1 00:00:00,280 --> 00:00:03,760 Speaker 1: This is the business of sports. Should Major League Baseball 2 00:00:04,000 --> 00:00:06,840 Speaker 1: shorten up the season? How do we present football to 3 00:00:06,920 --> 00:00:08,920 Speaker 1: the audience of the future. I don't think that most 4 00:00:08,920 --> 00:00:12,040 Speaker 1: players understand the power that they have. Michael, the future 5 00:00:12,080 --> 00:00:15,520 Speaker 1: of IndyCar racing is looking bright. Scott sash Neck very 6 00:00:15,560 --> 00:00:18,959 Speaker 1: basic math here, more bidders means more money. Evan Nobody Williams, 7 00:00:18,960 --> 00:00:22,079 Speaker 1: the team value has essentially quadruples. And the leaders in 8 00:00:22,120 --> 00:00:25,480 Speaker 1: the sports industry. Time to bringing our guest cal slide Runner, 9 00:00:25,600 --> 00:00:29,320 Speaker 1: National Hockey League Commissioner Gary Bettman, Atlanta Braves president Derek Schiller, 10 00:00:29,400 --> 00:00:34,720 Speaker 1: Patriots President Jonathan Kraft. Bloomberg Business of Sports from Bloomberg Radio. Hello, 11 00:00:34,840 --> 00:00:37,919 Speaker 1: I'm Evan, Nobby Williams and Michael Barr. Every week at 12 00:00:37,920 --> 00:00:41,720 Speaker 1: this time plus Mondays and Wednesdays, we explore the big 13 00:00:41,720 --> 00:00:44,320 Speaker 1: money issues in the world of sports. We missed you, Scott. 14 00:00:44,360 --> 00:00:47,040 Speaker 1: Today we speak with former Major League Baseball pitcher Michael 15 00:00:47,040 --> 00:00:50,239 Speaker 1: Swimmer about the business of sports betting, data and analytics. 16 00:00:50,240 --> 00:00:52,520 Speaker 1: But first, let's look at some of our top stories 17 00:00:52,520 --> 00:00:55,040 Speaker 1: of the week, beginning with next year's Super Bowl in 18 00:00:55,120 --> 00:00:58,960 Speaker 1: Miami and how much it will cost taxpayers there. Yeah, 19 00:00:59,000 --> 00:01:01,240 Speaker 1: so we have a kind of a full accounting right now, 20 00:01:01,280 --> 00:01:04,440 Speaker 1: it's looking like twenty million dollars. Uh. Four of those 21 00:01:04,480 --> 00:01:07,160 Speaker 1: million go down to go over to the Dolphins for 22 00:01:07,160 --> 00:01:09,639 Speaker 1: for hosting the thing. You know there there there's various 23 00:01:09,680 --> 00:01:14,400 Speaker 1: other costs, you know, police forces, firefighters, waste management. You know, 24 00:01:14,680 --> 00:01:18,039 Speaker 1: they're doing improvements across the county, soccer fields, football fields, 25 00:01:18,080 --> 00:01:20,880 Speaker 1: things like that. Um. But as we put it all together, 26 00:01:21,680 --> 00:01:25,759 Speaker 1: Miami taxpayers and Miami Dade County taxpayers twenty million dollars 27 00:01:25,800 --> 00:01:28,039 Speaker 1: to host the Super Bowl. I always wonder because every 28 00:01:28,040 --> 00:01:30,760 Speaker 1: time you hear somebody in a city bidding for the 29 00:01:30,800 --> 00:01:33,199 Speaker 1: Super Bowl, you always hear, well, it's going to bring 30 00:01:33,200 --> 00:01:35,199 Speaker 1: in business. It's going to bring in this is gonna 31 00:01:35,200 --> 00:01:38,240 Speaker 1: bring in that. And now you hear this is gonna 32 00:01:38,280 --> 00:01:41,400 Speaker 1: cost the taxpayers, yeah, and and and those. You know, 33 00:01:41,480 --> 00:01:44,160 Speaker 1: the the numbers on what it's going to bring in. 34 00:01:44,200 --> 00:01:48,200 Speaker 1: The economic impact studies are super controversial, to the point 35 00:01:48,240 --> 00:01:50,000 Speaker 1: that I I don't even want to give whatever the 36 00:01:50,080 --> 00:01:53,280 Speaker 1: number was that that Miami estimated on the show right now. 37 00:01:53,320 --> 00:01:55,480 Speaker 1: Typically you know, you move the decimal place to the 38 00:01:55,560 --> 00:01:57,960 Speaker 1: left one and that might be the number. So you know, 39 00:01:58,040 --> 00:02:02,560 Speaker 1: certainly Miami businesses, the the city the county. Everyone's expecting, 40 00:02:02,920 --> 00:02:05,000 Speaker 1: you know, a big windfall here from the super Bowl, 41 00:02:05,120 --> 00:02:07,440 Speaker 1: and it may happen right there. There's gonna be you know, 42 00:02:07,640 --> 00:02:10,120 Speaker 1: thousands and thousands of people that come to town for 43 00:02:10,240 --> 00:02:12,320 Speaker 1: possibly even as long as a week or maybe even 44 00:02:12,320 --> 00:02:16,639 Speaker 1: a little longer next February. But generally, you know, the 45 00:02:16,639 --> 00:02:19,880 Speaker 1: the impact of hosting big events like that is generally 46 00:02:19,960 --> 00:02:23,280 Speaker 1: very overstated. Well, it will obviously bring in revenue. You're 47 00:02:23,320 --> 00:02:27,120 Speaker 1: gonna have the restaurants all in the area, in all 48 00:02:27,160 --> 00:02:31,600 Speaker 1: the cabs and and livery driver, all that will be booked, 49 00:02:31,639 --> 00:02:34,160 Speaker 1: for sure, that's all gonna That's all well and good. 50 00:02:34,160 --> 00:02:36,639 Speaker 1: You're gonna have the limos and all this. But I 51 00:02:37,000 --> 00:02:42,200 Speaker 1: still don't understand how it can cost taxpayers money, uh, 52 00:02:42,400 --> 00:02:45,600 Speaker 1: for an event that you want in your city. I 53 00:02:45,600 --> 00:02:48,400 Speaker 1: I don't understand that. Yeah, and again the way these 54 00:02:48,440 --> 00:02:50,520 Speaker 1: accounting works, I mean, the thing you need to take 55 00:02:50,560 --> 00:02:52,640 Speaker 1: into account is that, you know a lot of people 56 00:02:52,639 --> 00:02:54,600 Speaker 1: are gonna come to Miami for the super Bowl, for sure. 57 00:02:54,919 --> 00:02:57,240 Speaker 1: There are probably also people that we're planning to go 58 00:02:57,280 --> 00:02:59,920 Speaker 1: to Miami for vacation in February that are choosing not 59 00:03:00,000 --> 00:03:02,280 Speaker 1: to because the super bowls in town. Right and and 60 00:03:02,360 --> 00:03:04,560 Speaker 1: for people who live locally, you know, they may spend 61 00:03:04,560 --> 00:03:07,600 Speaker 1: money to go to the NFL Fan Zone and other events, 62 00:03:08,000 --> 00:03:10,280 Speaker 1: but you know that might mean that they're spending less 63 00:03:10,280 --> 00:03:12,200 Speaker 1: money doing other things. They may not go to the 64 00:03:12,240 --> 00:03:15,639 Speaker 1: restaurant in March because they went out kind of to 65 00:03:15,960 --> 00:03:18,639 Speaker 1: hit the town for Super Bowl in February, right, So, 66 00:03:18,639 --> 00:03:21,120 Speaker 1: so so a lot of money just just moves around. Um. 67 00:03:21,160 --> 00:03:24,520 Speaker 1: But yeah, twenty million dollars And it's not often that 68 00:03:24,639 --> 00:03:27,440 Speaker 1: you know, the owner of the local NFL team get 69 00:03:27,560 --> 00:03:31,320 Speaker 1: gets a gets a large check for for for hosting 70 00:03:31,320 --> 00:03:33,600 Speaker 1: the thing. But with Stephen Ross, the owner of the Dolphins, 71 00:03:33,800 --> 00:03:37,040 Speaker 1: has kind of a unique partnership and a unique contract 72 00:03:37,080 --> 00:03:39,320 Speaker 1: down in Miami. But yeah, four million of that goes 73 00:03:39,360 --> 00:03:41,800 Speaker 1: to the Dolphins. All the other costs are you know, 74 00:03:41,880 --> 00:03:45,280 Speaker 1: your standard, you know, municipal costs for holding a week 75 00:03:45,320 --> 00:03:47,920 Speaker 1: long event in your city. Let's move on now to 76 00:03:48,120 --> 00:03:51,560 Speaker 1: the Pocono Raceway. First of all, the IndyCar Race. Uh, 77 00:03:51,680 --> 00:03:55,360 Speaker 1: congratulations to will Power for winning winning the race. But 78 00:03:55,760 --> 00:03:59,840 Speaker 1: it was weather effected, so it was shortened by about 79 00:04:00,000 --> 00:04:02,960 Speaker 1: company for laps because you can't have lightning in the area. 80 00:04:03,000 --> 00:04:06,480 Speaker 1: And that's what was happening. There's no other way for 81 00:04:06,520 --> 00:04:08,600 Speaker 1: me to put it. This is my home track, but 82 00:04:08,840 --> 00:04:12,640 Speaker 1: it's a dangerous track. And even Mario Andretti said this, 83 00:04:13,240 --> 00:04:16,760 Speaker 1: Uh he said, Pocono is not for sissy's that's a 84 00:04:16,960 --> 00:04:20,240 Speaker 1: direct quote. You are a clock in big time for 85 00:04:20,320 --> 00:04:24,520 Speaker 1: indy cars. This year we saw another big smash up. 86 00:04:25,400 --> 00:04:28,760 Speaker 1: And you have to remember with an open cockpit and 87 00:04:28,800 --> 00:04:32,160 Speaker 1: you see a car ride up against the wall with 88 00:04:32,200 --> 00:04:37,359 Speaker 1: the cockpit that way against the wall, you have a 89 00:04:37,400 --> 00:04:40,720 Speaker 