting project where it's applicable. So there's a lot of areas and there's a lot of other things. on the pro side that we're having conversations. What's really kind of cool is because of the brand that we developed, the brand Gravitas, you know, we're out there in the public domain. We have a lot of really cool inbound projects now from professional sports leagues and teams. They want us to take a look at, see if the science is applicable. Oh, I'm assuming that they found you,

:: 30:56

I'm assuming that they found you, you solved this challenge for them. They're probably throwing a lot of different things at you. If you can do this, then maybe you can take a look at that. You're becoming the AI. guru, for lack of a better term, for sports in a certain respect.

:: 31:13

I think that's fair, sure. We're happy to play that role and we love what we do.

:: 31:19

We've talked obviously a lot about pro sports, but to your earlier point, youth sports is this massive business opportunity that I think a lot of organizations are trying to figure out how to get to. Whereas the pro sports are sort of small and highly concentrated. Youth sports is, I think, can be best described as atomized. I mean, there are hundreds of thousands of organizations that are involved with the decision making around youth sports. How do you effectively attack that particular market? Is it leveraging the brand relationship you have at the high level and using that as the magnet? Or do you have a process that allows you to do that more efficiently?

:: 32:04

Well, you are very correct about the extreme fragmentation in eSports, and that's been the bane of most technology companies in the space. So the investment world has an expression they call what they call a zombie company, which is a company that has gotten to a certain size but can't scale, but at the same time can't grow, and so they're just sort of stuck. And the extreme fragmentation in eSports has resulted in a plethora of these types of companies because, you know, Youth sports is not a monolith that breaks down from, first of all, before you even get to individual sports, it's scholastic, you know, your school sports or community sports like your YMCA or Little League or your travel, your elite travel, your tournament sports, adult sports. That's just one dividing line. Then you've got seasonality, male, female. You have it by sports, basketball, baseball, football, lacrosse, dance and gymnastics. It goes on and on and on. And so most technology providers, when they enter space. The first thing they normally tell an entrepreneur is focus, focus, focus, right? That's normally what you do. The challenge is if you focus on what you know or one segment, you develop a lock -in. So if we're talking about something like video streaming is a great example of this. If you ask me who the leader in youth sports is for video streaming, I have to ask you, are you talking about high school? Because that's huddle. If you're talking about ice hockey, that's bar and door. If it's basketball, it's feed the beast or ball or TV. But if you're talking about baseball, well, then that's game changer. You can literally have to identify the segment. And that's true of every point need in the whole space. Registration, payments, compliance, insurance, facilities. I have this grid of - I'm breaking out in hives. It is very, very challenging. So the way we've gone to market, the way we've attacked it, it said, okay, first, where can we leverage our brand gravitas? Who has the most challenging? scheduling problem and what we identified is the operators of these large -scale tournaments these tournaments if you you have kids who play sports you know about these things you show up for two days or three days and there's 400 teams there there's 12 locations that is a challenging scheduling problem in some cases it can be as challenging as a professional problem and you know we have a unique set of ip that you wouldn't develop for the youth sports marketplace but hey You know, we developed it from the pro leagues. We might as well leverage it down here. And so we can use the same engine to get in with these operators. And the next thing we did is we identified that we're not going to be a point solution. And we've been building out our single business in a box or platform such that even today, our platform currently does seven things that would normally require seven logins. But today we're their website, their e -commerce, their registration, their scheduling, their scoring, their travel. their electronic ticketing, and their data content provider. So that's eight things out of the 31 lines of revenue or operational needs that a tournament operator has to have to run a scale tournament. And remember, these tournaments are basically small businesses that set up. And break down in the course of two days to eight days.

:: 35:18

And I'm assuming most of them are run by people who got into it because they love the sport and they wanted to, you know, see and provide an opportunity for kids to do this. And they get into the middle of it and doing it. And maybe it goes from an 18 tournament. And then, you know, the next thing they know, they've got 32 teams coming in. And the next year it's 64. And it scales far beyond what their initial capabilities and capacity is. And they never built out infrastructure.

