Latest / Nonsense with cj little and Jeff Parker / The Death of the Bookie: Why Prediction Markets are Eating Sports Betting

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The Death of the Bookie: Why Prediction Markets are Eating Sports Betting · Nonsense with cj little and Jeff Parker

• 0:00
  Welcome to nonsense season 4, episode 27, our big story but
• 0:03
  not our second show of the week because CJ was busy feeding his
• 0:05
  children's schools, teachers and.
• 0:07
  Staff a lot of possessives in there.
• 0:08
  How nice of you. I'm Jeff.
• 0:09
  Perk I'm CJ little the feeder. I'm the feeder of the people
• 0:12
  they would eat without me. They just get to eat something I
• 0:15
  think more delicious with me. Probably something pretty
• 0:16
  amazing, right? It was pretty good Teacher
• 0:18
  appreciation week at. Your school has to just be that
• 0:20
  like they've won the lottery. 32 lbs of three different beefs
• 0:23
  that I smoked and then braised for like a total of 12 hours.
• 0:27
  Yeah, it's pretty good. Let's talk about that instead of
• 0:28
  this gambling thing that's pretty good.
• 0:30
  This time we're looking at crystal balls and margin calls.
• 0:33
  How the Internet gambles on the future.
• 0:35
  Up next. So I smoke it over oak and then
• 0:37
  you do braise it. Oh, my whole house smells like a
• 0:40
  beef emporium. It's kind of lovely.
• 0:42
  Tell it slower. Here's the thing.
• 0:43
  Yes, I'm very excited about this episode.
• 0:45
  First of. All I know you are, you know
• 0:46
  lots about this. Let's just say this up front.
• 0:48
  You know lots about this and I know almost nothing though, so
• 0:50
  I'm excited to learn about this. When?
• 0:51
  You say how the Internet gambles on the future.
• 0:54
  Yes, I personally know how the Domain Name System works and the
• 0:57
  entire future of the Internet itself is a gamble, so we should
• 1:00
  start with that because I'm not even sure it's going to stay
• 1:02
  working you. Giant giant nerd.
• 1:05
  It's just, it's, it's held together with like gum and tape
• 1:07
  pretty much and a whole bunch of like hope and not a lot of
• 1:10
  redundancy that keeps the Internet running.
• 1:12
  They're just like, well, this should work.
• 1:13
  And you're like, is that the right answer?
• 1:15
  It's a little thing that was meant to exchange research
• 1:17
  papers. Basically, I know basically.
• 1:20
  Was never meant to run the world.
• 1:21
  And now there's trillions and trillions of dollars of market
• 1:23
  cap that are dependent. On all right back to the topic
• 1:25
  at hand, the price of probability inside the
• 1:27
  prediction market craze. Let's go I.
• 1:29
  Predict the this is going to go. Well, I predict this is going to
• 1:31
  be a disaster. Oh, all right.
• 1:32
  Those shares a lot more expensive than my shares.
• 1:46
  Prediction markets. This ain't just some backroom
• 1:48
  dice game. It's a high stakes so-called
• 1:50
  truth machine. As they say, where there's real
• 1:52
  paper on the line, all that bias and cap goes out the window.
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  Who says that? People?
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  You got to watch where the heavy hitters are laying their stacks.
• 1:59
  They're forcing every loudmouth to put up or shut up on
• 2:01
  everything from global beats to the next tech play.
• 2:04
  We're talking decentralized so-called wisdom, where the
• 2:06
  price tells you exactly who's holding the winning hand in real
• 2:09
  time. In a world full of fakes, these
• 2:11
  markets have actual skin in the game.
• 2:13
  So stop listening to the noise and start tracking the trades.
• 2:16
  The bag don't lie. Also, don't tell anyone the
• 2:18
  number 5 is lucky. OK, I understand your position
• 2:23
  now. Yeah, Yeah, I think I get it.
• 2:25
  I feel like you put prediction markets into the same bucket
• 2:28
  that I put astrology. That's what I feel like you do.
• 2:30
  How close am I? Am I pretty close?
• 2:32
  Am I? Am I getting there?
• 2:33
  You're. Close.
• 2:33
  I think astrology I might favor a little.
• 2:35
  More yes. Yeah, my favorite Einstein
• 2:37
  quote. There are two things that are
• 2:38
  infinite the universe and human stupidity.
• 2:40
  And I'm not sure about the universe.
• 2:41
  Yeah, sure. You're not wrong.
• 2:43
  I'm. I'm with you on that.
• 2:44
  I really am. Here's the thing, this this is
• 2:46
  very early, right. What we're sort of referring to
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  as the Poly market effect is really in its like infant
• 2:52
  stages. I do think that its trajectory
• 2:55
  is pretty clear and these markets are going to continue to
• 2:57
  expand. Prediction markets trajectory is
• 2:58
  clear to you to. Me.
• 2:59
  I think so. And you'd like to bet on that?
• 3:01
  I would. Like to bet on that.
• 3:02
  I would all this entire show should just be us placing bets
• 3:05
  and opening markets. I'm actually somewhat surprised
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  as we'll talk about how far regulation has already come to
• 3:10
  sort of catch up and try to curb this.
• 3:11
  Yeah, there are still big gaps. We're we're nowhere near being
• 3:14
  close, but it is farther along than I would have fact that I
• 3:16
  would have bet against that. You'll have to tell me about
• 3:18
  what that regulation is because I don't know.
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  Again, this is your your area more.
• 3:22
  Than mine, but I think now in in the sort of the AI genie that we
• 3:25
  can't shove back into the bottle, you're going to see
• 3:27
  acceleration in this forecasting market like you're just going to
• 3:30
  see it continue to to speed ahead.
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  It's really going to change how we have to operate, especially
• 3:35
  in business, but even just in in life, because the data is going
• 3:37
  to come so much faster, The information will come so much
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  faster than we're used to before.
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  And you think what we're getting from prediction markets is
• 3:43
  actual data that we should base decisions?
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  On yeah, it's got some noise in it for sure, but the signal
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  looks like it's about as good as what we've known before.
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  It's just coming much faster. And again, it's early days, so I
• 3:53
  suspect that we'll get better and not worse.
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  So to me, this isn't gambling, right?
• 3:56
  This isn't a story about gambling, right?
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  It's about how you how you sort of form and extract truth in a
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  decentralized and I want to just reiterate high speed environment
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  like the speed is something that gets glossed over a lot, but
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  it's so much like orders of magnitude faster than anything
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  else that we've seen. And to me this is fun because to
• 4:13
  me this is completely a story about gambling. 100% sorry about
• 4:16
  gambling. I love these episodes where we
• 4:18
  come from two different angles. Well, yeah, but it we if we were
• 4:21
  both right, that wouldn't be fun.
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  So I appreciate you take the other side of right and you're
• 4:24
  more of the stars of stars I love.
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  Having these conversations with you because you are smart and so
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  I know eventually you'll see it my way.
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  This is going to be fun. And another thing about why
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  Windows is great. It does seem like at least
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  again, early days that the ability to harness the masses,
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  the the sense of the masses, especially when you put
• 4:46
  something on the line. That's what we're going to talk
• 4:47
  about here in a second. Yes, is more accurate than a
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  handful of experts. Not in everything, I want to be
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  clear, not in everything, but in some things it does seem to be
• 4:56
  more accurate. And I find that somewhat
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  fascinating. And again, I don't think this is
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  all dialed in yet, but man, for, for where we are in 2026 of
• 5:01
  being able to put some capital behind a decision.