1: collective hold your breath. It's like, oh my goodness. Fortunately 90 00:04:40,760 --> 00:04:42,920 Speaker 1: everybody was okay in this one, but there have been 91 00:04:42,960 --> 00:04:48,160 Speaker 1: other wrecks. Last year's race, uh, he was, yeah, exactly, 92 00:04:48,240 --> 00:04:50,840 Speaker 1: and then someone died on the track four or five 93 00:04:50,880 --> 00:04:54,400 Speaker 1: years ago. Yeah, so this happens. And the track is 94 00:04:54,440 --> 00:04:57,840 Speaker 1: a very fast track for people not familiar, they call 95 00:04:57,920 --> 00:05:04,880 Speaker 1: it the Tricky Triangle and your clocking laps, well, it's exactly, 96 00:05:05,440 --> 00:05:07,479 Speaker 1: and it's two and a half mile, so you're you're 97 00:05:07,480 --> 00:05:13,120 Speaker 1: flying and you have probably the longest straight away on 98 00:05:13,560 --> 00:05:16,839 Speaker 1: the Indy car circuit. I mean, the whole front stretch 99 00:05:17,360 --> 00:05:20,200 Speaker 1: is where all the grand stands and you're flying, so 100 00:05:20,240 --> 00:05:22,719 Speaker 1: obviously your foot to the floorboard when you're doing this 101 00:05:22,760 --> 00:05:24,400 Speaker 1: and then you gotta woe it down when you go 102 00:05:24,560 --> 00:05:29,560 Speaker 1: into one and everybody's darting and diving where that's where 103 00:05:29,600 --> 00:05:31,719 Speaker 1: you see the start of a lot, and then everybody's 104 00:05:31,760 --> 00:05:35,320 Speaker 1: heading into turn two, which really sets everything up because 105 00:05:35,320 --> 00:05:39,440 Speaker 1: you're trying to get yourself set up. And that's what 106 00:05:39,680 --> 00:05:43,640 Speaker 1: happened in this case in this year's race. Uh that 107 00:05:44,200 --> 00:05:46,960 Speaker 1: two cars touched and and then you had five cars 108 00:05:46,960 --> 00:05:48,720 Speaker 1: and it was a big message. So at what point, 109 00:05:48,800 --> 00:05:52,240 Speaker 1: if you're Indy Car, do you say we can't race 110 00:05:52,360 --> 00:05:54,520 Speaker 1: here anymore? I mean, I I don't really follow any 111 00:05:54,520 --> 00:05:57,039 Speaker 1: car much. I know that you do. Uh. There was 112 00:05:57,120 --> 00:06:00,640 Speaker 1: so much chatter even I I recognized it during this 113 00:06:00,720 --> 00:06:04,760 Speaker 1: race on on August about you know, criticizing Indie Car 114 00:06:04,839 --> 00:06:06,880 Speaker 1: for choosing to go there. It certainly seems as though 115 00:06:07,200 --> 00:06:10,000 Speaker 1: there's been chatter about Pocono maybe not being a safe 116 00:06:10,080 --> 00:06:14,719 Speaker 1: racetrack for for Indiecar in the past. At some point, 117 00:06:14,800 --> 00:06:16,479 Speaker 1: do you step in if you're Indy Car and say, 118 00:06:16,480 --> 00:06:18,240 Speaker 1: you know what, you know, we're looking at our schedule 119 00:06:19,240 --> 00:06:21,880 Speaker 1: and we're not going to go to IndyCar until we 120 00:06:21,960 --> 00:06:24,080 Speaker 1: know that it's a place where you know, people aren't 121 00:06:24,080 --> 00:06:25,640 Speaker 1: going to be sent to the hospital every year. Well, 122 00:06:25,640 --> 00:06:28,920 Speaker 1: I'm gonna go and quote the great Mario Andretti. He said, 123 00:06:29,760 --> 00:06:32,359 Speaker 1: removing an Indy car race from Pocono would be a 124 00:06:32,360 --> 00:06:35,640 Speaker 1: big mistake, and I and I agree. Now, obviously I 125 00:06:35,680 --> 00:06:39,039 Speaker 1: don't want to see anything major league happened at the 126 00:06:39,040 --> 00:06:42,600 Speaker 1: track to to any driver. But the racing is exciting, 127 00:06:43,320 --> 00:06:46,400 Speaker 1: uh and and and some and sometimes it's just been 128 00:06:46,960 --> 00:06:49,279 Speaker 1: just awful luck. And I'm gonna talk about the lightning. 129 00:06:49,520 --> 00:06:53,239 Speaker 1: Why they shorten the race at Pocono because of lightning 130 00:06:53,520 --> 00:06:56,440 Speaker 1: at a NASCAR event? And I was there when this happened. 131 00:06:56,800 --> 00:07:01,279 Speaker 1: I think in the race ends, we're all trying to 132 00:07:01,320 --> 00:07:04,040 Speaker 1: get out in the parking lot and there was this 133 00:07:04,200 --> 00:07:06,520 Speaker 1: big bolt of lightning. I mean, it just scared the 134 00:07:06,520 --> 00:07:10,720 Speaker 1: living but Jesus out of everybody. And unfortunately during that 135 00:07:11,640 --> 00:07:14,800 Speaker 1: person who was at his car, he had the trunk 136 00:07:14,840 --> 00:07:18,600 Speaker 1: up and he was killed. And and that's so when 137 00:07:18,600 --> 00:07:20,840 Speaker 1: you hear it's like, why are they shortening the races 138 00:07:20,880 --> 00:07:23,080 Speaker 1: and why are they doing this because of whether this 139 00:07:23,160 --> 00:07:25,960 Speaker 1: is why you can't have lightning in the area, not 140 00:07:26,080 --> 00:07:28,520 Speaker 1: just in racing, but any sporting event. One other thing 141 00:07:28,560 --> 00:07:30,280 Speaker 1: I did want to ask you. I saw video of 142 00:07:30,320 --> 00:07:32,960 Speaker 1: them fixing the track after the initial crash, which I 143 00:07:32,960 --> 00:07:35,040 Speaker 1: think was on the first lap, They were putting up 144 00:07:35,760 --> 00:07:40,440 Speaker 1: fencing and zip tying it to the retaining netting. Is 145 00:07:40,440 --> 00:07:44,040 Speaker 1: that something that is that standard for safety precausions? Well, 146 00:07:44,080 --> 00:07:47,480 Speaker 1: he's zip tying a piece of chain link fence. YEA, 147 00:07:48,320 --> 00:07:52,880 Speaker 1: a very bad way to fix it. It's one of 148 00:07:52,880 --> 00:07:56,480 Speaker 1: those things where is he can't race without the safety 149 00:07:56,520 --> 00:07:59,440 Speaker 1: netting and part of that wreck took out the safety netting. 150 00:07:59,680 --> 00:08:03,320 Speaker 1: So this was kind of like a makeshift Jerry Riggs 151 00:08:03,360 --> 00:08:07,280 Speaker 1: style of trying to put this together. That's amazing. Oh man, 152 00:08:07,680 --> 00:08:10,960 Speaker 1: Uh and now let's move on. Uh, let's talk about Google. 153 00:08:11,320 --> 00:08:14,080 Speaker 1: And in fact, I wasn't even sure that I didn't 154 00:08:14,080 --> 00:08:17,200 Speaker 1: know that he even had a band on Fantasy sports ads, 155 00:08:17,240 --> 00:08:20,920 Speaker 1: but now they're lifting that. Yeah. This is an interesting 156 00:08:20,960 --> 00:08:22,640 Speaker 1: one and was sent and sent to us by by 157 00:08:22,640 --> 00:08:25,559 Speaker 1: a listener, So so a shout out to Jay Um. Yeah. 158 00:08:25,600 --> 00:08:29,160 Speaker 1: So you know, previously DFS companies have not been able 159 00:08:29,240 --> 00:08:33,800 Speaker 1: to through Google advertise their their pay to play games. Um, 160 00:08:33,840 --> 00:08:36,439 Speaker 1: and that is that's a big deal, right. Google is 161 00:08:36,240 --> 00:08:38,439 Speaker 1: a is a huge company. There's a reason a hundred 162 00:08:38,440 --> 00:08:42,240 Speaker 1: and sixteen billion dollars that's their revenue. Vast majority of 163 00:08:42,280 --> 00:08:45,240 Speaker 1: that comes from advertising. It's because they're good at it 164 00:08:45,280 --> 00:08:47,760 Speaker 1: and they're effective, and they have Google Search and YouTube 165 00:08:47,760 --> 00:08:50,400 Speaker 1: and a number of other platforms where those ads get seen. 166 00:08:50,800 --> 00:08:52,240 Speaker 1: So this is a pretty big deal. I think it's 167 00:08:52,240 --> 00:08:53,920 Speaker 1: a big deal for a few different groups. I mean, 168 00:08:53,920 --> 00:08:57,000 Speaker 1: obviously a big deal for DFS companies, and that includes 169 00:08:57,440 --> 00:08:59,840 Speaker 1: draft Kings, that includes FanDuel, that also includes, you know, 170 00:08:59,880 --> 00:09:03,000 Speaker 1: the the number of other smaller companies that might not 171 00:09:03,080 --> 00:09:05,200 Speaker 1: have the name recognition that they do. And some of 172 00:09:05,200 --> 00:09:07,960 Speaker 1: them are actually DFS only right, they're not even doing 173 00:09:08,000 --> 00:09:10,720 Speaker 1: sports betting at all. Um, So you know, this opens 174 00:09:10,800 --> 00:09:13,120 Speaker 1: up a whole new opportunity there, and it probably has 175 00:09:13,160 --> 00:09:15,360 Speaker 1: an impact for for other sites as well where those 176 00:09:15,360 --> 00:09:17,760 Speaker 1: ads are going to show up. Right if you, if 177 00:09:17,800 --> 00:09:21,560 Speaker 1: you're you know operator, own a sports adjacent side of 178 00:09:21,640 --> 00:09:24,000 Speaker 1: some sort where Draft Kings and fandal would like to 179 00:09:24,000 --> 00:09:26,800 Speaker 1: advertise but haven't been able