[00:00] Prediction markets are rigged. You're

[00:02] betting against insiders. Don't touch

[00:04] them. If you spent any time online

[00:06] lately, you've seen that narrative

[00:08] everywhere. And I get it. On the

[00:10] surface, it can look sketchy. New

[00:12] platforms, new types of markets,

[00:15] headlines about information, moving

[00:17] prices. So, today I want to slow this

[00:19] conversation down a bit. I'm going to

[00:21] walk you through how I actually approach

[00:24] prediction markets as a professional

[00:25] better, when I'll trade them, when I

[00:28] won't, and how you can think about them

[00:30] intelligently instead of emotionally.

[00:33] For those of you who are new here, I'm

[00:34] Rob Pizzola. I'm a professional sports

[00:35] better, and this is circles off.

[00:39] Here we go. This episode is presented by

[00:43] Kshi. And before we go any further, let

[00:46] me just address the obvious. Yes, we

[00:48] monetize circles off through

[00:49] partnerships with operators. That's how

[00:52] this business works. We've partnered

[00:54] with sports books, exchanges, and now a

[00:56] prediction market. And I know how that

[00:58] looks. But this is not going to be an

[01:00] infomercial. I'm not here to tell you

[01:03] that every market is safe. I'm not here

[01:06] to tell you to blindly trade anything.

[01:08] What I do believe is this. Prediction

[01:11] markets are not going away. If anything,

[01:14] right now, they're growing. The space is

[01:17] evolving very quickly and as bettererss

[01:20] you can either ignore that or you can

[01:22] learn how to navigate it intelligently.

[01:25] So this video isn't about hype. It's

[01:27] about understanding what game you're

[01:29] playing before you put your money into

[01:31] it. Because when it comes to prediction

[01:33] markets, the real question isn't are

[01:36] they rigged. The real question is do you

[01:39] understand the structure of the market

[01:41] that you're entering? Let's break that

[01:43] down. Before we even talk about

[01:44] prediction markets, let's start with

[01:46] something uncomfortable. The playing

[01:48] field in betting has never been

[01:51] perfectly level anywhere. Not at

[01:54] traditional sports books, not in

[01:56] exchanges, not in DFS back in the day,

[01:59] nowhere. Now, to be clear, I'm not one

[02:02] of those people who thinks that sports

[02:04] are scripted or rigged. In general,

[02:07] professional sports are legitimate

[02:09] competitions. outcomes, in my opinion,

[02:11] are not secretly predetermined. But

[02:14] information asymmetry, that absolutely

[02:16] exists. Injuries leaked before they're

[02:19] officially announced. Lineup changes,

[02:21] they get whispered around. Beat

[02:23] reporters tweet something subtle and the

[02:25] market moves before most people even see

[02:27] it. Sometimes the market just reacts

[02:30] faster than the public can. And

[02:32] sometimes the edge isn't even about an

[02:35] injury. years ago when the Vegas Golden

[02:38] Knights entered the NHL, they were

[02:40] phenomenal at home early in their

[02:42] inaugural season. And I had friends who

[02:44] worked in the nightlife industry in

[02:45] Vegas. Every now and then I'd get a text

[02:48] said, "Hey, a bunch of players from so

[02:51] and so team, the visiting team are out

[02:53] at a club right now. It's 3:30 in the

[02:55] morning." Now, is that guaranteed to

[02:56] matter? No. But is that information that

[03:00] not everyone else betting into the same

[03:02] market had? Yes, it is. And that's the

[03:04] reality of betting. Sometimes you react

[03:07] faster to public information. Sometimes

[03:10] you're closer to a source. Sometimes you

[03:13] just notice something others don't. The

[03:15] point is not that sports books are

[03:17] corrupt. The point is that the playing

[03:20] field, it's never perfectly flat. None

[03:23] of that is unique to prediction markets.

[03:26] Information, speed, access, awareness,

[03:30] that has always been part of this game.

[03:32] So when people say don't touch these

[03:35] prediction markets, insiders will crush

[03:37] you. My response is very simple. That

[03:40] dynamic already exists everywhere else.

[03:43] So what actually is a prediction market?

[03:45] Let's strip this down to the basics. In

[03:48] a traditional sports book, the structure

[03:50] is very simple. The house sets a price.