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  They say what we would commonly refer to as a bet on an outcome
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  and then at scale that can help you divine the truth.
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  We could sit here for hours, I think, and go back and forth
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  about your position versus the right position.
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  But instead of doing that, what I think we should do is break
• 5:17
  something to some chunks. Sure, sure.
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  You're not gonna like any of them.
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  I can already tell we're gonna break it into four parts.
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  The first being sort of what I'm thinking of as the mechanics,
• 5:25
  right? The like, why does the wisdom of
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  the crowd or why do we think the wisdom of the crowd works?
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  What does that mean? And, and, and how do we
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  structure that? Then there's the what I'm
• 5:32
  calling the current implement patients.
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  So the rise of these event markets that have come to exist
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  really in just the past handful of years.
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  Kaushi and Polymark polymarkets are the 2.
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  Big ones, yeah. Then I want to talk a little bit
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  about what I will just call the cheating, because there's a lot
• 5:45
  of cheating that we know about and then there's a whole lot of
• 5:48
  cheating that we kind of don't know about, but kind of suspect.
• 5:51
  And then the performance, and I think that's the most exciting
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  one, is to talk about how these things have done so far in its
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  very sort of nascent life. How does that how the?
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  Prediction markets have done. How have their how have their
• 6:00
  outcomes been? Compared only to astrology,
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  Excellent. They do great.
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  Compared to astrology, up 3%. Looking forward.
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  Does that sound good? That sounds great.
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  Let's get started. Talk to me about the mechanics,
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  the wisdom of the crowd. What?
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  What is this all about? So it's not to, and I, I said
• 6:13
  this earlier sort of in jest. This isn't like crystal ball I'm
• 6:16
  throwing a dart. This is, it's more collective
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  math, right? It's more looking at the masses
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  and trying to figure out what the masses.
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  Believe. Let's explain that because the
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  masses actually are putting real money on to some position.
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  Yes. Will will this happen?
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  Will this not? Most all of these are set with a
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  specifically a, a binary outcome.
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  You are betting on a yes or no question.
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  And if the event happens, typically that contract is worth
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  $1.00. And if it doesn't, it's worth 0,
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  right? Just to keep it simple.
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  That's the way these are implemented.
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  So it makes it very easy. Now, this implies odds that are
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  whatever the prices that you're betting.
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  So if you're saying, if there's a contract that says really a
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  billionaire go to Mars this year, if that's trading at 30-4
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  cents, the market is collectively saying there's a
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  34% chance that it happens. And then if it doesn't, you're
• 7:00
  on the 66% side. The incentive is that you're not
• 7:02
  just giving in your opinion, but you're buying a piece of the
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  future and that market will change, right?
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  So if you think the chance is actually 50% of this billionaire
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  going to Mars and you buy at 34%, you've got arbitrage on
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  that. That difference, that 16 cent
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  difference is what you're effectively buying or
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  potentially gaining. Does that make sense?
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  And this is different from gambling.
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  This is different from just placing a bet on whether or not
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  a billionaire goes to Mars, because this is a so-called
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  event contract. It's like a swap.
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  Yes, it's an event contract. Which it's a financial
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  derivative. We we could probably do a whole
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  episode on the, let's just call it the pedanticness.
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  Of that you mean by. That well, it's a bet, but all
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  bets are on future outcomes. So like, I don't know, I just
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  think I feel like it gets a little grey in there like yes,
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  this is a a swap on a future. It is a yes no side, but that is
• 7:45
  in fact what we would classically call a bet.
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  That's 100% a bet. They literally call it bets in
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  their ads. Yes, you know, I feel like there
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  there's a lot of legwork that goes into to making specifying
• 7:54
  the difference, but I'm like, what bet is not on a future
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  outcome? You don't bet on past outcomes.
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  Sure, that wouldn't make any sense.
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  But by calling it an event contract, it gets them around
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  state taxes and age requirement. Yes, and that makes it not
• 8:04
  gambling. But again, let's talk about
• 8:06
  roulette for a second. Oh, I like this.
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  A ball gets dropped onto a wheel and lands on a number.
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  Yes, that is a future. Outcome.
• 8:13
  Of course, that's a future outcome.
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  That's what it is, absolutely. I'm just going to leave that out
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  there for a second. So what you're saying is this is
• 8:18
  100% gambling? I'm saying this is 100%
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  gambling, yes, and I'm looking forward to the polymarket mafia
• 8:23
  coming up to my house later on today.
• 8:25
  Sure, there's 100% chance of. This is bucket shops that are
• 8:27
  legal I. Don't know what a bucket shop
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  is? Oh, my goodness.
• 8:29
  It was like in the early 20th centuries, they had these
• 8:31
  storefronts. Yeah.
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  And customers could on stock price movements without
• 8:35
  actually. Oh, yeah, yeah.
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  Stocks. I know they were called bucket
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  shops. Oh yeah, yeah, yeah, yeah.
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  Which by the way, those exist now.
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  There are just platforms where you can do exactly that,
• 8:43
  basically a bucket shop. No, no, no, not basically 100%
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  is I. Don't know a better way to put
• 8:48
  this. This is a third party
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  derivative. In other words, I have no that's
• 8:51
  how you think. No benefit from the outcome.
• 8:53
  I don't actually hold this. Well, in theory.
• 8:55
  This is not like corn futures where I'm a corn farmer and I'm
• 8:58
  selling my futures of corn, Yeah, so that I don't I no
• 9:01
  longer have risk of no rain or too much rain or all of those
• 9:04
  sorts of things. I'm betting on locking at a
• 9:06
  price. That's a way to think of it.
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  That's a first person derivative.
• 9:09
  A third party derivative. It would be where I have no
• 9:11
  outcome, just somebody who's betting on corn.
• 9:13
  By the way, in futures, eventually if I sit around,
• 9:16
  truck is going to pull up if I don't sell my futures in corn
• 9:19
  and it's going to deliver corn to me.
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  Yes, because I am actually a first party to this.
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  Bet. Yes, exactly.
• 9:25
  That's why you want to get the beaks report early and often.
• 9:28
  So in order for this to work, there's wisdom of the crowd.
• 9:30
  To work, you need a handful of things.
• 9:32
  And this is James Sarawky's. I think it's I think it's
• 9:35
  Polish. This comes from his wisdom of
• 9:37
  the crowds. In order for a crowd to be
• 9:38
  smarter than an expert, it needs three key things.
• 9:42
  The first thing you need is diversity.
• 9:43
  So you need a mix of the, you know, the rocket scientist and
• 9:46
  the bored teenager and the industry insiders.
• 9:48
  You need all of them looking at the same problem from different
• 9:51
  angles. You need independence so that
• 9:53
  people aren't just following a leader like some, you know,
• 9:55
  whatever TV pundit or someone who's who's sort of quote UN
• 9:58
  quote leading the market. They need to make their own
• 10:00
  choices based on their own private info.
• 10:02
  And then you need decentralization so that there's
• 10:04
  no like arbiter of the decision making.
• 10:07
  The answer emerges from the bottom up.
• 10:09
  How do you 'cause that to happen on Cauchy and polymarket?
• 10:12
  If I have a lot of money, how do I just not take a massive
• 10:15
  position on something to sway the entire market?
• 10:17
  You can take a massive yeah, you can and you can you can try to
• 10:20
  move the market, but the point is the market will correct
• 10:22
  itself. That's the, the, the point here
• 10:24
  is that if somebody goes in and drops 10 million bucks on a bet,
• 10:27
  everybody go, well, I'm going to buy the other side of that.