:: 35:40

they never built out infrastructure. And they never thought of. They're a victim of their own success. And now the car is doing 60 miles an hour and they're trying to change a tire while the car is going 60. It's a challenging problem. And we can come in with our expertise. And from this regard, my experience in the enterprise software space, right, is where is, I would say, the big advantage you would do is you have these platform plays, whether it's a Salesforce, SAP, Oracle. microsoft we can be that for these tournament operators we can give them the operating platform and then all their individual needs we plug into it now they have a single source of truth a single source of data and we're just picking off the individual needs that they have to satisfy to give a better experience their customers lower the cost their customers one of the things we do with our travel is we lower the cost of of hotel travel for the attendees the tournaments and they make more money they operate more efficiently their customers have a better experience And we can do this. And honestly, I think we're the only ones in the space actually doing it. It's an enterprise software playbook brought to the youth marketplace, leveraging our IP and technology and our brand gravitas at the pro level. So we have some unique tools to work with. You know, if another company wanted to do this, I'm not sure they could because we do, you know, we do have some advantages built in at this point.

:: 37:01

As we get wrapping up here, John, this is probably the golden age of sports and technology right now, certainly in terms of startups. There are no shortage of companies out there that are looking to access the markets that you are currently paddling around in. As someone who has had success bringing both non -sports technology companies up to conclusion and acquisition, I'm wondering what advice you have for other people out there that are looking to develop. tools or applications or use technology to reach the sports market in an effective way. Are there any thoughts that you have, any advice that you can share?

:: 37:41

Sure. I mean, I would tell you in this day and age, what's critical and key is speed. You cannot move slow anymore. Technology is no real advantage, which is a weird thing for me to say where we have unique IP on the scheduling end. How fast you're able to move, adjust, adapt to the marketplace will dictate your success, right? You know, that's your only moat. So it's speed plus the brand you develop equals your moat. And so you really need to be willing to pivot quickly, embrace all the new technology. I'll tell you right now, we have a smaller dev team with seven individual products here than going back a decade ago. we would have had 130 developers to support. In fact, we had 45 developers to support two products. And now we have a significantly smaller number to support, basically eight. And so embracing technology. So we're not just an AI company and the product we deliver. We're full AI across the board. It's how we develop, how we produce marketing materials. It's everything. It's how we live.

:: 38:47

It's all the things that you're also talking about too, like speed to pivot, speed to market is, I'm assuming assisted by the fact that you can be a much leaner organization. I mean, maybe not the best news for people who are studying computer science and coding right now at, you know, at higher levels, but it certainly does if you're a business operator, allow you to make decisions and move much more quickly because you can disseminate that strategy change amongst like to your team, seven people.

:: 39:18

A hundred percent that it is. I'm not sure I would tell anybody to go into, computer science i think you know going to psychology only from the standpoint of understanding how people think and interact with systems i would say the creative side the user experience so graphic design ui ux development would be another place almost all coding now is moving towards called vibe coding david you could sit down today and if i told you the tools the tool set to use you could describe a software system and the tools will literally build that system so

:: 39:56

My head exploding.

:: 39:58

It's where we're at. And that didn't really, it was in an infancy a year ago. It didn't exist two years ago. Imagine where we'll be in two years from now. Yeah,

:: 40:10

it's just really, I'm going to think of something and it's going to spring up on my screen almost.

:: 40:14

And so the very nature of a guy like a company like us is that. You know, you have to be willing to embrace these type of technology changes. And ultimately, it's better for the customers. We could be much more responsive to our customers' requests and features and functions. We move at a pace. You know, if I was to show you, for example, our ticketing platform, right? There's 37 electronic ticketing providers out there. There's three, what we call whales, one intermediate, and the rest are smaller. I'm sorry to break them that way, but you could get to them. You know,

:: 40:45

them. You know, hey, this is a quick whiteboard strategy session.

:: 40:48

Exactly. So there's, you know, a Ticketmaster, a StubHub, a SeatGeek. Those are whales. And then you've got your Vivid Tickets. And then after that, there's everyone else. And you've seen them. That's the GoFan and the EventBite. You know all these players. Or you've seen at least who I'm talking about.

:: 40:53

then you've got your

:: 41:03

I bought tickets from them.

:: 41:04

I bought tickets from them. In the time that we started developing on a platform, identifying the need, understanding that we had a captive audience in our operators and that the operators needed a ticketing platform, we closed a feature gap. all the way up to, in some cases, where the whales are. And we did it in six months. And by the way, and this is last weekend,

:: 41:27

our ticketing platform was used to sell across multiple operators, 14 ,000 tickets. So this is in production in the field.

:: 41:33

This is happening now. You're taking money for tickets.