to yet. Uh, this probably 180 00:09:26,840 --> 00:09:29,079 Speaker 1: opens up some new avenues for you. Now let's get 181 00:09:29,080 --> 00:09:31,560 Speaker 1: to this week's interview with former Major League Baseball pitcher 182 00:09:31,600 --> 00:09:33,880 Speaker 1: Michael Swimmer. Michael had a two year career with the 183 00:09:33,880 --> 00:09:37,480 Speaker 1: Philadelphia Phillies and after leaving baseball, he founded Big League Advance, 184 00:09:37,760 --> 00:09:40,680 Speaker 1: a company that invests in minor league baseball players, offering 185 00:09:40,760 --> 00:09:43,680 Speaker 1: upfront cash in exchange for a percentage of future major 186 00:09:43,760 --> 00:09:47,560 Speaker 1: league earnings. His latest venture is Jambo's Picks, a subscription 187 00:09:47,559 --> 00:09:50,280 Speaker 1: service that sells sports betting advice. Michael, thank you for 188 00:09:50,360 --> 00:09:52,600 Speaker 1: joining us. Thank you very much for having me. Michael, 189 00:09:52,640 --> 00:09:54,280 Speaker 1: you and I spoke for the first time, you know, 190 00:09:54,360 --> 00:09:56,080 Speaker 1: last week. You know, we talked a lot about your 191 00:09:56,080 --> 00:09:58,240 Speaker 1: two businesses, which are are fascinating and we're gonna get 192 00:09:58,240 --> 00:10:01,280 Speaker 1: into all that here, but starters. Kind of the common 193 00:10:01,320 --> 00:10:03,720 Speaker 1: thread between the two of them is data. You know, 194 00:10:03,760 --> 00:10:07,760 Speaker 1: they both use algorithms, analytics, predictive modeling, and it made 195 00:10:07,800 --> 00:10:10,520 Speaker 1: me think about, you know, the saying in business data 196 00:10:10,600 --> 00:10:13,320 Speaker 1: is the new oil. I'm curious, from where you sit, 197 00:10:13,440 --> 00:10:16,600 Speaker 1: how well does the sports business world use data. Are 198 00:10:16,640 --> 00:10:18,680 Speaker 1: they cutting edge? Are they way behind? Are they in 199 00:10:18,679 --> 00:10:21,280 Speaker 1: the middle of What does it look like from your perspective, Well, 200 00:10:21,320 --> 00:10:23,880 Speaker 1: it depends on the sport and it depends, you know, 201 00:10:24,320 --> 00:10:25,880 Speaker 1: how how it looked at. The data is the oil? 202 00:10:25,880 --> 00:10:27,839 Speaker 1: Like I couldn't agree more with that comment. I mean, 203 00:10:27,840 --> 00:10:30,400 Speaker 1: everything we do is data driven. I think sports has 204 00:10:30,440 --> 00:10:31,800 Speaker 1: a long way to go. If I had to give 205 00:10:31,840 --> 00:10:33,880 Speaker 1: it a score between one and tent, I'd probably put 206 00:10:33,920 --> 00:10:36,480 Speaker 1: it about a three right now. But that's in general 207 00:10:36,520 --> 00:10:40,120 Speaker 1: in the entire sports world. Obviously, for example, baseball and 208 00:10:40,200 --> 00:10:43,240 Speaker 1: basketball are far more advanced than football and even European 209 00:10:43,240 --> 00:10:46,120 Speaker 1: soccer right now. But that's just kind of an in 210 00:10:46,200 --> 00:10:48,720 Speaker 1: general in terms of analytics teams and how analytics and 211 00:10:48,840 --> 00:10:52,960 Speaker 1: data are being used. But even in basketball and in baseball, 212 00:10:53,000 --> 00:10:56,679 Speaker 1: there are ways to use data that are that aren't 213 00:10:56,679 --> 00:10:59,199 Speaker 1: currently being used in stuff that that we're doing over 214 00:10:59,240 --> 00:11:01,959 Speaker 1: a typically advance to gimbos. Yeah, I mean, I agree 215 00:11:01,960 --> 00:11:03,560 Speaker 1: with you. I think three is kind of a good number, 216 00:11:03,559 --> 00:11:06,120 Speaker 1: and I think that would surprise a lot of sports 217 00:11:06,120 --> 00:11:09,800 Speaker 1: fans who maybe think of sports as kind of the 218 00:11:10,320 --> 00:11:13,640 Speaker 1: front the leading edge of a lot of of analytic 219 00:11:13,679 --> 00:11:17,319 Speaker 1: and technology. Yeah, I mean, you know, sports fans, it's funny. 220 00:11:17,320 --> 00:11:20,400 Speaker 1: It's hard to watch games now, especially even commentators. These 221 00:11:20,440 --> 00:11:22,720 Speaker 1: are experts in the field, and some of those things 222 00:11:22,720 --> 00:11:24,120 Speaker 1: they say, you just want to scratch your head. I 223 00:11:24,200 --> 00:11:26,079 Speaker 1: I just watched games on mut now and listen to 224 00:11:26,200 --> 00:11:28,240 Speaker 1: music because I go, it's just too hard for me. 225 00:11:28,760 --> 00:11:31,920 Speaker 1: So so take me back. You're a major league baseball pitcher. 226 00:11:31,960 --> 00:11:35,680 Speaker 1: And your interest in statistics dates back right into into 227 00:11:35,679 --> 00:11:38,000 Speaker 1: your time as a picture right. Yeah, well actually before 228 00:11:38,040 --> 00:11:40,520 Speaker 1: that high school I took a p stats placed out 229 00:11:40,559 --> 00:11:43,280 Speaker 1: all the credits at UVA. Just always loved numbers, have 230 00:11:43,360 --> 00:11:47,000 Speaker 1: always loved math um and able to you know, parlay 231 00:11:47,120 --> 00:11:50,720 Speaker 1: that into pitching and being able to build models to 232 00:11:50,880 --> 00:11:54,240 Speaker 1: try to get hitters out and and really you know, 233 00:11:54,400 --> 00:11:57,400 Speaker 1: believe in the chef match that's happening with each pitch 234 00:11:57,480 --> 00:11:59,920 Speaker 1: from a picture and a hitter, and it's something I 235 00:12:00,080 --> 00:12:02,160 Speaker 1: always had a passion for from in love with then 236 00:12:02,280 --> 00:12:04,319 Speaker 1: worked out pretty well. So tell me a bit. I mean, 237 00:12:04,400 --> 00:12:08,000 Speaker 1: you you built a model, a pitch sequencing model while 238 00:12:08,080 --> 00:12:10,800 Speaker 1: you were a major league baseball pitcher, right, what exactly 239 00:12:10,800 --> 00:12:13,480 Speaker 1: did that look like? So in baseball, you gotta you 240 00:12:13,520 --> 00:12:16,040 Speaker 1: have a picture and a hitter, and hitters have tendencies 241 00:12:16,080 --> 00:12:18,400 Speaker 1: and they have patterns, and you can recognize those patterns 242 00:12:18,400 --> 00:12:21,400 Speaker 1: as a picture. You know, before in high school, for example, 243 00:12:21,480 --> 00:12:23,280 Speaker 1: you know, I had enough stuff to get by and 244 00:12:23,280 --> 00:12:26,280 Speaker 1: get through. Then the college level, freshman year, I had 245 00:12:26,320 --> 00:12:28,560 Speaker 1: a ten point a d r A and it's really 246 00:12:28,600 --> 00:12:30,600 Speaker 1: a big wake up call, and had a pitching coach 247 00:12:30,720 --> 00:12:33,760 Speaker 1: and a manager that called the game, and they were 248 00:12:34,000 --> 00:12:36,200 Speaker 1: walking me through their ideas on how to call games 249 00:12:36,200 --> 00:12:39,160 Speaker 1: looking at what hitters are doing. I then took that knowledge, 250 00:12:39,160 --> 00:12:42,560 Speaker 1: which was very subjective knowledge from the experts, and then 251 00:12:42,800 --> 00:12:45,360 Speaker 1: tried to model that out. And I modeled out hitters. 252 00:12:45,600 --> 00:12:47,080 Speaker 1: You know where they where they put their feet in 253 00:12:47,080 --> 00:12:49,040 Speaker 1: the box, where their first step is, where their body 254 00:12:49,080 --> 00:12:52,360 Speaker 1: position is going their best, their arm length arm lenk 255 00:12:52,480 --> 00:12:54,880 Speaker 1: is actually pretty important, and know how much of the 256 00:12:54,920 --> 00:12:57,599 Speaker 1: plate they can or cannot cover. You especially see a 257 00:12:57,600 --> 00:12:59,640 Speaker 1: lot of short arm hitters stand right on top of 258 00:12:59,679 --> 00:13:02,640 Speaker 1: play that you think the inside corners available because but 259 00:13:02,720 --> 00:13:04,440 Speaker 1: they have those shore arms are actually able to get 260 00:13:04,480 --> 00:13:06,920 Speaker 1: the ferrel to the inside corp. Chase Utley is a 261 00:13:06,920 --> 00:13:10,640 Speaker 1: great example of that. Cody Bellinger to that longer arms, 262 00:13:10,679 --> 00:13:12,760 Speaker 1: but he can kind of step in the bucket more 263 00:13:13,080 --> 00:13:16,120 Speaker 1: and just looking at what they're sitting on, and if 264 00:13:16,320 --> 00:13:18,360 Speaker 1: they get into patterns of what they're sitting on, and 265 00:13:18,320 --> 00:13:20,360 Speaker 1: the younger the hitter is, the ease of the pattern 266 00:13:20,440 --> 00:13:22,400 Speaker 1: is to figure out usually they're sitting on a first 267 00:13:22,400 --> 00:13:26,000 Speaker 1: pitch fastball or you know, something of that nature. You 268 00:13:26,000 --> 00:13:27,560 Speaker 1: can kind of start off with like a bad breaking 