• 10:29
  It's going to swing the numbers way to the favor of me buying
• 10:31
  the other side because there's so much, so much cash on one
• 10:35
  side of the bet. That's not really how human herd
• 10:37
  mentality works. We all start to question our our
• 10:40
  own logic and go oh, maybe that billionaire really will go to
• 10:43
  space. This.
• 10:43
  Week but then guys like you like to go the other way go well now
• 10:46
  I can buy these shares for half a cent and I think this is an
• 10:49
  85% outcome so I'm in the money and you go buy a bunch of them
• 10:52
  right and swing it the other way.
• 10:53
  That's how this is supposed to work.
• 10:55
  They don't do short term things like that, but yes.
• 10:56
  I understand, but that's the point, right?
• 10:58
  The point is if you believe in the other side and someone tries
• 11:01
  to move the market, now it's just made the people who have
• 11:03
  strong belief in the other side a better opportunity for them to
• 11:06
  move the market back. OK, so you know those three
• 11:07
  things, right? And then one of the the big
• 11:09
  differences about these, well, call the modern implementations
• 11:12
  of these event markets, so specifically polymarkets and and
• 11:15
  Cauchy are that you have to put skin in the game.
• 11:17
  You have to actually put up some cash.
• 11:19
  You can't just give your position by saying, oh, I think
• 11:21
  this is going to happen because it makes you feel good or does
• 11:24
  some some amount of virtue signaling.
• 11:25
  You actually have to make a bet. Like the guys who are buying all
• 11:28
  those shares of GameStop. Well, that's an interesting
• 11:31
  parallel, and one that is harder for me to speak to because they
• 11:34
  have propped that up for a hell of a lot longer than I would
• 11:35
  have expected. Buy and Hodel.
• 11:37
  Buy and Hodel. Yeah, that's a whole, that's a
• 11:38
  whole separate show. Because why has that persisted
• 11:40
  for as long as it has? It doesn't fit for me, but
• 11:42
  somehow it has. The belief is that by having
• 11:44
  skin in the game, you can filter out some of the noise because
• 11:48
  over time you're going to lose money to the people that who
• 11:51
  know. So you're you're the smart
• 11:53
  money, the people with the best information of having a louder
• 11:55
  voice in the price than the loudest people on on, you know,
• 11:58
  whatever the social media or the discussion board for sure, sure.
• 12:00
  So then you need they need some form of calibration, right?
• 12:03
  You need some sort of truth, some sort of arbiter of truth
• 12:05
  that isn't an individual but is a consensus.
• 12:08
  That gets a little interesting, right, how these systems are
• 12:11
  decentralized so that you're not just getting a piece of news
• 12:13
  from a single news source, but you're instead of.
• 12:16
  Getting a truth engine to this. Yes, some sort of truth engine.
• 12:18
  And I really do think that as a whole, that's an entire deep
• 12:21
  dive topic that I'm still trying to wrap my brain on how that
• 12:23
  works. But it's pretty awesome that you
• 12:25
  have these really fast resolution times and you
• 12:27
  incentivize people for the truth.
• 12:29
  And that seems to. Work, say fast, about two hours.
• 12:31
  Two hours, yeah, Two hours are the ones that I've looked at.
• 12:33
  What I'd like to highlight is that if you go to a poll of
• 12:36
  someone, which is a more common, at least historically common
• 12:39
  metric for determining the outcome of something, you ask
• 12:41
  them what they think they're going to say what they want to
• 12:44
  say, right? In polls, you hear what people
• 12:46
  say, but bets measure what they believe.
• 12:49
  There's a gap there, right? People don't say what they
• 12:50
  believe. There can absolutely be a gap.
• 12:52
  Let me see if I can make that a little clearer.
• 12:54
  When you have a poll like are you going to vote for Donald
• 12:57
  Trump? What you're going to get is a
• 12:58
  number of people who that shows that Donald Trump is going to
• 13:01
  win by 1% or whatever that poll outcome is going to be.
• 13:04
  Sure, when you have a Kaushi like thing, will Donald Trump
• 13:06
  win? What you have is by what
• 13:07
  percentage of the people betting do you think Donald Trump will
• 13:10
  win? Well, you're actually getting an
• 13:11
  odds and you're not getting a rating of how he will do in the
• 13:14
  vote. You're getting a likelihood of
• 13:16
  him getting that 61 percent or? 51% yes, yeah, absolutely.
• 13:19
  People are betting on it, not just taking account and then
• 13:21
  extrapolating from. That so it's a very different
• 13:23
  thing than a. Poll, I want to be very specific
• 13:25
  here. A typical political poll yes,
• 13:27
  would work exactly that way. I'm saying if you poll people
• 13:29
  and ask them who's going to win, not how they voted, there's a
• 13:31
  difference. I'm specifically comparing those
• 13:33
  two. People are going to tell you not
• 13:35
  what they believe, right? They're going to tell you what
• 13:36
  they want to say. Money is where the belief comes.
• 13:39
  There is a difference. So those two are comparative.
• 13:42
  It's not what what they're voting, but it's you actually
• 13:44
  saying what do you think is going to happen, right.
• 13:45
  What they say is different than what they believe.
• 13:47
  That's the point that I'm trying to make.
• 13:48
  Does that make sense? You sort of when you put the,
• 13:50
  the, the capitalistic element into this, people all of a
• 13:53
  sudden start to be a little more, more truthful and honest.
• 13:56
  Cautious. Yeah, I'm not cautious.
• 13:58
  I'd say just say, just say honest.
• 13:59
  The guy who ran Lehman Brothers before it went bankrupt had 99%
• 14:02
  of his net worth in Lehman Brothers, and he had all of his
• 14:05
  belief that they were going to pull out of this.
• 14:07
  Sure. So people do bet completely the
• 14:09
  wrong way in aggressive ways. It does happen.
• 14:12
  Oh yeah. It doesn't make them more or
• 14:13
  less right. No, but that.
• 14:14
  But this is the part you don't get.
• 14:16
  You need the diversity of people.
• 14:18
  That's how you ultimately get it right.
• 14:19
  How many people bet against Lehman at the time?
• 14:22
  I don't even think that's a fair comparison, but more than one.
• 14:24
  Certainly it wasn't just him. So that's the difference is that
• 14:27
  you've now have the money, keeps people from just clicking on
• 14:30
  what they feel is right, like you need some sort of currency.
• 14:32
  In this particular case, we're using capital.
• 14:34
  Skin in the game, as you say in. Others, they use reputation,
• 14:37
  right? There are some of these markets
• 14:39
  that don't use cash, they use reputation.
• 14:41
  Over time, as you build up a reputation, now that becomes
• 14:43
  valuable to you. So now you, you don't want to
• 14:45
  risk that. In this case, we're just using
• 14:47
  cash. I think it's the easier one to
• 14:48
  understand. Now you get this like level of
• 14:49
  discipline that you just don't see typically in public life
• 14:52
  because in public you're putting on some performance, especially
• 14:55
  on social media. You're trying to signal some
• 14:57
  part of your identity. And we look behind the curtains.
• 14:59
  In many cases, what they're placing bets on do not align
• 15:03
  with what they're trying to signal.
• 15:04
  Without money in the game, sometimes you're you're betting
• 15:06
  on what you hope, not necessarily what.
• 15:07
  Yeah, or, or what you want other people to see, right.
• 15:09
  I think that's another part that you and I don't, it doesn't
• 15:11
  resonate with you. And I is folks are like, well,
• 15:13
  I'm going to pretend that I'm this person.
• 15:15
  It's like you and I just kind of say what we believe in a
• 15:17
  prediction market, you are incentivized to be accurate.