[03:52] You bet into it. The house takes the

[03:54] other side of your wager. Yes, the book

[03:57] might try to balance action. They manage

[04:00] risk, but at the end of the day, you're

[04:03] betting into the sports book. They are

[04:05] the counterparty. Now, you compare that

[04:07] to a prediction market. Instead of

[04:09] betting against a house, you're trading

[04:12] contracts. A contract represents an

[04:15] outcome, something that either happens

[04:18] or doesn't happen. The price of that

[04:21] contract reflects the market's implied

[04:23] probability. So, something is trading at

[04:26] 60 cents. as an example, the market is

[04:28] saying there's roughly a 60% chance that

[04:31] it occurs. But here's the key

[04:33] difference. You're not betting against a

[04:35] centralized bookmaker. You're trading

[04:37] against other participants, other

[04:39] traders, other bettors, other people

[04:42] expressing their probability through

[04:44] price. The platform facilitates the

[04:48] market, but the price is largely

[04:50] determined by supply and demand. And on

[04:52] the surface, that sounds cleaner, more

[04:54] efficient, or or more pure. But here's

[04:57] where things get interesting. Let's talk

[04:59] specifically about sports markets on

[05:02] prediction platforms. Let's say there's

[05:05] a college basketball game, I don't know,

[05:07] Iowa versus Wisconsin. If you're trading

[05:10] that game on a prediction market instead

[05:12] of betting it at a traditional sports

[05:14] book, what has actually changed? The

[05:18] answer, not much. The underlying risk is

[05:22] the same. The ball still gets tipped.

[05:24] The game still plays out. Injuries still

[05:27] matter. Matchups still matter. The

[05:29] outcome is still determined on the

[05:32] court. You're still trying to assign a

[05:34] probability to an event that hasn't

[05:36] happened yet. That part has not changed.

[05:40] Take the NFL draft as another example.

[05:42] Draft markets move aggressively on

[05:45] information. They always have. A player

[05:47] might open up at plus money to go third

[05:50] overall. Then a report comes out and

[05:52] then a mock draft and then another

[05:54] report and then sharp money hits the

[05:56] market. And by draft night, that same

[05:59] player that was an underdog might be

[06:01] sitting at minus 10,000. Does that mean

[06:04] that the market is corrupt? No, it

[06:07] doesn't. It means information entered

[06:10] the market. And that already happens at

[06:13] traditional sports books. Lines move on

[06:15] injury leaks. They move sometimes on

[06:18] insider reporting. They move on

[06:20] whispers. They move on sharp action.

[06:22] Information driven movement is not new.

[06:26] So when you're trading a sports market

[06:29] on a prediction platform, you're not

[06:31] suddenly entering some brand new

[06:34] dangerous ecosystem. You're still

[06:36] operating in a world where price reacts

[06:38] to information. That's always been the

[06:40] game. Now, this is where we get into the

[06:43] nuanced part of things because there are

[06:45] markets where information risk is very

[06:48] real. Let's use a reality TV example. I

[06:51] I won't spoil anything here for anyone,

[06:53] but there's a a market up right now on

[06:56] who will win an upcoming season of

[06:58] Survivor, season 50. Now, from what I

[07:01] understand, this season will have a live

[07:04] finale. So, technically, the winner

[07:07] isn't publicly known yet. But here's the

[07:09] important detail. The season itself has

[07:12] already been filmed. The final three

[07:14] contestants are already known. All the

[07:16] votes have already been cast. Which

[07:20] means somewhere a group of people

[07:23] already know who they voted for. That

[07:26] information exists. There's roughly $3

[07:30] million in volume traded on this market

[07:32] right now. and one contestant has been

[07:35] sitting around 75% probability and that

[07:39] price moved almost immediately after the

[07:41] market opened. Now again, I'm not

[07:44] accusing anyone of anything, but this is

[07:46] where you have to pause and you have to

[07:48] slow down because before I trade

[07:50] anything, I ask myself one question, one

[07:54] very specific question. Is this a

[07:56] probability market or is this an

[07:58] information market? If I'm betting a

[08:01] basketball game, that's a probability

[08:03] market. the outcome hasn't happened yet.