269 00:13:27,600 --> 00:13:29,040 Speaker 1: ball down the middle that you can kind of take 270 00:13:29,080 --> 00:13:31,200 Speaker 1: first strike, and then later in the counts, you know 271 00:13:31,200 --> 00:13:32,880 Speaker 1: that they're looking to put a ball in play and 272 00:13:32,920 --> 00:13:34,000 Speaker 1: that's where you can kind of get him with a 273 00:13:34,040 --> 00:13:38,640 Speaker 1: fastball high. But as hitters advanced, their approach advances, and 274 00:13:38,679 --> 00:13:41,880 Speaker 1: that's where you know, the modeling takes place of Okay, 275 00:13:42,000 --> 00:13:44,720 Speaker 1: in my eye, test is no longer good enough here 276 00:13:44,760 --> 00:13:46,240 Speaker 1: to be able to determine what they're sitting on, what 277 00:13:46,280 --> 00:13:49,640 Speaker 1: they're looking for. But these models are. And that's really 278 00:13:49,679 --> 00:13:52,240 Speaker 1: what I believe got me to the major leagues and 279 00:13:52,280 --> 00:13:54,680 Speaker 1: get and had the statistics. You know that I was 280 00:13:54,760 --> 00:13:57,200 Speaker 1: able to put up. It certainly wasn't because of my stuff, 281 00:13:57,200 --> 00:13:59,520 Speaker 1: that's for sure. I had to figure out another way 282 00:13:59,520 --> 00:14:02,120 Speaker 1: to beauce. And so this was This is an Excel 283 00:14:02,160 --> 00:14:04,600 Speaker 1: spreadsheet that has when you're in the major leagues. I mean, 284 00:14:04,640 --> 00:14:07,360 Speaker 1: is there a tab for Albert pool holes that says 285 00:14:07,440 --> 00:14:11,920 Speaker 1: where his foot is? Where? How long are every single players? Arm? 286 00:14:12,000 --> 00:14:14,640 Speaker 1: Link is not a I didn't measure that. You can 287 00:14:14,720 --> 00:14:16,400 Speaker 1: kind of just tell we're just trying to look at 288 00:14:16,400 --> 00:14:21,240 Speaker 1: plate coverage and and basically body momentum. Use body momentum 289 00:14:21,240 --> 00:14:23,560 Speaker 1: to see what's pitch they're looking for. So heading into 290 00:14:23,600 --> 00:14:26,040 Speaker 1: each game, you know, you're looking at all the potential 291 00:14:26,120 --> 00:14:28,520 Speaker 1: hitters that you can face, and you're essentially trying to 292 00:14:28,560 --> 00:14:30,720 Speaker 1: memorize so that when you're on the mound you have 293 00:14:30,800 --> 00:14:32,680 Speaker 1: it in your head already. You make it sound a 294 00:14:32,720 --> 00:14:37,640 Speaker 1: lot more complicated than it really was. It was, and 295 00:14:37,680 --> 00:14:39,600 Speaker 1: it wasn't the hitting, but I guess over time, after 296 00:14:39,720 --> 00:14:41,720 Speaker 1: years and years of doing it, it got pretty just 297 00:14:41,760 --> 00:14:44,600 Speaker 1: spend you know, five to eight hours before every year, 298 00:14:44,680 --> 00:14:46,320 Speaker 1: he's going over all the hitters. I mean, there's only 299 00:14:46,360 --> 00:14:49,400 Speaker 1: twelve possible hitters you could face. Being able to do 300 00:14:49,440 --> 00:14:51,920 Speaker 1: that on on each of the hitters wasn't too difficult 301 00:14:52,000 --> 00:14:54,120 Speaker 1: as time went on. Originally, of course it took you know, 302 00:14:54,240 --> 00:14:56,800 Speaker 1: twenty plus hours, but then as you got to it, 303 00:14:56,840 --> 00:14:58,760 Speaker 1: he's the same hitters over and over and over again. 304 00:14:58,800 --> 00:15:01,520 Speaker 1: It got to be got to be pretty shocking. The 305 00:15:01,640 --> 00:15:04,040 Speaker 1: hitters rarely changed. I mean, I'd have a report on 306 00:15:04,080 --> 00:15:05,160 Speaker 1: the hit it and faced me a a year and a 307 00:15:05,160 --> 00:15:06,920 Speaker 1: half later that you got traded and traded back and 308 00:15:07,200 --> 00:15:09,280 Speaker 1: must always be the same thing. Um, even though I 309 00:15:09,400 --> 00:15:11,320 Speaker 1: looked at it as a brand new person, and the 310 00:15:11,360 --> 00:15:14,680 Speaker 1: results would almost come out identical. And so for listeners 311 00:15:14,720 --> 00:15:16,600 Speaker 1: who understand when we're talking about you were in the 312 00:15:16,640 --> 00:15:19,400 Speaker 1: Phillies in two thousand eleven and two thousand twelve, were 313 00:15:19,400 --> 00:15:21,800 Speaker 1: there any other Did you have other teammates who were 314 00:15:21,840 --> 00:15:24,000 Speaker 1: doing anything kind of similar to what you were doing, 315 00:15:24,000 --> 00:15:27,800 Speaker 1: either hitters or pictures, not that I love pictures. Spent 316 00:15:27,880 --> 00:15:29,920 Speaker 1: a lot of time working on it. Some of them, 317 00:15:29,920 --> 00:15:31,960 Speaker 1: like Royal Alliday, spent just as much time in the 318 00:15:32,040 --> 00:15:35,680 Speaker 1: diller room studying hitters and looking for things. But again 319 00:15:35,680 --> 00:15:38,520 Speaker 1: he was doing it very subjectively, but he was smart 320 00:15:38,600 --> 00:15:41,640 Speaker 1: enough to where his subjective Braden was was was as 321 00:15:41,680 --> 00:15:43,960 Speaker 1: close as it could be. And so Hitters A. Pictures 322 00:15:43,960 --> 00:15:46,720 Speaker 1: did spend a lot of time doing that, Catchers pitching coaches, 323 00:15:46,880 --> 00:15:49,200 Speaker 1: but other pictures didn't. You know, Cliffly and a lot 324 00:15:49,200 --> 00:15:50,680 Speaker 1: of success, and he's like, you know, I don't think 325 00:15:50,680 --> 00:15:52,240 Speaker 1: he should off once in his career. You just threw 326 00:15:52,240 --> 00:15:54,920 Speaker 1: whatever picture was called. And he's an executioner, and if 327 00:15:54,960 --> 00:15:57,880 Speaker 1: you can execute the pitch, that's another way to do it, 328 00:15:58,320 --> 00:16:00,480 Speaker 1: you know. To answer your question directly, I think I 329 00:16:00,560 --> 00:16:02,760 Speaker 1: was the only person actually building models at that time, 330 00:16:02,800 --> 00:16:04,600 Speaker 1: at least I didn't know of anybody else was it 331 00:16:04,640 --> 00:16:07,120 Speaker 1: frustrating to watch Cliffland. I mean, you're spending hours and 332 00:16:07,160 --> 00:16:09,480 Speaker 1: hours before every series going through all this watching film, 333 00:16:09,480 --> 00:16:11,560 Speaker 1: putting together your spreadsheet, and he goes out and just 334 00:16:11,720 --> 00:16:14,280 Speaker 1: kind of throws and executes. It wasn't because it's a 335 00:16:14,320 --> 00:16:16,360 Speaker 1: way that works. You know, there's a lot of ways 336 00:16:16,400 --> 00:16:19,400 Speaker 1: to be successful. I believe there's two main areas to 337 00:16:19,400 --> 00:16:21,800 Speaker 1: be really successful in sports, either to be in full 338 00:16:21,840 --> 00:16:25,240 Speaker 1: control or to fully give up control and trust. And 339 00:16:25,280 --> 00:16:27,120 Speaker 1: that's what cliff Ley was. You know, I've trusted the 340 00:16:27,160 --> 00:16:28,880 Speaker 1: catcher's done the work and it's gonna call the right 341 00:16:28,920 --> 00:16:31,240 Speaker 1: game and knows knows what's going on, so I'm gonna execute. 342 00:16:31,280 --> 00:16:33,480 Speaker 1: And he fully believed in that. There's no doubting or 343 00:16:33,520 --> 00:16:36,560 Speaker 1: second guessing. For me, that's just sign my brainworks. I 344 00:16:36,760 --> 00:16:39,920 Speaker 1: had to be in control of everything that that's going 345 00:16:39,960 --> 00:16:42,600 Speaker 1: on and the balls coming out of my hands. The 346 00:16:42,600 --> 00:16:45,160 Speaker 1: results is on me. I want to put as much 347 00:16:45,160 --> 00:16:48,160 Speaker 1: information as I can to get the best results. So 348 00:16:48,400 --> 00:16:50,200 Speaker 1: there's definitely more than one way to be successful. I 349 00:16:50,240 --> 00:16:52,200 Speaker 1: think the middle grounds where a lot of people fail. 350 00:16:52,480 --> 00:16:54,560 Speaker 1: They're not smart, not necessarily to build these models have 351 00:16:54,640 --> 00:16:57,520 Speaker 1: figured out, but they also have the intuitions like oh, 352 00:16:57,560 --> 00:16:59,120 Speaker 1: maybe I shouldn't throw that fish, and then you end 353 00:16:59,160 --> 00:17:01,560 Speaker 1: up second guests in yourself and after we can get 354 00:17:01,600 --> 00:17:04,040 Speaker 1: into some trouble. At least from what I've seen, we're 355 00:17:04,080 --> 00:17:06,639 Speaker 1: speaking with former Major League baseball pitcher Michael Swimmer, and 356 00:17:06,680 --> 00:17:09,200 Speaker 1: Michael as we talk about this algorithm that you built 357 00:17:09,440 --> 00:17:12,680 Speaker 1: two thousand thirteen, you hurt your shoulder, you start thinking 358 00:17:12,680 --> 00:17:15,320 Speaker 1: about what's what's going to happen after baseball, and and 359 00:17:15,480 --> 00:17:19,720 Speaker 1: this data approach kind of becomes the genesis for your 360 00:17:19,760 --> 00:17:23,480 Speaker 1: first business. Big League advances that right, That's correct. So um, 361 00:17:23,480 --> 00:17:25,880 Speaker 1: when I was with the Phillies, I joined the Players Union. 