• 15:19
  You only win if you're accurate. Noise is arguably punished,
• 15:23
  whereas online you could be noisy all you want, on social
• 15:25
  media don't care. Like actually, arguably noisy is
• 15:27
  better. Better for you to be noisy if
• 15:29
  your goal is to get more people to listen to you.
• 15:31
  The wishful thinking in prediction markets doesn't go
• 15:33
  very long. You're not going to last very
• 15:35
  long there, at least not with a good return.
• 15:36
  Same with a sports book, though. You're putting money down on a
• 15:38
  team. In a sports book, same sort of
• 15:39
  thing. You're betting against the
• 15:40
  house. Here, you're betting against
• 15:41
  another human. Right.
• 15:42
  No. In a sports book, arguably
• 15:44
  you're betting against the other side of the bet.
• 15:46
  If the book is run correctly, you're betting against the other
• 15:49
  side of the bet. I think those are pretty pretty
• 15:51
  analogous. OK, 'cause the the house isn't
• 15:53
  taking a position. In theory, the house made a
• 15:55
  market and they try to balance the bets so that you're on one
• 15:58
  side or the. Other Well, the house is taking
• 15:59
  a 4% vig or. They're taking VIG 10% in any
• 16:02
  case they. Want, Yeah, yeah, in the case of
• 16:03
  the prediction markets, it's a 1%.
• 16:05
  Vig as the market moves, there's reasons why you can't keep it
• 16:08
  balanced. But if you can keep it balanced
• 16:09
  in a sports book, you always make money as the house.
• 16:12
  Sure, always. But if it's unbalanced, then
• 16:14
  that's when you can actually lose money and then a a rake
• 16:16
  comes out. Is there someone actually on a
• 16:18
  on a very small scale making markets where they're covering
• 16:22
  gaps so that there is a market? Yeah.
• 16:24
  You know what a market maker is. I buy a few shares just so that
• 16:26
  there's a, so that there's a big kick it off that we've
• 16:28
  established. Yeah, yeah.
• 16:29
  I don't know how that works on these.
• 16:30
  I, I suspect there is some form of market making, but I also
• 16:34
  don't know if, if you don't get a market when it just falls off,
• 16:36
  there's no cost to it. So I think it just falls off,
• 16:39
  but I don't know. That's a really good question.
• 16:40
  OK, let's talk about like the event market, the implementation
• 16:43
  of these things, sort of how this has happened.
• 16:44
  And this isn't new. A lot of people I that I've
• 16:46
  talked to think this is like some side effect of crypto and
• 16:50
  it's not right. We've had the for a long time
• 16:53
  and even before we had what I will call sort of scientific
• 16:55
  polling, we had early forms of prediction markets that existed,
• 16:58
  usually the form of political betting.
• 17:00
  One of these dates back to the early 1500s where people bet on
• 17:04
  who would be the next sort of papal successor.
• 17:06
  And even then it was already considered a quote, old
• 17:08
  practice. It's not like this is new,
• 17:10
  right? This has been around for a
• 17:12
  while. But the part that comes from
• 17:13
  cryptocurrency is the polymarket is based on the Polygon
• 17:17
  blockchain, which is sort of derived from the blockchain that
• 17:20
  you use in cryptocurrency. Yeah, yeah.
• 17:22
  I'm just saying these didn't come from crypto.
• 17:23
  Crypto is an implementation of, I'd argue, a very good
• 17:26
  implementation of this because now you've got some visibility
• 17:28
  into what's happened. It's also the way they use the
• 17:30
  truth machine to sort of lock in what the answer is in a version
• 17:33
  of the blockchain. My my point is these existed
• 17:35
  before that this sort of enabled it.
• 17:37
  Could you have done this as well without blockchain?
• 17:39
  Probably not, right? You're standing on the shoulders
• 17:41
  of cryptocurrency. Yeah, yeah.
• 17:43
  That's good to think. Of it in a way because there is
• 17:44
  a distributed Ledger. Romans were obsessed with with
• 17:46
  betting on who be the next Pope. You mentioned the Wall Street
• 17:49
  bets of like, I think that was like the late 1800s, right?
• 17:51
  Where you would sort of bet on stocks without actually owning
• 17:54
  the stock. The bucket shops the.
• 17:55
  Real sort of what I'll call like intellectual Big Bang for
• 17:58
  prediction markets happened in the 1940s, and that was from the
• 18:01
  Nobel Prize winning economist Frederick Hayek, who argued that
• 18:05
  the most important Information Society is truly dispersed.
• 18:08
  It's dispersed across many so that no one person knows
• 18:10
  everything. But the market price acts as a
• 18:12
  giant vacuum, sucking up all those little pieces of secret
• 18:15
  information and turning them into one single accurate number.
• 18:18
  Right run single signal. That was his theory.
• 18:21
  It does start to to move your focus from like just listening
• 18:23
  to the the one or or two smartest people in the room and
• 18:27
  looking at what the whole market is saying.
• 18:29
  Everybody gets a voice the. Precursor for the modern Poly
• 18:32
  markets and and Kalchi's was what we call the Iowa
• 18:34
  experiment. So this is in the late 80s and
• 18:36
  this was the Iowa electronic markets.
• 18:38
  So the University of Iowa professors were annoyed that
• 18:40
  pollsters didn't see Jesse Jackson's 1988 success coming.
• 18:43
  So they launched a political stock market as a like just a
• 18:46
  small academic experiment and it worked for for decades.
• 18:49
  IEMS market prices were more accurate than professional
• 18:51
  polls, about 75% of the. Time and the federal government
• 18:54
  turned a blind eye to this trading just because they
• 18:57
  thought it was research. Yeah, they, they put it under
• 18:59
  the the guise of research, which it was.
• 19:00
  I mean, there there wasn't anyone like really making money
• 19:02
  on this. It wasn't like it had been
• 19:03
  marshallized money. Yeah.
• 19:05
  They were limited in what they could bet.
• 19:06
  Yes, and it proved that the people are much more honest when
• 19:08
  they have to put up 5 bucks instead of just answering a
• 19:11
  phone survey. So that was like the first
• 19:13
  modern example of this this working.
• 19:15
  There were some not great examples of this.
• 19:18
  This was one that I I put very vague recollection of but didn't
• 19:20
  really know the details of. In early 2000s, 2003, there was
• 19:24
  a professor named Robin Hanson who worked with the Pentagon to
• 19:26
  create a market where people could bet on things like coups
• 19:28
  and terrorist attacks in the Middle East.
• 19:30
  And politicians just hated it. It got really bad press.
• 19:33
  I think people didn't fully understand it.
• 19:34
  They called it sick and grotesque.
• 19:36
  The project was shut down 24 hours after it was sort of
• 19:39
  disclosed or made available. And the prediction markets were
• 19:42
  sent like, just into the dark ages of regulation.
• 19:44
  They were just completely set aside for for two decades.
• 19:47
  It's pretty dark. Well, yeah.
• 19:49
  I mean, it isn't. It isn't.
• 19:50
  It brings up an interesting point, though.
• 19:51
  Yeah, imagine I'm like an Israeli pilot and I'm in flying
• 19:55
  over. I know I'm been ordered to go
• 19:56
  drop bombs on Lebanon. I pull up my phone very quickly
• 19:59
  before I drop my bombs, and I make a nice big bet on Kaushi
• 20:02
  that there's going to be a bomb dropped on Lebanon within the
• 20:06
  next two hours. And I bet all the money I own
• 20:08
  'cause I'm gonna go drop that bomb.