:: 41:36

Exactly. Well, our operators are using our platform. That whole cycle, A, I don't think would have been possible. And B, would have taken years to do. years. And so that is sort of what you have to be able and willing to do if you're going to be in the technology space, whether it's sports, logistics, business operations, refrigeration, plumbing supplies, it doesn't really matter. This day and age is here. AI is here. I try to tell people all the time, AI is not going to take your job. Who's going to take your job is the person who uses AI to do your job. So we all need to embrace it. I'm sure there's tools that you can use to do the editing and the clips and develop. This is all done on magnetic tape,

:: 42:19

is all done on magnetic tape, John. I have a razor blade that I use to cut everything off. I'm old school, brother. Hey,

:: 42:29

I'm with John Stewart. He's the CEO and co -founder of Fast Break AI. This conversation has covered a lot of ground. It's simultaneously fascinating and terrifying to think about how much change is going to take place and how much the sports that we know and love are going to both benefit from it and be impacted by it. So, John, I want to say thank you for the time. But before I let you go, I'm going to dump you into the lightning round. All right. Series of questions for you. Just give me the first thing that pops into your mind. Are you ready? Ready. God, I'm smoking like a true engineer. He's ready to roll. You received your Bachelor in Science in Mechie from a Polytechnic Institute located in Western Massachusetts. John, please pronounce the name of that university as a true Massachusetts resident would.

:: 43:22

Worcester Polytechnic Institute.

:: 43:24

Very good. Yes. Worcester Polytech. You got to pack your car in the lot there. You got to take care of it. Right. Worcester. Right. For those of you who aren't. What are the number of times you could have been confused with the host of The Daily Show?

:: 43:39

Oh my God. I can't even count it anymore. It's a joke that everyone feels compelled to make at some point. I sort of lean into it now. Yeah.

:: 43:48

I will also say that this podcast host did not once reference it during our conversation until we got to the lightning round, which is sort of that free for all.

:: 43:57

Thank you so much. And by the way, I don't mind. It's funny. You lean into it.

:: 44:00

You lean into it. Like we talked about, you sold map anything to Salesforce for a kingly sum of money. What was the one ridiculous thing you bought yourself after the deal was done?

:: 44:12

Ridiculous thing that I bought myself? Well, I don't know about anything ridiculous that I bought, but my favorite thing that I did was I did set up, and I know this is going to sound weird, but I did set up a donor advised foundation with a bunch of money. And especially during COVID, I was able to give, I'm able to write a lot of $5 ,000 and $10 ,000 checks to people who need it. And that's the thing I enjoy the most. How about that? As opposed to the thing that I bought the most. As opposed to some sort of thing,

:: 44:34

opposed to the thing that I bought the most. As opposed to some sort of thing, it hits the soul in a good spot.

:: 44:39

It makes you feel better about you, believe it or not. Giving, and I will tell you that giving away or charity is really not about the person you're helping. It's about how it makes you feel, right? Selfishly. So I enjoyed that. So I didn't, that was probably the single largest purchase I made actually was the setting up the DAF. Actually, it absolutely was a single individual unit of thing.

:: 45:02

All right. Good answer, John. You know,

:: 45:04

You know, I'm a pilot. I had a small single engine plane, a Cessna. I upgraded to a Cirrus rather. I upgraded to a multi -engine plane. How about that? There you go.

:: 45:13

There you go. Now we're talking. All right. That's a good upgrade right there. All right. So you get a good dual answer right there. Favorite sport to play today?

:: 45:20

To play today or to watch or to play?

:: 45:23

To play today.

:: 45:25

Man, I am old and out of... Maybe watching sports on TV is what counts now.

:: 45:30

watching sports on TV is what counts now.

:: 45:33

My favorite sport to watch on TV is NFL football, of course. My favorite sport to watch in the stadium is NHL hockey. There's no better sport. There's no better sport live.

:: 45:42

no better sport. There's no better sport live. It's the truest of the true things in sports. And I think the sport to play,

:: 45:47

I think the sport to play, oh, man, you know, I don't really play one. By the way, when I was an athlete in high school, And these don't really translate to being an adult. I was a wrestler and a pole vaulter. So they don't really adult pole vaulting league. That might be a first.

:: 46:04

might be a first.

:: 46:09

Combine those. If we can figure out how to pull off wrestling pole vaulting, that would be something else. All right. Last one. You've got five kids. You have five boys. So first of all, the amount of spackle and hole repair for your walls in your house. I can't even imagine. And I'm assuming that no amount of AI is going to make your sports travel any easier. So what is going to be next in the developmental pipeline? Sport parent cloning or tournament teleportation?

:: 46:33

Ooh, good one. I think I like the idea of teleportation because it's travel that kills you. That would be my preference.

:: 46:41

Jon Stewart, thanks for the time today.

:: 46:44

Thank you, Dave. I really appreciate you having me. Enjoyed the conversation.