[08:04] We're all forecasting. But if I'm

[08:06] trading something where key information

[08:09] is already determined somewhere behind

[08:11] the scenes, even if it hasn't been

[08:13] revealed publicly, that changes the

[08:16] dynamic. If votes have already been

[08:18] cast, if finalists are already locked

[08:21] in, if the chart shows a massive spike

[08:24] the moment the market opens, that

[08:26] signals danger to me. If you see

[08:28] millions in volume and one side is

[08:31] heavily skewed almost instantly, that's

[08:33] danger because at that point you might

[08:36] not be forecasting better than the

[08:38] crowd. You might be stepping into a room

[08:40] where some people already know how the

[08:42] story ends. But here's the important

[08:44] distinction.

[08:46] That's not prediction markets are bad.

[08:48] That's don't walk into an information

[08:51] war unarmed. You don't have to trade

[08:54] every market that exists. Part of being

[08:57] a smart better is recognizing when the

[09:00] game you think you're playing isn't

[09:02] actually the game that's being played.

[09:05] Now, let's contrast that with something

[09:08] completely different.

[09:10] Take a market like what will be the

[09:13] highest temperature in New York City

[09:15] today available on Kali right now or

[09:18] Miami or Los Angeles. climate related

[09:21] metrics. Even a market like annual

[09:25] measles cases,

[09:27] these are very different animals. Some

[09:30] markets are just forecasting exercises.

[09:33] There's no secret room where somebody

[09:36] already knows the answer. There's no

[09:38] group of insiders who cast votes weeks

[09:41] ago. There's no executive memo sitting

[09:44] in someone's inbox. It's just

[09:45] probability.

[09:47] weather models,

[09:49] epidemiology projections, trend

[09:52] analysis, public data. Now, sure,

[09:55] someone might have a better model than

[09:56] you, someone might be faster, someone

[09:59] might be smarter, but that's skill

[10:01] asymmetry, not information asymmetry.

[10:05] There's also typically very little

[10:07] incentive to manipulate something like

[10:10] that. The volume on these markets aren't

[10:12] massive. The real world outcome is hard,

[10:16] if not impossible, to influence. You're

[10:19] not changing the temperature in New York

[10:21] to win a contract. You're not

[10:23] meaningfully moving nationwide measles

[10:26] numbers because you want to profit

[10:29] $400,000

[10:30] on a market. So, those markets are are

[10:33] fundamentally different from something

[10:36] like a pre-recorded TV outcome. Now,

[10:39] let's use a corporate example. You might

[10:41] see a market like will Tesla release a

[10:45] new model this year. When that market

[10:48] first opens, it may look completely

[10:50] normal, balanced trading, gradual price

[10:54] movement, just people forecasting based

[10:57] on public information. Then one day you

[10:59] see a sharp spike, big volume hits, the

[11:02] price jumps aggressively in one

[11:03] direction. That's your signal. That's

[11:06] when you pause because maybe news is

[11:08] about to break. Maybe something

[11:10] internally uh maybe someone internally

[11:13] already knows something. Maybe the

[11:15] market just shifted from probabilistic

[11:18] to informational. And this is the key

[11:20] lesson. Every market has some sort of

[11:23] life cycle. Some start tradeable and

[11:26] they end compromised. Early in the life

[11:29] cycle, it might be a forecasting

[11:31] exercise. Later in the life life cycle,

[11:33] it might become an information battle.

[11:35] Your job isn't to trade everything. Your

[11:38] job is to recognize which stage you're

[11:40] in. There's another concept that matters

[11:43] here as well. The counterparty.

[11:46] Let's go back to a sports example for a

[11:48] second. When I was betting NHL at at a

[11:51] high level, there were days where I'd

[11:54] identify a number that I loved, big

[11:56] edge. I'd hit it hard. The line would

[11:59] move immediately in my direction. I had

[12:01] market impact. Great. But then later in

[12:03] the day, boom, it gets smashed right

[12:06] back the other way. right in my face.

[12:08] Big money, aggressive movement into

[12:10] bigger limits all the way back to my

[12:13] original number. And at that point, I'm

[12:17] not emotional. I'm not defensive. I'm

[12:19] just asking myself a couple of

[12:21] questions. Who is on the other side? And

[12:25] what do they know? Because if someone is

[12:28] willing to move serious money into the

[12:30] market against me, I have to respect

[12:32] that. Maybe they know about, you know, a

[12:35] flu bug in the locker room. Maybe a a

[12:38] goalie injury or lineup change that

[12:41] hasn't been reported.