• 20:10
  Yeah, the rest of the world doesn't know that.
• 20:11
  Yeah. So information there is not
• 20:12
  distributed. Well, this is the, this is the
• 20:14
  now you're getting like what I think of as insider trading,
• 20:16
  right? That would be.
• 20:17
  Pretty inside I I wanted to at least cover.
• 20:19
  Some of these markets, before we jump into that, like the OK, OK,
• 20:22
  just because like we've talked about calci and polymarkets.
• 20:24
  So those are the ones that most people know.
• 20:26
  They've got different positions, they sort of focus on different
• 20:28
  things. But for the most part those are
• 20:29
  the big ones. There are many others.
• 20:31
  There's a a sort of newcomer that's owned by crypto.com
• 20:34
  that's been focused on margin trading.
• 20:36
  They, they've been allowing you to like ratchet up margin to bet
• 20:38
  on anything from sports to politics or to culture.
• 20:41
  Fabulous. So people can borrow a lot of
• 20:43
  money for their yes. Exactly.
• 20:44
  So you can. You can borrow the money.
• 20:45
  You're gonna lose what? A great idea.
• 20:47
  There's still some, some academic focused ones.
• 20:50
  Predicted is 1, the calculus is 1.
• 20:52
  I find those to be even more interesting.
• 20:55
  And then you got all sorts of underlying infrastructure that
• 20:57
  are starting to aggregate these, which I find fascinating
• 21:00
  specifically for finance and, and for others.
• 21:01
  So my point is, it's not just calci and polymarkets.
• 21:04
  There are many others that have moved into this space.
• 21:07
  I don't think they're all going to survive.
• 21:08
  I think, you know, with a handful of players in different,
• 21:09
  different sections, but there's a lot.
• 21:11
  The big take away for me from this is like the information is
• 21:13
  moving a lot faster and I see no world in which it slows.
• 21:16
  Down and and so they'll be they'll be more betting on.
• 21:18
  It no no, you just get signal much faster.
• 21:20
  You can't wait for a survey. You'll be so far behind if
• 21:23
  you're, I'm just thinking like if you, if you're making
• 21:24
  decisions, if, if you're an executive at your corporation.
• 21:28
  Well, this is a survey. You just happen to have money at
• 21:30
  stake. But but my point is that the
• 21:32
  information is coming at you much faster than waiting three
• 21:35
  weeks for a Bloomberg survey to complete.
• 21:38
  Sure, like you get real signal, valuable signal well ahead of.
• 21:41
  That, by the way, both Polymarket and Calci bet that
• 21:44
  the Chiefs would win the Super Bowl.
• 21:45
  Yeah, sports betting sports betting.
• 21:46
  Get out of sports betting firm. But back up a second, you know
• 21:48
  how much of Sports Betting Calci's trade volume is?
• 21:51
  There's a lot. It's 90% of what they do.
• 21:54
  Currently, I think it's less than that.
• 21:55
  I think it started out as that. And FanDuel is the sports
• 21:57
  betting platform. Cauchy is considered not the
• 22:00
  sports betting platform, yet 90% of their betting of their of
• 22:03
  their trade volume. I know it started that way.
• 22:06
  When is is that? Court filings, regulatory
• 22:08
  disclosures and 3rd party data analytics says 90% of trading
• 22:10
  volume on Cauchy is betting on sports.
• 22:12
  I mean, it looks like as of currently they're still north of
• 22:16
  88%. So as of April, you're still
• 22:20
  seeing about 70. 97% for April was sports related.
• 22:25
  So it's still pretty high, still higher than I thought.
• 22:27
  You have to ask yourself why do state gambling laws not apply
• 22:30
  here instead of CFTC oversight? That's that's to me, what's the
• 22:33
  what's the difference? Regular gambling?
• 22:35
  What's the difference? You drop a ball into a under a
• 22:38
  roulette table, it's a future outcome.
• 22:39
  What's the difference? It's a probability based future
• 22:41
  outcome. By the way, I was never in favor
• 22:43
  of swaps becoming legal. Sure, Just to really show you
• 22:45
  how far back I go. Yeah.
• 22:46
  So now you're into insider trading.
• 22:49
  Line, you're saying there's insider trading going on in the
• 22:51
  prediction? Markets.
• 22:52
  None. None at all.
• 22:53
  This is all above board. Everything here is great.
• 22:55
  Everything here is perfect. See, this is where it gets
• 22:57
  really interesting. I no longer know what is insider
• 22:59
  trading and what isn't. It was always had some element
• 23:01
  of blurriness to me and now it just has even more.
• 23:04
  Sometimes I can affect the outcome.
• 23:05
  I mean like those people who were throwing dildos on the WNBA
• 23:08
  course and now that because this market exists.
• 23:10
  Number of dildos thrown on the court.
• 23:12
  Yeah, somebody the odds of a dildo big thrown on the WNBA
• 23:14
  court, I now can affect that outcome.
• 23:16
  Yes, I can now go throw a dildo and make that pay off.
• 23:19
  So I can bet really big. Of course.
• 23:20
  That's what's so interesting to me about these things.
• 23:23
  It's like even before you get to prediction markets, if you just
• 23:26
  think about what we call classic, you know, non betting
• 23:29
  stock markets, you know, well, OK, it's pretty clear what
• 23:32
  insider trading is. You have information, it's not
• 23:33
  publicly available, it's insider trading.
• 23:35
  And then you realize what percentage of large trades are
• 23:38
  being made with insider information.
• 23:40
  You just can't connect the dots as easily.
• 23:42
  Somebody hears from somebody, from another source, they got a
• 23:44
  guy who knows a thing. You know, this is coming and
• 23:46
  maybe you don't have a Direct Line, but you got a dotted line
• 23:48
  to a thing. That's still insider training,
• 23:50
  right? And what what percentage of that
• 23:51
  that does not get dealt with in a civil or criminal manner?
• 23:55
  99.999%. Huge percentage of right, huge
• 23:58
  percentage of virtually all of it does what it has gotten dealt
• 24:01
  with in the case of stock market manipulation from insider
• 24:04
  trading. A lot of times they get busted
• 24:06
  on the little bit that they can get busted on, yes, but the
• 24:08
  other billions they've made they get to keep because they didn't
• 24:10
  get, you know, nobody, nobody proved that on they can't prove
• 24:12
  it percentage. Yeah, In a capitalistic world,
• 24:14
  who's supposed to keep them honest?
• 24:16
  They're not incentivized to stay honest, especially if you can't
• 24:18
  prove it. How does that work?
• 24:19
  You expect them to be like, well, I have this information I
• 24:21
  shouldn't and trade on it super tough.
• 24:22
  Yeah. If I take that view and look at
• 24:24
  prediction markets, I'm like, man, I could argue prediction
• 24:26
  markets are more regulated than what you see.
• 24:28
  Oh, no, In the stock market. You have this, you have the
• 24:29
  exact same problem. I literally can, in many cases,
• 24:32
  I can cause the outcome. I can go streaking on the the
• 24:35
  Super Bowl, yeah, grounds and I can win my bet because I caused
• 24:38
  the event to happen, Yeah. But you've got more visibility
• 24:41
  into who placed the bet that you don't have as much visibility to
• 24:44
  who placed the bet in the financial.
• 24:45
  Market that's not true. We we end up busting these
• 24:47
  people. I'm saying as a percentage of of
• 24:49
  trades made and bets placed, I suspect you probably have very
• 24:52
  little regulation and enforcement in prediction
• 24:54
  markets more as a percentage played than in the non
• 24:58
  prediction markets in the financial market, maybe I don't
• 25:00
  know. We sort of think of insider
• 25:01
  trading into a couple buckets. You've got the folks who can
• 25:03
  manipulate the market, which are are the ones that the the puppet
• 25:06
  masters, the market manipulators.