362 00:17:26,160 --> 00:17:29,120 Speaker 1: I was on the licensing committee and the executive subcommittee, 363 00:17:29,359 --> 00:17:31,920 Speaker 1: and I was really, you know, hurt by how minor 364 00:17:31,960 --> 00:17:35,639 Speaker 1: leaguers were treated, both financially and really just as people 365 00:17:35,640 --> 00:17:38,560 Speaker 1: in general. They get five thousand dollars a year and 366 00:17:38,600 --> 00:17:41,480 Speaker 1: the team doesn't pay for anything, and it's it's really tough, 367 00:17:41,560 --> 00:17:43,679 Speaker 1: and you you're spending that all seasons not trying to 368 00:17:43,720 --> 00:17:45,760 Speaker 1: live your American dream and be the best baseball player 369 00:17:45,840 --> 00:17:48,320 Speaker 1: you can. And I wanted to change that, and I 370 00:17:48,320 --> 00:17:50,879 Speaker 1: wanted to fix that, and I brought together like a 371 00:17:50,960 --> 00:17:54,160 Speaker 1: presentation for the union. But ultimately those of you don't 372 00:17:54,160 --> 00:17:57,280 Speaker 1: know the Major League Baseball Players Association covers major league 373 00:17:57,320 --> 00:17:59,760 Speaker 1: players only. They did not cover to seven thousand minor 374 00:17:59,800 --> 00:18:02,120 Speaker 1: leagu years. Seven thousand minor leaguers, you have a less 375 00:18:02,119 --> 00:18:04,320 Speaker 1: than ten percent chance to play one single day in 376 00:18:04,320 --> 00:18:06,920 Speaker 1: the major league and about three percent chance of less 377 00:18:06,920 --> 00:18:08,600 Speaker 1: to make a lot of money. And my idea is, 378 00:18:08,640 --> 00:18:10,320 Speaker 1: I've built all these models. I know what it takes 379 00:18:10,320 --> 00:18:12,320 Speaker 1: to be successful as a player. I've been in baseball 380 00:18:12,359 --> 00:18:16,240 Speaker 1: since since I can remember walking, and I thought that, look, 381 00:18:16,359 --> 00:18:18,560 Speaker 1: I can identify these players, and I'd like to build 382 00:18:18,560 --> 00:18:21,200 Speaker 1: a company to invest in these players, the rich their 383 00:18:21,240 --> 00:18:24,480 Speaker 1: career and enjoy in their success with them. So the 384 00:18:24,520 --> 00:18:26,879 Speaker 1: idea is, you create a company that you'd give the 385 00:18:27,000 --> 00:18:29,960 Speaker 1: minor league players money up front of an investment, not alone, 386 00:18:30,359 --> 00:18:32,000 Speaker 1: and if they didn't make it to the major league, 387 00:18:32,080 --> 00:18:34,280 Speaker 1: they keep all the money, and if not, then we 388 00:18:34,640 --> 00:18:36,840 Speaker 1: have a deal where we would get a percentage of 389 00:18:36,920 --> 00:18:39,359 Speaker 1: their earnings and the player can choose the percentage who 390 00:18:39,359 --> 00:18:41,080 Speaker 1: wants to give up. We based every offer of a 391 00:18:41,119 --> 00:18:44,119 Speaker 1: one percent offer and go from there. And so I 392 00:18:44,200 --> 00:18:47,080 Speaker 1: started that company with Paul Deepedest actually For those of 393 00:18:47,080 --> 00:18:49,639 Speaker 1: you who don't know, Paul Deepadesto is the main character 394 00:18:49,680 --> 00:18:52,359 Speaker 1: in the book the Michael Lewis book Moneyball, and the 395 00:18:52,440 --> 00:18:55,399 Speaker 1: Jonah Hill character in the in the movie Moneyball, And 396 00:18:55,720 --> 00:18:58,720 Speaker 1: together we were able to build upon the model that 397 00:18:58,800 --> 00:19:02,000 Speaker 1: I had created. I mean, when you went to Pauldi Podesta, 398 00:19:02,080 --> 00:19:04,080 Speaker 1: who you know, worked a number of Major League Baseball 399 00:19:04,080 --> 00:19:07,960 Speaker 1: front offices and is now with the NFL's Cleveland Browns, 400 00:19:08,440 --> 00:19:10,560 Speaker 1: you know, he he made it clear that he was 401 00:19:10,720 --> 00:19:12,800 Speaker 1: he had kind of been waiting right for for someone 402 00:19:12,840 --> 00:19:14,359 Speaker 1: to come along with this idea. It's something he had 403 00:19:14,359 --> 00:19:17,000 Speaker 1: thought about before. Yeah, that meeting was a was a 404 00:19:17,040 --> 00:19:19,520 Speaker 1: total champ meeting. It was so lucky. You know, every 405 00:19:19,560 --> 00:19:21,639 Speaker 1: kind of a successful story, I feel like there's a 406 00:19:21,680 --> 00:19:24,600 Speaker 1: big luck component here, and this was certainly my big 407 00:19:24,680 --> 00:19:28,560 Speaker 1: lust component. I met him at a healthcare conference because 408 00:19:28,600 --> 00:19:30,520 Speaker 1: one of my friends had an extra ticket and his 409 00:19:30,640 --> 00:19:33,080 Speaker 1: wife was hurt shoulder, and I yesked if I wanted 410 00:19:33,119 --> 00:19:35,720 Speaker 1: to go, and so I said sure. Because Pauldi Podesta 411 00:19:35,760 --> 00:19:38,200 Speaker 1: was a keynote speaker, I saw him and he came 412 00:19:38,240 --> 00:19:40,840 Speaker 1: up to me and immediately recognized me. Because at the time, 413 00:19:40,840 --> 00:19:42,640 Speaker 1: You're gonna remember when I was pitching for the Phillies. 414 00:19:42,680 --> 00:19:45,040 Speaker 1: He was a mess, and so you know, we played 415 00:19:45,040 --> 00:19:48,120 Speaker 1: each other a bunch and uh, you know, he asked 416 00:19:48,119 --> 00:19:49,960 Speaker 1: me what I was up to now. I told him 417 00:19:50,000 --> 00:19:52,720 Speaker 1: and he was in total shock. Was like I had 418 00:19:52,760 --> 00:19:55,000 Speaker 1: the same exact idea in two thousand and four. He 419 00:19:55,040 --> 00:19:57,080 Speaker 1: was going to do it. He actually had people that 420 00:19:57,080 --> 00:20:00,159 Speaker 1: were potentially gonna fund it, but then the Dodgers from 421 00:20:00,200 --> 00:20:02,000 Speaker 1: him a GM job, which in his first GM job, 422 00:20:02,040 --> 00:20:05,160 Speaker 1: and he couldn't say no to that. So he's involved. 423 00:20:05,160 --> 00:20:08,959 Speaker 1: He's a second largest shareholder besides myself, and uh, and 424 00:20:08,960 --> 00:20:11,040 Speaker 1: we we hit the ground running. So it was really 425 00:20:11,040 --> 00:20:12,720 Speaker 1: cool meetings. So give us a sense. I know you 426 00:20:12,760 --> 00:20:15,520 Speaker 1: said that all these each individual contract is different, but 427 00:20:15,520 --> 00:20:19,840 Speaker 1: but kind of generally, these are six figure loans to 428 00:20:19,960 --> 00:20:23,119 Speaker 1: minor league baseball players in exchange, we don't say the 429 00:20:23,240 --> 00:20:27,480 Speaker 1: lt got your investment, investment investment, because you don't don't 430 00:20:27,480 --> 00:20:29,800 Speaker 1: pay players, they don't make it. Yeah, we got players 431 00:20:29,800 --> 00:20:32,120 Speaker 1: to take deals and then immediately retire the next day 432 00:20:32,119 --> 00:20:34,960 Speaker 1: simply because they were depressed in baseball and you can't 433 00:20:35,000 --> 00:20:37,080 Speaker 1: mild depression. And that's their money, they keep it, you know, 434 00:20:37,280 --> 00:20:40,280 Speaker 1: That's what happened. And does that frustrate you know, not 435 00:20:40,359 --> 00:20:43,040 Speaker 1: at all. I've lived in I lived the life. I 436 00:20:43,160 --> 00:20:46,439 Speaker 1: understand how depressing it is. Um. You know, we have 437 00:20:46,560 --> 00:20:50,400 Speaker 1: a hundred and seventy nine players now and look one 438 00:20:50,440 --> 00:20:52,639 Speaker 1: of them does that, and and we have several players 439 00:20:52,640 --> 00:20:55,000 Speaker 1: are out of baseball right now, right said the model 440 00:20:55,080 --> 00:20:58,399 Speaker 1: was wrong on and they're out of baseball. And several 441 00:20:58,400 --> 00:21:00,720 Speaker 1: players are out the end then notes like they so much, 442 00:21:00,760 --> 00:21:03,160 Speaker 1: You've changed my life, you know, it's just it's why 443 00:21:03,200 --> 00:21:05,879 Speaker 1: I did this. This is a by players for players company. 444 00:21:06,240 --> 00:21:09,240 Speaker 1: The deal is the deal, and and that's fit. How 445 00:21:09,240 --> 00:21:12,200 Speaker 1: many players have you have? You guys invested in one 446 00:21:12,480 --> 00:21:15,680 Speaker 1: seventy nine, seventy nine and and give us a sense 447 00:21:15,720 --> 00:21:18,240 Speaker 1: of those a hundred seventy nine you know, certainly it's 448 00:21:18,240 --> 00:21:20,359 Speaker 1: a young company, so they're working there with through the system. 