For a long time, we have understood prediction markets as a very “rational” thing: people bet on the future based on public information, and market prices reflect consensus. But over the past year, we have increasingly realized one thing: many prediction markets are not “predicting the future” but rather exposing “results already known to a few” in advance.
When an outcome is already determined but not yet public, prediction markets become an extremely brutal thing: they don’t require leaks, anonymous letters, or even a single word. The direction of capital itself is the leak.
Prediction markets are changing the way “secrets” exist:
Imagine a few scenarios:
· A hit TV series has finished filming—will the main character die or not?
· The judging process for a gaming award has basically concluded, but the results haven’t been announced
· An AI company is about to release a key product or announce merger and acquisition news
· Regulatory outcomes, exchange listing timing, or governance vote trends for a certain Crypto protocol
In the traditional world, these are called “insider information.” But after the emergence of prediction markets, they face a new problem: as long as someone knows and can place bets, secrets are hard to avoid being captured by the market. You don’t need to know “who said what”; you just need to observe:
· Which options are unusually heavily weighted
· Which addresses consistently place bets during key time periods
· Which accounts repeatedly “bet correctly in advance” in similar events
This isn’t conspiracy theory; it’s the natural outcome of probability and incentives.
From “content reporting” to “result stress testing”
This is also why we’ve started to reflect on traditional news models. The past content logic was: event occurs → a few people know → reporting (release) → the public knows
Prediction markets bring another path: event occurs → someone knows → someone places a bet → prices start to deviate → the world already “knows in advance”
There’s even an more extreme path: event occurs → someone knows → someone places a bet → prices start to deviate → causing the event to change
Regarding this path, I can give a classic example: at the end of Coinbase’s (NASDAQ: COIN) Q3 2025 earnings call, CEO Brian Armstrong said something that seemed casual:
“I’m kind of fascinated by a prediction market. I’m tracking a prediction market betting on what we’ll say on this earnings call… So I have to say these words before the call ends: Bitcoin, Ethereum, blockchain, staking, and Web3.”
These words weren’t random; they were what people bet on in prediction markets regarding whether certain words would appear in this call. After Armstrong said this, the related prediction markets immediately settled, and bettors who wagered on these words being spoken made profits. According to reports, around $80,000 in bets across markets like Kalshi and Polymarket were instantly settled.
In other words, without these bets, in another parallel world, Brian Armstrong would have just completed the earnings call normally without deliberately saying these words. This is the “reality distortion field” of prediction markets; betting itself has the power to change reality, which is common in sports betting where outcomes often skew toward the least bet option due to insider manipulation. But whether it’s words in a Coinbase earnings call or a soccer match, after all, they don’t greatly impact our world. However, as Polymarket and Kalshi grow, the topics on them will get closer to our lives, and this “reality distortion field” of prediction markets will genuinely affect our lives.
In the future world, content will no longer be the starting point of information but a tool for verification and explanation; in extreme cases, content can even change reality. This is what BlockBeats’ prediction market reporting is doing: it’s not a “prediction market navigation site” nor simply recounting what happens on Polymarket or Kalshi.
What we truly care about are three things:
· Which events’ odds changes don’t seem driven by sentiment or public information?
· Are there addresses that consistently heavily bet “before results” with abnormally high historical hit rates?
· Do these behaviors point to some “known but not public” fact?
We analyze:
· Topics and option odds in prediction markets
· Bettors’ on-chain addresses and related behaviors
· Similar betting patterns in historical events
To do one thing: treat prediction markets as a “secret stress tester,” not an opinion voting box.
Currently, our key focus areas include:
· Macro policy trends and geopolitics that can impact capital markets
· AI industry: product release timing, mergers and acquisitions, key personnel changes
· Crypto industry: TGE, regulation, governance outcomes, major protocol changes
The future of the content industry:
The real challenge of prediction markets isn’t accuracy, but that they are dismantling an order long assumed by the content industry and regulators: only information allowed to be spoken becomes “public knowledge.” When everything can be bet on, secrets are no longer constrained solely by systems, professional ethics, or news blackouts but must continuously confront price discovery mechanisms.
In mild scenarios, this means TV series endings, award outcomes, and business decisions will be known in advance by the market; in extreme scenarios, it even touches war and geopolitical conflicts: people can learn “military intelligence”-level information through bets by soldiers on the front lines, directly influencing the course of war. When outcomes are already known to a few, and the market allows betting on them, price itself can become an undeniable signal of reality.
My first sense of awe toward the financial industry came in college when I read a small story: Bridgewater founder Ray Dalio, early in his career, helped McDonald’s hedge chicken futures; in the US, large restaurant chains almost always simultaneously configure futures hedging for their core raw materials to withstand sharp price cycle fluctuations, ensuring consumers can eat quality-stable, price-controlled McNuggets anytime. What awed me wasn’t Dalio’s later achievements but the first clear realization: the original purpose of financial markets was never trading itself but to make the real world operate more stably and predictably.
Futures markets help people hedge commodity price risks; stock markets help socially valuable companies finance and develop more efficiently; in this process, traders and speculators provide liquidity, farmers lock in future earnings early, and companies gain stable cost structures. While market participants each take what they need, overall it’s a long-term positive EV system.
This brings us back to a more fundamental question: with massive speculative liquidity like Polymarket already existing, can we guide it toward more truly positive EV directions? If an event, once it occurs, significantly impacts personal lives, assets, or decisions, can we leverage prediction market liquidity, even evolving a product form akin to “event insurance” through multiple market combinations, like “flight delay insurance” in our lives today—it may not compensate for flight delay losses but offers some psychological comfort.
Prediction markets aren’t challenging any single media outlet but forcing a bigger question: when the world starts being bet on, who still has the power to decide “what can be known?” and “when can it be known?” We will continue exploring this path. Additionally, the BlockBeats prediction market analysis team has now been established. If you also love content and are curious about prediction markets, you’re welcome to join anytime. (Resumes can be sent to [email protected] or HR Telegram @Jhy10vewh0 with note “prediction market”) We also welcome prediction market and AI-related startup teams to discuss with us. BlockBeats will do its best to provide maximum exposure to excellent startups. Contact email: [email protected]
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