• 25:08
  And if you can influence the outcome, if you can throw the
• 25:09
  dildo onto the court right then you shouldn't be allowed to bet
• 25:12
  off. Most folks, except for the folks
• 25:14
  who are actually doing it, would agree that that's.
• 25:16
  Good. Let's say I'm the guy who throws
• 25:17
  a dildo on the court and I don't actually bet on it, but I tell
• 25:20
  all my friends you should bet on me throwing a dildo out on the
• 25:22
  court. Well, that would be the next
• 25:23
  bucket, right? That's where you have
• 25:24
  information. How do I connect those dots?
• 25:26
  That's going to get a lot tougher.
• 25:27
  But you have that same problem now in financial markets.
• 25:29
  You can't connect those dots. I do.
• 25:31
  I'm not saying that's any better.
• 25:32
  That's the same. It's the same problem.
• 25:33
  Right. Same with like the you mentioned
• 25:35
  earlier, the the leaks, right? We're prosecuting a guy right
• 25:37
  now because he was part of the armed forces that went into
• 25:41
  Venezuela and he placed a bet before he went in on exactly
• 25:45
  when this was going to happen and got paid out.
• 25:46
  So he leaked classified information effectively by
• 25:49
  placing this bet. Sure.
• 25:50
  He didn't say that he had inside information of it.
• 25:52
  But what I think is we're going after, like in this particular
• 25:55
  case, we're going after this guy who placed a bet on when we were
• 25:58
  going to invade, not invade, but but but go into Venezuela to
• 26:02
  remove the people that were in power.
• 26:03
  And that's pretty bad, right? I think it's leave class
• 26:04
  information that's pretty bad. But then you look at some of the
• 26:06
  other bets that have been placed on large market moving
• 26:09
  situations, that information had to come from the top.
• 26:12
  And we're not prosecuting any of those folks, at least not yet.
• 26:14
  Of course, of course. And that to me is a bigger
• 26:16
  problem. Like people should go to prison
• 26:17
  for this. I think we're just going to put
• 26:19
  the wrong people in prison for it, at least to start.
• 26:20
  We'll see if that if that changes.
• 26:21
  Absolutely true of financial markets as well.
• 26:24
  It does seem like, and I am let's just say less than
• 26:26
  cautiously optimistic there's going to be a continued analysis
• 26:31
  and productization around catching these folks because
• 26:33
  it's not in the market's best interest to catch them, right?
• 26:35
  It's in the market's best interest for them to exist.
• 26:37
  Ignore they make. Yeah, exactly.
• 26:38
  Just like the financial markets, you make money on volume, so you
• 26:40
  want more volume. So I'm just like, are you really
• 26:43
  incentivized to catch these folks?
• 26:44
  Like, isn't that the point of regulation?
• 26:46
  Who would catch? Them who is going to catch them?
• 26:48
  The CFTC? Never going to happen.
• 26:49
  Michael Selig, the the chairman of the, there's no way.
• 26:53
  He's a big Trumper and the Trumpers are in this thing 100%.
• 26:56
  I mean, look at Donald Trump Junior as both an unpaid advisor
• 26:59
  and an investor in Polymarket, and he's also a paid advisor to
• 27:02
  Calci. So there's no way these people
• 27:04
  are going to be regulated in any way, shape or form.
• 27:05
  Yeah, you would hope that they would self regulate that's.
• 27:08
  Not going to happen. That's never going to.
• 27:09
  Happen I mean Polymarket has worked with some blocking
• 27:11
  investigators to try to find on chain data, but again, why would
• 27:15
  they be incentivized to do this I get that you want the platform
• 27:18
  to be viewed as trustworthy, but everybody thinks they've got an
• 27:20
  edge or they they want to be able to execute on their edge
• 27:23
  when they have an edge like I really don't know what the
• 27:25
  answer for this is going to be on insider trading.
• 27:27
  I do think it's going to require a lot of data sharing right MLB
• 27:30
  has started doing this with the CFTC to to ensure that players
• 27:34
  aren't using their inside knowledge of injuries to bet on
• 27:37
  these these betting platforms. I think that's what has to
• 27:39
  happen. So the more visibility you have
• 27:40
  into that data, the better. And that's why I do think the
• 27:42
  prediction markets are different than the financial markets is
• 27:44
  you have more visibility into the data.
• 27:46
  You really do. You mentioned that a couple
• 27:47
  times. Let's talk about the good stuff.
• 27:49
  There's good stuff. What what So how have these
• 27:51
  markets perform? Yes, because I do think that is
• 27:54
  the most important questions to see specifically how they
• 27:56
  performed on things. How accurate have they been?
• 27:58
  So I've got a couple. OK.
• 27:59
  In the 2024 US election, yes, traditional polls leading up to
• 28:02
  the election were showing a coin flip and right up until the end.
• 28:05
  Meanwhile, Polymarket was consistently leaning towards the
• 28:07
  eventual winner, often by a margin of 58% to 42%.
• 28:11
  Again, because polling is not the same thing as prediction.
• 28:13
  Markets. In this cherry pick case, it
• 28:15
  ended up being more accurate. It wasn't more accurate.
• 28:17
  It was because the polls still had them within the margin of
• 28:19
  error. So the polling was accurate.
• 28:21
  There are two. Three different things.
• 28:22
  So you're saying the polling doesn't do a good job of telling
• 28:24
  you the outcome? Polling isn't telling you the
• 28:26
  outcome. OK, you don't have enough.
• 28:27
  Resolution, but we use polling to tell the outcome.
• 28:29
  When you don't have the resolution, it looks like you
• 28:32
  have an answer. When you say 5149, you do not.
• 28:35
  You don't have the resolution. So in this particular case,
• 28:37
  polling did not accurately determine the outcome of the
• 28:41
  vote. Polling exactly captured the
• 28:43
  outcome of the vote, polling said.
• 28:45
  We can't tell from our polling. Who's leading?
• 28:47
  Did it work or did it not work it?
• 28:48
  Worked 100% because it said here's the resolution we have
• 28:51
  and that's a statistic. Tie, turns out Poly market data
• 28:53
  actually looked to be pretty good at predicting the outcome
• 28:56
  of that election. I'm saying polling couldn't tell
• 28:58
  you the answer that's correct. That to me is getting it wrong.
• 29:00
  That's correct. That's the correct way to say
• 29:01
  it. Didn't give you the answer, it
• 29:03
  got it. Wrong.
• 29:03
  Didn't get it wrong, it got it right.
• 29:05
  If that question posed to polling is who is going to win
• 29:08
  the election and the answer is I don't know, is that the right
• 29:10
  answer or is that the wrong answer?
• 29:12
  That is a correct answer. I don't know is a correct?
• 29:13
  Answer. I understand that it it did its
• 29:15
  job within how it was. Did its job exactly as it was
• 29:18
  designed. But it didn't get the outcome.
• 29:20
  It didn't get the answer. Sure.
• 29:21
  My point is that in this particular case, it didn't give
• 29:23
  us the answer, which is what we were asking it to do.
• 29:26
  To me, the natural conclusion is this is another way to determine
• 29:29
  an outcome of an event. So do we think it's going to be
• 29:32
  more likely to be right in the future or wrong?
• 29:34
  That to me, is the interesting part.
• 29:36
  Like, I don't know. 'Cause they been wrong a lot.