449 00:21:20,359 --> 00:21:22,199 Speaker 1: How many are in the major leagues right now? Well, 450 00:21:22,240 --> 00:21:24,479 Speaker 1: I can tell you our first fund because that started 451 00:21:24,480 --> 00:21:28,080 Speaker 1: in two thousand, um uh and the two thousand fifteen 452 00:21:29,000 --> 00:21:32,440 Speaker 1: and ended about eighteen months later about two thousand eighteen. 453 00:21:33,080 --> 00:21:35,480 Speaker 1: And we have seventy seven players in our first fund. 454 00:21:35,800 --> 00:21:37,760 Speaker 1: You got to understand, we don't get the top prospects 455 00:21:37,800 --> 00:21:40,640 Speaker 1: either right the first round pick, and so all those 456 00:21:40,640 --> 00:21:43,240 Speaker 1: seven thousand and number that under ten percent, that includes 457 00:21:43,240 --> 00:21:45,160 Speaker 1: first round picks. So the guys that we're going after 458 00:21:45,440 --> 00:21:47,480 Speaker 1: are really probably under five percent chance to make the 459 00:21:47,480 --> 00:21:50,440 Speaker 1: major leagues. And we have thirty eight at seventy seven currently, 460 00:21:50,800 --> 00:21:54,120 Speaker 1: um we've played in Major League Baseball, and we're expecting 461 00:21:54,119 --> 00:21:56,720 Speaker 1: a number of to be north of fifty by the 462 00:21:56,760 --> 00:22:00,399 Speaker 1: time all said and done. Over seventy percent of players 463 00:22:00,400 --> 00:22:03,000 Speaker 1: that we signed in those seven we're outside the top 464 00:22:03,200 --> 00:22:06,879 Speaker 1: three hundred prospects in baseball when we sign them. But 465 00:22:06,920 --> 00:22:09,160 Speaker 1: it's the model. The model is able to day analytics. 466 00:22:09,200 --> 00:22:11,399 Speaker 1: The stuff that we're doing is groundbreaking and it's been 467 00:22:11,440 --> 00:22:14,680 Speaker 1: able to reap the rewards. So you give us some names. 468 00:22:14,680 --> 00:22:17,640 Speaker 1: I know Fernando Tatiss Jr. Is one of them, who's 469 00:22:17,800 --> 00:22:19,760 Speaker 1: a Rookie of the Year candidate this year by the way, 470 00:22:19,800 --> 00:22:23,439 Speaker 1: so so good calling that one. Well, he's unfortunately heard himself. 471 00:22:23,480 --> 00:22:26,320 Speaker 1: So that's that was the very depressing news. All our 472 00:22:26,480 --> 00:22:29,280 Speaker 1: our players are you know, our deals are confidential. The 473 00:22:29,320 --> 00:22:31,720 Speaker 1: only way I can, um you know, tell you is 474 00:22:31,760 --> 00:22:35,160 Speaker 1: if they you know, let us and so I can 475 00:22:35,160 --> 00:22:39,240 Speaker 1: tell you the players that Jared Rucks are, um who 476 00:22:39,359 --> 00:22:41,040 Speaker 1: is out of baseball. I mean, I can give you 477 00:22:41,040 --> 00:22:42,359 Speaker 1: like a list of five or six guys that are 478 00:22:42,359 --> 00:22:45,399 Speaker 1: out of baseball already because they have no problems to 479 00:22:45,480 --> 00:22:49,040 Speaker 1: sharing that the ideas. These players don't want teens to 480 00:22:49,119 --> 00:22:52,960 Speaker 1: know that they're doing this necessarily it's their businesses, their money, 481 00:22:53,000 --> 00:22:55,720 Speaker 1: and they don't want teams, you know, aware of their 482 00:22:55,760 --> 00:22:58,520 Speaker 1: financial standing. But for Nando Tatis, you've got to give 483 00:22:58,520 --> 00:23:00,359 Speaker 1: the guy all the credit in the world. Were running 484 00:23:00,359 --> 00:23:02,359 Speaker 1: to a little tough patch, you know, early on, people 485 00:23:02,400 --> 00:23:04,480 Speaker 1: not really understanding what we were doing. He wanted to 486 00:23:04,600 --> 00:23:07,399 Speaker 1: go on the record and say how how helpless was 487 00:23:07,520 --> 00:23:10,520 Speaker 1: to minor leaguers and you know him and how they're 488 00:23:10,520 --> 00:23:12,480 Speaker 1: taking We're taking the risk. It's just a great option 489 00:23:12,560 --> 00:23:17,080 Speaker 1: for players to have. So he's there, Um Joseo students 490 00:23:17,160 --> 00:23:18,720 Speaker 1: with the major league in the Major League and the 491 00:23:18,720 --> 00:23:22,000 Speaker 1: Pirates having a great season. Francisco Mahia, who is a 492 00:23:22,080 --> 00:23:24,960 Speaker 1: young catcher on the on the Padres, is also one 493 00:23:25,000 --> 00:23:27,120 Speaker 1: of our players. But those are the only three, really 494 00:23:27,160 --> 00:23:28,879 Speaker 1: that I can think of that are the major leagues 495 00:23:29,480 --> 00:23:32,240 Speaker 1: that wanted to go on the record. And you brought 496 00:23:32,320 --> 00:23:34,320 Speaker 1: up Francisco Miha, who was one of the better, one 497 00:23:34,359 --> 00:23:37,480 Speaker 1: of the top prospects in baseball, and he sued Big 498 00:23:37,600 --> 00:23:40,399 Speaker 1: League Advanced a couple of years ago, a lawsuit that 499 00:23:40,480 --> 00:23:43,560 Speaker 1: was eventually dropped, but but did bring some some attention 500 00:23:43,640 --> 00:23:46,840 Speaker 1: to what you're doing and essentially, I mean call into 501 00:23:46,920 --> 00:23:49,200 Speaker 1: question whether what you guys are doing or it was 502 00:23:49,280 --> 00:23:52,320 Speaker 1: exploitative kind of How did you respond to to that lawsuit? 503 00:23:53,280 --> 00:23:55,359 Speaker 1: This was one probably one of the biggest mistakes I've 504 00:23:55,359 --> 00:23:58,560 Speaker 1: made at CEO. Was not explained to people what we 505 00:23:58,640 --> 00:24:00,800 Speaker 1: were doing. I wanted to keep up very low profile, 506 00:24:01,119 --> 00:24:02,840 Speaker 1: and so we were operating for a couple of years 507 00:24:03,119 --> 00:24:05,639 Speaker 1: before anybody heard or knew what we were doing. And 508 00:24:05,720 --> 00:24:07,800 Speaker 1: the first time anybody heard of it was this lawsuit 509 00:24:07,840 --> 00:24:11,879 Speaker 1: from Francisco Media. So people instantly jumped to conclusions, you know, 510 00:24:11,960 --> 00:24:14,200 Speaker 1: what are these companies doing? Dada da dad. You know 511 00:24:14,280 --> 00:24:16,760 Speaker 1: it's really you know, bad, like Loan Show. They didn't 512 00:24:16,840 --> 00:24:18,600 Speaker 1: understand it. Of players, they never have to pay us back. 513 00:24:18,960 --> 00:24:21,960 Speaker 1: Players have lawyers reviewing their contract that you know, we 514 00:24:22,080 --> 00:24:24,560 Speaker 1: have video tapes of every single player before we sign him, 515 00:24:24,960 --> 00:24:27,320 Speaker 1: explaining the deal. If you understand if you're gonna make 516 00:24:27,359 --> 00:24:30,560 Speaker 1: five million dollars you're only gonna you're you're gonna only 517 00:24:30,680 --> 00:24:32,920 Speaker 1: make four hundred and fifty million if you do a 518 00:24:32,960 --> 00:24:35,960 Speaker 1: deal us for ten. Right, all of that is explained. 519 00:24:36,040 --> 00:24:37,920 Speaker 1: Then I would never be able to sign a single 520 00:24:38,000 --> 00:24:40,440 Speaker 1: player with a conscience if I did not know for 521 00:24:40,520 --> 00:24:44,320 Speaker 1: sure that the players completely understood what he was doing. Unfortunately, Francisco, 522 00:24:44,320 --> 00:24:46,320 Speaker 1: I believe it's got really bad advice because he knews 523 00:24:46,359 --> 00:24:49,120 Speaker 1: from the lawsuit, he did file a lawsuit. He then, 524 00:24:49,440 --> 00:24:51,720 Speaker 1: um not only did he drop the lawsuit, but wrote 525 00:24:51,760 --> 00:24:55,640 Speaker 1: a very long public apology to us. In the apology 526 00:24:55,720 --> 00:24:58,320 Speaker 1: explaining that what he thinks that we're doing is great 527 00:24:58,359 --> 00:25:02,800 Speaker 1: for minor leaguers, and um, he did pay uh portions 528 00:25:02,840 --> 00:25:05,280 Speaker 1: of our legal fees as well. So UM, there was 529 00:25:05,320 --> 00:25:07,439 Speaker 1: no settlement, there's no anything like that. It was simply 530 00:25:07,680 --> 00:25:09,760 Speaker 1: you know, he he understood and he made a mistake 531 00:25:09,800 --> 00:25:13,800 Speaker 1: in doing that and apologized for us. And uh it 532 00:25:13,920 --> 00:25:16,439 Speaker 1: also got in the light. There's articles writ in Sports 533 00:25:16,440 --> 00:25:20,000 Speaker 1: Illustrated and The Athletic and other areas. And then once 534 00:25:20,040 --> 00:25:23,040 Speaker 1: people understood, once people got the story understood, like man, 535 00:25:23,119 --> 00:25:26,200 Speaker 1: this company's off. But initially because that was the first 536 00:25:26,240 --> 00:25:27,680 Speaker 1: thing they heard, it was a really tough