[12:43] Maybe they just disagree with my number.

[12:46] But that internal dialogue is part of

[12:48] being a professional better. And that

[12:51] question, who is my counterparty and

[12:54] what do they know, exists everywhere in

[12:57] betting,

[12:59] sports books, exchanges,

[13:02] DFS, prediction markets. This is not

[13:05] some unique danger that only exists on

[13:08] new platforms. It's the same fundamental

[13:12] dynamic. You are always trading against

[13:15] someone.

[13:17] The only question is whether you're

[13:19] aware of that and whether you're

[13:21] prepared for it. So the real question

[13:24] becomes should you bet prediction

[13:26] markets? My answer is not yes to

[13:30] everything and it's definitely not stay

[13:33] away from all of this stuff. It's this.

[13:37] Don't blindly trade everything. Evaluate

[13:41] the structure. Look at the volume. Look

[13:44] at the price history. Look at how the

[13:46] market behaved when it first opened. Did

[13:49] it move gradually over time as

[13:52] information became public or did it

[13:54] spike aggressively in the early going?

[13:57] Ask yourself, is this still a

[13:59] probabilistic market or has it turned

[14:02] into an information market? If it's a

[14:05] basketball game, a weather forecast, a

[14:08] macroeconomic metric, you're probably

[14:11] just forecasting. If it's a pre-recorded

[14:14] event, a closed-d dooror vote, a

[14:16] corporate announcement that insiders

[14:18] might already know about, you need to

[14:20] tread carefully. This isn't complicated.

[14:23] You don't need some advanced degree in

[14:25] market structure. You just need to slow

[14:27] down and you need to observe because 99%

[14:31] of the time, you can tell whether you're

[14:33] walking into a forecasting exercise or

[14:36] an information battle. And if you feel

[14:38] like it's the latter, in my opinion,

[14:40] move on. there's always another market.

[14:43] The edge in betting isn't just about

[14:45] picking winners. It's about choosing the

[14:47] right games to play in the first place.

[14:50] Now, as I mentioned at the top, this

[14:52] episode is presented by Cali. And again,

[14:54] I want to be transparent about that. We

[14:57] monetize circles off through

[14:59] partnerships with operators. That's how

[15:01] this channel exists. That's how we fund

[15:03] the content and the production. But

[15:06] sponsorship doesn't mean blind

[15:08] endorsement. If you're going to explore

[15:11] prediction markets, whether it's on Kali

[15:14] or anywhere else, do it intelligently.

[15:17] Don't trade something just because it

[15:20] exists. Look at the order book. Look at

[15:22] the chart. Look at how the market

[15:24] behaved when it opened. Think about the

[15:27] structure. Be smart about it. Ask

[15:29] yourself whether you're forecasting or

[15:31] whether you're stepping into an

[15:33] information battle. There are markets on

[15:36] there that are thoughtful. They're

[15:38] interesting forecasting exercises. There

[15:41] are others you might decide to pass on.

[15:44] That's that's all part of being a

[15:46] disciplined better. If you want to check

[15:48] out the types of markets I've been

[15:49] referencing, you can use the link in the

[15:51] description below. Just make sure you

[15:52] approach it the same way you should

[15:54] approach anything else in this space

[15:57] with skepticism, with structure, and

[16:01] most importantly, with discipline. I'm

[16:03] genuinely curious what you guys think

[16:05] about this. Drop a comment below. What

[16:07] types of prediction markets would you

[16:09] never touch? And on the flip side, what

[16:11] markets do you think are completely fair

[16:13] for forecasting exercises? Let's

[16:15] actually have a thoughtful discussion

[16:16] about it instead of just yelling, you

[16:18] know, rigged at everything that's new.

[16:21] If you enjoyed this breakdown and if you

[16:23] want more of this content, deeper dives

[16:26] into stuff like market structure, edge,

[16:28] information risk, all of that, make sure

[16:30] you hit like, make sure you subscribe to

[16:32] the channel. There's a lot more coming

[16:35] on this channel. I might even do a

[16:36] future episode where I pull up a few

[16:39] specific live markets, walk through some

[16:41] of this stuff in real time, how I

[16:43] analyze them, what I'm looking at, what

[16:46] I'm avoiding, and and why I'm avoiding

[16:49] it if I am. Appreciate you watching, and

[16:51] as always, think before you bet.