• 29:37
  Take a look at the Republican supermajority we're supposed to
• 29:40
  get in the Congress. According to Cal, she and Polly
• 29:42
  Market, that didn't happen at all, and they bet strongly that
• 29:45
  that would happen. Take a look at Ken Paxton, who
• 29:47
  had an 83% chance of winning. Didn't happen.
• 29:50
  It's wrong a lot. I also just hate like politics
• 29:52
  and sports I think are the worst things to put through this but
• 29:54
  then I question this. Is all sports.
• 29:56
  Though, But that's the thing, that's the what I've questioned
• 29:58
  is like, is that really what all this is, is like at the end of
• 30:00
  the day, is it all just sports, big gap politics?
• 30:03
  Is that like 98% of it? It's the.
• 30:05
  Vast majority of it is sports, Yeah.
• 30:07
  They try really hard to promote themselves as oracles of the
• 30:09
  truth. Yeah.
• 30:10
  And really, it's sports book gambling.
• 30:12
  It's not really any any difference.
• 30:14
  I don't see any difference anyway.
• 30:15
  God. That's got to piss off those
• 30:16
  guys so bad. The sports books guys so bad,
• 30:18
  right, 'cause they, they fall under this is what you're saying
• 30:20
  earlier, They fall under state regulation.
• 30:22
  Yeah. So there's like states like
• 30:23
  California where they're like you can't play as they should
• 30:25
  cause California says no to sports betting.
• 30:27
  Absolutely. But then these guys are like no,
• 30:28
  no, no, no, no, no, no, no, no, no.
• 30:30
  It's a future event, therefore it's a swap.
• 30:32
  By the way, the swap should never have been allowed to be
• 30:34
  legal. Either like I didn't know until
• 30:35
  you said I didn't know Cal. She was 90%.
• 30:37
  I thought I read that that's the core as like a before thing, not
• 30:40
  as a current thing. It's it's the vast majority of
• 30:42
  their garbage. They had led me to believe that
• 30:44
  it was like 25%. I was like, OK, a lot of sports.
• 30:47
  No, no, not even close, not even close.
• 30:49
  The vast majority of their platform is sports betting.
• 30:53
  Still, as of today, sure. Sure, sure.
• 30:55
  Well. Yeah, but we glossed over, I'm
• 30:57
  like, well, why don't you go sports bet elsewhere?
• 30:58
  Well, the reason you want sports bet elsewhere is because they
• 31:01
  are regulated by States and in many states you can't bet.
• 31:04
  Now there are some differences that are not that are not
• 31:07
  obvious, but I do think are are mildly important.
• 31:10
  So like with a sports book, you have the house effectively makes
• 31:14
  the odds, the house is setting the odds, and they're moving the
• 31:17
  line. Based upon the bets they
• 31:18
  received. Typically based on how much
• 31:20
  action they have on one side or the other in the prediction
• 31:23
  markets, there's no house sure right?
• 31:25
  You're you're just trading shares with other users.
• 31:27
  It's a clearing house, so. If you buy a yes share, it's
• 31:29
  because another user is willing to sell you it at that price and
• 31:31
  the price represents this sort of implied probability that I
• 31:35
  think that is a significant difference.
• 31:36
  But at the end of the day, same effect, same effect.
• 31:39
  At the end of the day, I also think it's interesting that the
• 31:41
  market, the event markets do have a clear juice.
• 31:45
  They're showing you the vig, they're showing you the fee,
• 31:47
  whereas with most sports books, it's just sort of historically
• 31:50
  hidden. Why is that right?
• 31:51
  Well, it's implied in the odds, right?
• 31:53
  You have to calculate it in the odds, right?
• 31:55
  If you're decent at math, you can figure it out pretty easily.
• 31:58
  But it's hidden in the odds. Yeah, that is a difference,
• 32:00
  right? I mean, you, you can figure it
• 32:02
  out because you're paying 110 to get 100.
• 32:04
  Doesn't seem like hard math. To me, it's still a rate, but
• 32:07
  it's a transaction fee. You pay transaction fees
• 32:08
  everywhere, right? You process a credit card, you
• 32:10
  pay a transaction. Fee.
• 32:11
  But even though it's if it's just 1%, it's no different than
• 32:13
  if it's 5%. It means in aggregate we all
• 32:15
  lose money. Yes, of course.
• 32:16
  Because of course frictional cost of this thing.
• 32:18
  Yes, of course, but but at least it's visible, right?
• 32:21
  And I can appreciate that different.
• 32:22
  I mean, that's why calci and polymarket's volume is so high
• 32:25
  in sports betting. It's because you have like
• 32:26
  California and Texas. Cheaper gambling.
• 32:28
  Oh yeah, you get the big states. You get the big states, you get
• 32:30
  the states where, where they where there's technically sports
• 32:33
  betting is illegal. Now everybody sort of floods in
• 32:36
  the. Vast majority of of players on
• 32:38
  calci and Polymarket lose money. Well, I think it's even before
• 32:41
  you get to the insider trading, but let's come back.
• 32:43
  Yeah, let's come back to that. There's another point that is
• 32:45
  interesting. I don't think this makes up a
• 32:46
  large part of their volume, but I just want to point out between
• 32:48
  sports betting and non sports betting in events or whatever,
• 32:52
  whatever, whatever you want to call sports betting in these
• 32:53
  event markets is the age difference.
• 32:56
  If you're sports betting, that's gambling and usually that's
• 32:58
  going to be a 21 year or older majority age, right?
• 33:01
  Minimum to play in these event markets is usually 18 or over.
• 33:04
  You should have to be an adult. I don't think that makes a big
• 33:06
  difference, but it is a difference.
• 33:07
  You get more idiots, and the younger they are, the more idiot
• 33:09
  they are. I.
• 33:09
  Don't know. I'm getting Dumber with age.
• 33:12
  That's true. That's true.
• 33:13
  I'm not sure about that particular thing.
• 33:15
  There is one thing that stood out, and I want you to take us
• 33:18
  with a grain of salt. OK.
• 33:19
  But because I'm. I'm just, I don't know which way
• 33:22
  is up anymore. Sky is blue, sky is green.
• 33:24
  I have no idea. OK.
• 33:25
  There was a Federal Reserve study, sure.
• 33:27
  This year, 2026, that compared Kalshi.
• 33:30
  So one of these, these event markets to professional economic
• 33:33
  forecasters regarding things like interest rate hikes and
• 33:35
  inflation. Yeah.
• 33:36
  The markets mean absolute air was statistically identical to
• 33:39
  the pros. Sure.
• 33:40
  That kind of caught my eye a little bit, Sure, because at
• 33:43
  first I'm like, Oh well, they're equally as uninformed.
• 33:45
  As idiots, the pros. Yeah, that was kind of my first
• 33:48
  take away, which. Is true, that's 100% right.
• 33:50
  But is that really the answer? That is the absolute correct
• 33:52
  thing. But so many economists are just
• 33:54
  making things up so and man, go away.
• 33:57
  I mean, what are you talking about?
• 33:58
  What are you talking about? I want to agree with you on
• 34:00
  this, but I want to offer one potential difference.
• 34:03
  Yeah, the market gets there, the event market gets there faster.
• 34:06
  Well, sure. Right.
• 34:07
  So wait, hold on, if you're going to get, forget about the
• 34:10
  fact that the consensus. You can lose money faster,
• 34:13
  that's true. No, not.
• 34:13
  Necessarily. You at least know what the
• 34:15
  market's position is faster, right?
• 34:17
  Sure, that could be valuable. If you have a thesis and you
• 34:20
  want to bet against it, you know where it's going to get.