time. And 537 00:25:27,760 --> 00:25:30,359 Speaker 1: that's why I gotta give for a name of Fatis Jr. 538 00:25:30,359 --> 00:25:32,359 Speaker 1: All a credit. Once he saw that the negative press 539 00:25:32,440 --> 00:25:34,440 Speaker 1: come out, he wanted to set the record straight. And 540 00:25:34,560 --> 00:25:36,720 Speaker 1: I gotta come in the man for doing that. It's 541 00:25:36,760 --> 00:25:39,479 Speaker 1: kind of a sensitive area, right because baseball fans are 542 00:25:39,520 --> 00:25:44,040 Speaker 1: certainly familiar with the idea that oftentimes young, poor, uneducated, 543 00:25:44,160 --> 00:25:47,800 Speaker 1: talented players do get taken advantage of by managers or 544 00:25:47,840 --> 00:25:51,000 Speaker 1: by agents who aren't looking out for them holistically. Yeah, 545 00:25:51,119 --> 00:25:53,840 Speaker 1: unfortunately that is the case, Um. And that's also why 546 00:25:53,920 --> 00:25:57,200 Speaker 1: we're we passed the building Delaware. At least it's on 547 00:25:57,320 --> 00:25:59,200 Speaker 1: the governor's death rate to sign it right now. That 548 00:25:59,320 --> 00:26:01,840 Speaker 1: made sure of these agreements that these players had to 549 00:26:01,920 --> 00:26:04,359 Speaker 1: have lawyers with them, that all the material terms had 550 00:26:04,400 --> 00:26:08,399 Speaker 1: to be described to them in Um, their native language, 551 00:26:08,520 --> 00:26:10,680 Speaker 1: and the contract have to be written in their native language. 552 00:26:10,840 --> 00:26:13,240 Speaker 1: And again as we recording, to make sure they understand. 553 00:26:13,280 --> 00:26:15,640 Speaker 1: You know, other companies that have the space don't necessarily 554 00:26:15,720 --> 00:26:18,119 Speaker 1: do that, and they are being taken advantage of and 555 00:26:18,400 --> 00:26:21,560 Speaker 1: and that's unacceptable to me. And so I'm really happy 556 00:26:21,720 --> 00:26:24,800 Speaker 1: that the Delaware legislature took it upon themselves to be 557 00:26:24,880 --> 00:26:27,600 Speaker 1: the first to pass a bill in this in that effect, 558 00:26:27,640 --> 00:26:30,920 Speaker 1: so again we can make sure players understand what they're 559 00:26:30,920 --> 00:26:33,119 Speaker 1: doing in terms of signing these types of contracts. So 560 00:26:33,240 --> 00:26:36,080 Speaker 1: let's move forward bigly advances your first company and kind 561 00:26:36,119 --> 00:26:38,760 Speaker 1: of out of some of the money that you raised 562 00:26:38,840 --> 00:26:41,879 Speaker 1: for that and the management fees, you put together an 563 00:26:42,160 --> 00:26:45,560 Speaker 1: analytics team to kind of go across sports and think, okay, 564 00:26:45,760 --> 00:26:48,880 Speaker 1: where can we maybe do something else from a business perspective. 565 00:26:49,240 --> 00:26:52,160 Speaker 1: And what you guys ended up on is sports betting 566 00:26:52,440 --> 00:26:55,919 Speaker 1: and more specifically a tout service which you know, finds 567 00:26:56,240 --> 00:26:59,880 Speaker 1: sports betting picks that they think are particularly good um 568 00:27:00,200 --> 00:27:03,359 Speaker 1: and sells those picks to gamblers. How did you kind 569 00:27:03,400 --> 00:27:05,640 Speaker 1: of end up with that? As kind of the next 570 00:27:05,720 --> 00:27:08,960 Speaker 1: iteration of you know, this algorithm predictive modeling that you're 571 00:27:08,960 --> 00:27:12,560 Speaker 1: doing well with this success of the funds, we're able 572 00:27:12,600 --> 00:27:15,520 Speaker 1: to generate a pretty good pile of cash there, and 573 00:27:15,760 --> 00:27:18,960 Speaker 1: and wanted to bring together this great advance the analytic team. 574 00:27:19,480 --> 00:27:22,560 Speaker 1: So I talked to paulity Pidestes, Sam Hanky also and 575 00:27:22,680 --> 00:27:24,440 Speaker 1: he's like, you know who who we have out there 576 00:27:24,640 --> 00:27:27,720 Speaker 1: who's good? Like assembled this what I call dream team 577 00:27:28,240 --> 00:27:32,159 Speaker 1: of analysts around all sports, and you know NBA League Office, 578 00:27:32,440 --> 00:27:35,760 Speaker 1: and we're really able to focus on predicting games. We 579 00:27:35,840 --> 00:27:38,240 Speaker 1: can predict the outcomes of games we could we thought 580 00:27:38,320 --> 00:27:41,639 Speaker 1: possibly work for teams. Right now, Team A, you have 581 00:27:41,680 --> 00:27:43,720 Speaker 1: a forty percent chance to win against Team B. But 582 00:27:43,760 --> 00:27:45,719 Speaker 1: if you do these eight different things and run more 583 00:27:45,800 --> 00:27:48,919 Speaker 1: picking rolls or throw these pitches or run these plays 584 00:27:49,000 --> 00:27:51,200 Speaker 1: as a football team, you actually go from a forty 585 00:27:51,240 --> 00:27:54,280 Speaker 1: percent chance to win and like bees, like consultants was 586 00:27:54,359 --> 00:27:56,760 Speaker 1: the idea. But we had the first prove that we 587 00:27:56,880 --> 00:27:59,240 Speaker 1: can actually predict outcomes of game bear than anybody else 588 00:27:59,240 --> 00:28:01,640 Speaker 1: in the best way to prove that is to beat 589 00:28:01,680 --> 00:28:03,800 Speaker 1: the Vegas line and the market line, because that is 590 00:28:03,880 --> 00:28:07,000 Speaker 1: what people think is the most efficient line. So we 591 00:28:07,160 --> 00:28:11,280 Speaker 1: did that. We started in college basketball and unbelievable success. 592 00:28:11,359 --> 00:28:13,720 Speaker 1: We picked it about almost fifty nine person against the 593 00:28:13,760 --> 00:28:16,760 Speaker 1: spread of the one ten tests. And people don't realize this. 594 00:28:16,800 --> 00:28:19,560 Speaker 1: Teams are extremely cheap when it comes to these types 595 00:28:19,600 --> 00:28:22,600 Speaker 1: of things. And then you know, we started thinking about, okay, 596 00:28:22,640 --> 00:28:24,840 Speaker 1: can we actually use this money to bet in Vegas? 597 00:28:24,920 --> 00:28:28,280 Speaker 1: So UM and I thought, let's just raises gigantic fun 598 00:28:28,400 --> 00:28:30,879 Speaker 1: to just start betting on sports, and became doing it yourself, 599 00:28:30,960 --> 00:28:34,440 Speaker 1: going to be great. Yeah, yeah, doing ourselves. Unfortunately, what 600 00:28:34,520 --> 00:28:36,959 Speaker 1: I find is that the reason the market isn't very 601 00:28:37,000 --> 00:28:39,280 Speaker 1: efficient is because money is not allowed to come into it, 602 00:28:39,520 --> 00:28:42,320 Speaker 1: and we're getting shut down every everywhere. After sixteen days 603 00:28:42,360 --> 00:28:44,200 Speaker 1: in Las Vegas, I was shut out of every casino, 604 00:28:44,680 --> 00:28:46,880 Speaker 1: every sports book down to the posted limits, which is 605 00:28:46,920 --> 00:28:51,960 Speaker 1: three And so that's when I realized, like, that wasn't 606 00:28:51,960 --> 00:28:53,840 Speaker 1: gonna work. How do pro gamblers do it? The guys 607 00:28:53,840 --> 00:28:56,520 Speaker 1: who are making a living, you know, making millions of 608 00:28:56,560 --> 00:28:59,040 Speaker 1: dollars a year doing this, how how do they kind 609 00:28:59,080 --> 00:29:01,960 Speaker 1: of find the liquidity in the gambling market? Very easily, 610 00:29:01,960 --> 00:29:03,800 Speaker 1: you can bet three hundred dollars a place and you 611 00:29:03,920 --> 00:29:06,560 Speaker 1: multiply that by hundred or fifty different places. They got 612 00:29:06,600 --> 00:29:08,840 Speaker 1: a guy in post Breaka that has forty five different 613 00:29:08,880 --> 00:29:12,479 Speaker 1: accounts world net net internationally, and it's a good way 614 00:29:12,520 --> 00:29:13,880 Speaker 1: to make a living. You can make a couple of 615 00:29:13,880 --> 00:29:17,200 Speaker 1: million bucks doing that. But it's not scalable that Chambos. 616 00:29:17,200 --> 00:29:19,520 Speaker 1: We're paying five million dollars a year for data and 617 00:29:19,640 --> 00:29:21,560 Speaker 1: for people, so we can't you know, if we're making 618 00:29:21,600 --> 00:29:23,800 Speaker 1: two to three million dollars a year, we're losing money, right, 619 00:29:24,120 --> 00:29:28,400 Speaker 1: And so that's where I had thought about selling the picks. 620 00:29:28,480 --> 00:29:30,440 Speaker 1: You know, you can stop me. I can't bet three 621 00:29:30,520 --> 00:29:34,360 Speaker 1: hundred thousand dollars games, but a thousand people can bet. 622 00:29:34,560 --> 00:29:36,960 Speaker 1: So that's when we got into the subscription service space. 623 00:29:37,760 --> 00:29:39,880 Speaker 1: It's you know, it's hard for me to imagine a 624 00:29:39,960 --> 00:29:45,240 Speaker 1: worst industry, maybe tobacco industry, but I was gonna say, 625 00:29:45,440 --> 00:29:49,480 Speaker 1: you kind of like the industry with literally possibly the 626 00:29:49,520 --> 00:29:52,239 Speaker 1: word the town industry for gambling is. It probably has 627 00:29:52,280 --> 00:29:54,920 Speaker 1: the worst reputation of any industry I can think of 628 00:29:54,960 --> 00:29:58,400 Speaker 1: all and as it should. And I wanted to I 629 00:29:58,520 --> 00:30:00,640 Speaker 1: wanted to disrupt this industry. I wanted to turn it 630 00:30:00,720 --> 00:30:03,960 Speaker 1: on its head, and I wanted to know anybody because 631 00:30:03,960 --> 00:30:06,560 Speaker 1: I wanted to be the first ever, fully transparent and 632 00:30:06,720 --> 00:30:11,280 Speaker 1: financially accountable description service. Right, why do people hate touts? 633 00:30:11,360 --> 00:30:15,719 Speaker 1: Because it's you're giving the subscriber has negative expected value 634 00:30:15,880 --> 00:30:18,080 Speaker 1: if you lose. For us, we want to lose. I said, look, 635 00:30:18,120 --> 00:30:20,200 Speaker 1: if we're giving out picks to lose, I want to 636 00:30:20,240 --> 00:30:23,200 Speaker 1: lose the company. And so we created this system with 637 00:30:23,280 --> 00:30:26,120 Speaker 1: this financial guarantee that has never existed in this space, 638 00:30:26,680 --> 00:30:29,480 Speaker 1: where every single package you buy, if our picks lose 639 00:30:29,560 --> 00:30:31,800 Speaker 1: over that time, frame, you're gonna get your money back, 640 00:30:31,920 --> 00:30:34,240 Speaker 1: plus we're gonna give you additional money on top. And 641 00:30:34,320 --> 00:30:36,360 Speaker 1: it's a lot of money on top. Our seven team 642 00:30:36,400 --> 00:30:39,800 Speaker 1: week plan that spans the entire NFL football teams three 643 00:30:39,880 --> 00:30:42,240 Speaker 1: dollars a pick, which is particularly the cheapest in the industry, 644 00:30:42,520 --> 00:30:44,320 Speaker 1: but it is over a thousand picks, which is which 645 00:30:44,400 --> 00:30:46,480 Speaker 1: is probably the highest in the industry. So it costs 646 00:30:46,520 --> 00:30:49,400 Speaker 1: three thousand dollars. If we can't beat the market, If 647 00:30:49,400 --> 00:30:51,400 Speaker 1: you get the same amount in every single game and 648 00:30:51,480 --> 00:30:53,920 Speaker 1: we're down units, that means you've lost money. We're gonna 649 00:30:53,920 --> 00:30:57,360 Speaker 1: give you ten thousand dollars pack. If you look forward 650 00:30:57,400 --> 00:30:59,400 Speaker 1: to kind of what worries if if you guys are 651 00:31:00,000 --> 00:31:02,920 Speaker 1: if you can consistently pick a that is a slam 652 00:31:03,040 --> 00:31:05,240 Speaker 1: dunk home run, you know that that that is a 653 00:31:05,320 --> 00:31:08,720 Speaker 1: tremendous number and one that will make money for your clients. 654 00:31:09,200 --> 00:31:12,400 Speaker 1: What concerns you? Is it that you know maybe is 655 00:31:13,160 --> 00:31:14,520 Speaker 1: not what you're going to settle out at. Is it 656 00:31:14,600 --> 00:31:18,120 Speaker 1: that the reputation of the industry harms you in some ways? 657 00:31:18,280 --> 00:31:20,640 Speaker 1: What are the concerns that you look forward as you 658 00:31:20,680 --> 00:31:22,840 Speaker 1: guys try to drop a model I I believe the 659 00:31:22,880 --> 00:31:24,960 Speaker 1: model I've seen what it can do, and what I'm saying, 660 00:31:24,960 --> 00:31:27,959 Speaker 1: I think it's me to beat the market day. All 661 00:31:28,000 --> 00:31:29,480 Speaker 1: you have to do is beat better than fifty two, 662 00:31:30,920 --> 00:31:32,880 Speaker 1: you know, and I am I'm not worried about that 663 00:31:33,040 --> 00:31:34,640 Speaker 1: at all. And give me a sense. I mean, you 664 00:31:34,760 --> 00:31:37,280 Speaker 1: mentioned that this is a more scalable model, in your 665 00:31:37,320 --> 00:31:40,080 Speaker 1: eyes than than just you know, sending setting up offices 666 00:31:40,120 --> 00:31:43,800 Speaker 1: in different jurisdictions and betting them yourself. I see a 667 00:31:43,880 --> 00:31:47,040 Speaker 1: situation in which you get so big that as soon 668 00:31:47,120 --> 00:31:49,200 Speaker 1: as you put out a pick, you know, people are 669 00:31:49,240 --> 00:31:51,400 Speaker 1: betting it, and the lines move, and suddenly it becomes 670 00:31:51,440 --> 00:31:54,960 Speaker 1: difficult for everybody who subscribes to you to get you know, 671 00:31:55,080 --> 00:31:56,880 Speaker 1: the odds at at the at the price that you 672 00:31:57,000 --> 00:31:59,760 Speaker 1: offered them. How do you kind of think about a 673 00:31:59,800 --> 00:32:02,360 Speaker 1: few future in which, if you're really successful, it actually 674 00:32:02,400 --> 00:32:06,720 Speaker 1: becomes harder for your clients to bet on the lines 675 00:32:06,800 --> 00:32:10,160 Speaker 1: that you're offering. It's a great point, and and that 676 00:32:10,320 --> 00:32:13,520 Speaker 1: will drastically hurt our subscription service. I don't know how 677 00:32:13,560 --> 00:32:15,560 Speaker 1: long it's gonna take for the markets to adjust, but 678 00:32:16,040 --> 00:32:17,960 Speaker 1: I don't want how long it's gonna last. This is 679 00:32:18,080 --> 00:32:21,280 Speaker 1: essentially a business where if you do really really well, 680 00:32:21,880 --> 00:32:24,600 Speaker 1: you're kind of out of business fairly quickly. I don't 681 00:32:24,600 --> 00:32:26,720 Speaker 1: know that's fairly quickly. I don't underestimate how long it 682 00:32:26,800 --> 00:32:30,480 Speaker 1: takes through markets to react, especially in the sports betting market. 683 00:32:30,760 --> 00:32:32,959 Speaker 1: We'd have to get a lot of subscribers. Have been 684 00:32:32,960 --> 00:32:35,560 Speaker 1: a lot of money for these uh for the markets 685 00:32:35,600 --> 00:32:37,520 Speaker 1: to move that you're saying it was. And last question 686 00:32:37,600 --> 00:32:39,280 Speaker 1: for you, I know your guys are also looking at 687 00:32:39,320 --> 00:32:43,640 Speaker 1: potentially other opportunities using using this algorithm without giving away 688 00:32:43,680 --> 00:32:45,720 Speaker 1: any trade secrets. What else are you looking at? What 689 00:32:45,800 --> 00:32:47,920 Speaker 1: else do you think there is a hole in the 690 00:32:48,000 --> 00:32:50,520 Speaker 1: market for a predictive model that does really well in 691 00:32:50,600 --> 00:32:54,760 Speaker 1: sport extra sport y. Yeah, there's three main areas we're 692 00:32:54,800 --> 00:32:57,360 Speaker 1: looking at. We've been offered deals, if you will, in 693 00:32:57,440 --> 00:33:00,239 Speaker 1: all three and that's a running a sports book. Um, 694 00:33:00,400 --> 00:33:03,720 Speaker 1: these team ownerships, teams coming to us wanting to offer 695 00:33:04,080 --> 00:33:06,400 Speaker 1: give us actually a piece of ownership of these teams 696 00:33:06,440 --> 00:33:08,720 Speaker 1: in order to come in and use our modeling to 697 00:33:08,800 --> 00:33:11,560 Speaker 1: help teams win. Um. We saw Mark Cuban actually do 698 00:33:11,760 --> 00:33:15,160 Speaker 1: that earlier this year, maybe it's last year. And then lastly, 699 00:33:15,240 --> 00:33:17,640 Speaker 1: the content space, we're at the top of the first 700 00:33:17,680 --> 00:33:20,640 Speaker 1: inning in terms of sports betting content, and I think 701 00:33:20,680 --> 00:33:23,040 Speaker 1: that there are a lot of different and unique ways 702 00:33:23,520 --> 00:33:26,120 Speaker 1: to bring content to viewers that actually want to know 703 00:33:26,720 --> 00:33:28,480 Speaker 1: why our teams winning and lose the games and the 704 00:33:28,600 --> 00:33:31,440 Speaker 1: actual analysis. I mean, look, we're getting into a twenty 705 00:33:31,520 --> 00:33:35,480 Speaker 1: four seven gambling entertainment network. This will happen within the 706 00:33:35,560 --> 00:33:38,720 Speaker 1: next two years. Michael Schwimmer, former Major League Baseball pitcher, 707 00:33:39,400 --> 00:33:42,320 Speaker 1: founder of Big League Advance and Jambo's Picks. Thank you 708 00:33:42,360 --> 00:33:46,440 Speaker 1: for joining us. You're listening to Bloomberg Business of Sports. 709 00:33:46,480 --> 00:33:48,320 Speaker 1: We're here each and every week at the same time, 710 00:33:48,400 --> 00:33:51,240 Speaker 1: plus online wherever you get your podcasts. You can catch 711 00:33:51,320 --> 00:33:54,760 Speaker 1: that Monday's, Wednesdays and Thursdays. I'm Evan Ovie, Williams, Scott 712 00:33:54,800 --> 00:33:56,840 Speaker 1: and Michael will be back next week. And this is 713 00:33:56,920 --> 00:33:59,880 Speaker 1: Bloomberg Business of Sports on Bloomberg Radio around the