• 34:22
  Faster, Yeah. I'm not betting on the wisdom of
• 34:24
  the crowd for sure. You could bet against.
• 34:25
  Think about this. This is crazy.
• 34:26
  More than 2/3 of all the money that was won on Polymarket,
• 34:30
  Yeah, was won by 740 accounts. Wow.
• 34:34
  OK, that is an argument for what out of how many people?
• 34:37
  It's not 749 accounts, Jeff. It's a lot.
• 34:40
  It's. More than that, yes.
• 34:41
  Yeah. It's a lot more than.
• 34:42
  That I can put it in percentage terms of something like less
• 34:45
  than 15% of users on polymarket were actually in the black.
• 34:48
  Oh, I would have guessed the number even less than that.
• 34:50
  You're just a rube. It's a rube's game.
• 34:52
  Gambling is a tax on people who are bad at math.
• 34:54
  I mean, this is the joke is that if you're in a room playing
• 34:57
  poker and you don't know who the mark is, sure it's you.
• 34:59
  You're the one. That's the answer.
• 35:00
  I think grifters say that too. I'm just saying polymarkets and
• 35:04
  Calisher are going to answer all of our questions about the
• 35:06
  unknown, about the universe, everything that the, the, the,
• 35:09
  the hive mind knowledge will tell us, all of the things.
• 35:12
  We don't need science anymore. We can just give up on science
• 35:14
  and math. Excellent, Fantastic.
• 35:16
  But at the end of the day, the fact that it's all sports
• 35:18
  betting just makes me sad. I'm sorry.
• 35:20
  Why? Why am I sorry?
• 35:21
  No, why? Why is Why is sports betting the
• 35:25
  thing? I think people care about sports
• 35:26
  betting. I don't.
• 35:27
  I couldn't tell you why. They care about sports, right?
• 35:29
  I mean, I think that's the thing.
• 35:30
  They care about sports. That's why they do.
• 35:31
  It I'm about to care a lot less about NBA basketball for a few
• 35:34
  months. Why they're going to lose.
• 35:35
  I don't think the odds are good. Lakers are trading $0.15 right
• 35:39
  now. It doesn't look great all.
• 35:40
  Right. We have to get out here quickly
• 35:42
  before we do. Have you seen or anything good
• 35:43
  this last week? Not to mention my current dismal
• 35:47
  state of affairs with prediction markets.
• 35:49
  But if you're like me and you just think that the entire
• 35:51
  world's economy is just a giant Jenga tower, it's held together
• 35:54
  with Scotch tape and delusions, then Michael Lewis is The Big
• 35:58
  Short from 2010 is is the book that you should read.
• 36:00
  It's a great. Book.
• 36:01
  Yeah, the book. The book.
• 36:02
  Yeah, yeah, yeah. I thought you talking about the
• 36:03
  movie. But I've actually never seen.
• 36:04
  I don't think I've ever seen the.
• 36:05
  Film. Oh, it's good.
• 36:06
  It's really good. I loved the book so I can I can
• 36:08
  flex on that. But if you, if you are
• 36:10
  unfamiliar with with Michael Lewis, which I don't know how
• 36:12
  that's possible, it's the ultimate sort of I told you so
• 36:14
  story, right? It follows a handful of social
• 36:16
  misfits and math nerds who realized the global housing
• 36:19
  market was a House of Cards long before the 1st brick fell.
• 36:23
  And instead of trying to save the world, which I guess some
• 36:25
  people might try to do, they did the most prediction market thing
• 36:28
  possible. They placed a massive bet
• 36:30
  against the entire system. But everybody knows is that
• 36:32
  housing prices are never going to go down.
• 36:34
  Right. Ever.
• 36:35
  Except it turns out they are. And I thought Lewis did a great
• 36:38
  job of turning what was relatively dry financial jargon
• 36:42
  into this, like, high stakes thriller.
• 36:44
  It was heist. Yeah.
• 36:45
  Yeah. And I don't think you need to
• 36:46
  know the first thing about subprime tranches to enjoy the
• 36:49
  sheer absurdity of the characters.
• 36:51
  Like a one eyed hedge fund manager who plays heavy metal
• 36:53
  drums to blow off steam. Like, he brought in these great
• 36:56
  aspects of the characters that were that were really awesome.
• 36:58
  It's hilarious. It's infuriating.
• 37:00
  Michael Burry is an interesting guy.
• 37:02
  Burry I. Still follow quite.
• 37:03
  Literally did not see things the way everyone else sees it.
• 37:06
  Yeah. Literally has a different view
• 37:07
  in in a literal and figurative sense, but it's a fast pace to
• 37:11
  look at what happened when the experts are wrong and the people
• 37:13
  are willing to bet on the unthinkable, end up sort of
• 37:16
  winning it all. And my favorite part of the
• 37:17
  story, not to give it away, is when the guys from Goldman came
• 37:20
  to try to buy back his his side of the trade.
• 37:23
  They're like, we would love to pay you back on this.
• 37:25
  He was like, hard no. Of course, of course.
• 37:27
  Hard no. Like, what do you think I've
• 37:28
  been doing for the last whatever, five years?
• 37:30
  He was sitting on him, but I haven't seen the movie.
• 37:32
  According to Jeff, it's pretty good, but it's got the book.
• 37:34
  I can, I can I can strongly adore.
• 37:36
  So how about you? What have you seen?
• 37:37
  My wreck is 1995's Leaving Las Vegas, which just had a gorgeous
• 37:41
  4K. Oh cool, really beautiful.
• 37:43
  In the neon purgatory of the Strip, Ben Sanderson, played by
• 37:46
  Nicolas Cage, who won the Best Actor Oscar for it, isn't
• 37:48
  looking for a jackpot, he's looking for an exit.
• 37:51
  After torching his career and family, he heads to Las Vegas
• 37:54
  with a severance check and a singular goal, drinking himself
• 37:57
  to death alongside Sarah, played by Elizabeth Shue, who was
• 38:00
  nominated for an Oscar for it. A sex worker trapped in her own
• 38:02
  cycle of exploitation, this becomes the ultimate loser
• 38:06
  anthem. The film strips away the glitz
• 38:08
  to reveal the city's hollow core.
• 38:10
  There are no high stakes wins, only the the quiet mechanical
• 38:12
  rot of the 4:00 AM lifestyle where dignity is traded for a
• 38:15
  cheap high. Vegas acts as the perfect
• 38:17
  graveyard, a place designed to facilitate the total collapse of
• 38:20
  a human life. Such an amazing movie Leaving
• 38:23
  Las Vegas available on all the usual streamers.
• 38:26
  Now, I don't think I've ever seen the entirety of that film,
• 38:29
  just part. It's so good.
• 38:30
  Oh, it's so. Yeah.
• 38:31
  Nicolas Cage is amazing in this film.
• 38:32
  All right, I'm going to check that out.
• 38:33
  That is the episode. Thank you for joining us for all
• 38:35
  this nonsense. Truly terrible podcast from the
• 38:38
  awful company. This is on the web at nonsense
• 38:40
  dot productions. I'm little, I'm Jeff Parker.
• 38:42
  If you like this program, please follow down and subscribe and
• 38:44
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• 39:03
  Will be every Tuesday and Thursday morning and 32 bit
• 39:06
  float. For more nonsense, please join
• 39:07
  us. It's gross.
• 39:21
  What's gross? This whole thing, these markets,
• 39:23
  the way they came up, were you thinking?
• 39:24
  Generally, gambling markets came up in some way that was
• 39:27
  delightful.