Original Title: "The Golden Age of Prediction Markets: Polymarket Craze, Kalshi Emergence"

Original Source: OneKey Chinese

From the 2024 US presidential election to the 2025 AI boom and sports events, prediction markets are on fire. Polymarket's trading volume surged by over 300% during the election, and the on-chain "collective wisdom" pricing ability has never been more prominent. According to Polymarket Analytics data, the cumulative trading volume of top on-chain prediction markets has surpassed $1 billion, with nearly 30,000 established markets covering various topics such as politics, technology, sports, and crypto.

Why now? On-chain prediction markets are more transparent, secure, and censorship-resistant than traditional platforms; coupled with loosening US regulations, players like Coinbase and Kalshi are joining the game. These markets are attracting an increasing number of users and funds, evolving from mere entertainment betting to a new tool for information validation: when users bet real money, the price itself reflects the probability judgment under collective wisdom.

This feature is particularly prominent in major events. For example, in the 2024 US presidential election, Polymarket priced Trump's winning probability at 97% earlier than mainstream media; even when polls showed a "50-50" split, the market had already indicated over 60% inclination. Betting funds make probability more than just talk but a signal worth considering.

So, how do these markets operate? What are the differences between the on-chain prediction mechanism and the traditional model we are familiar with?

"Fundamental Mechanism of On-Chain Prediction Markets"

To understand on-chain prediction markets, let's first review how users make a "bet" in a traditional prediction market.

Let's say there is a market for the event "Will the Fed cut interest rates in September," with only two outcomes: "cut" and "not cut."

Bob believes the economy is weakening, with a high probability of a rate cut, so he bets $60 on "cut"; Alice and James then respectively put in $20 and $12 on "not cut." In this case, there is a total of $92 wagered in the market, with $60 on "cut" and $32 on "not cut." On traditional platforms, users do not see the so-called "probability" but rather odds. For example, the platform may offer odds of 1.53x for "cut" and 2.88x for "not cut."

Behind the odds is actually a probability derived from the distribution of funds:
> "Will cut interest rates" ≈ 60 ÷ 92 ≈ 65%
> "Will not cut interest rates" ≈ 32 ÷ 92 ≈ 35%

The side with more bets has lower odds, resulting in a smaller return upon winning, while the side with fewer bets has higher odds, leading to a more generous return upon winning. For example, if the interest rate is indeed cut, betting $60 would result in a share of $92, with odds of approximately 1.53x; if the interest rate is not cut, betting $32 would result in a share of $92, with odds of approximately 2.88x.

This is the operational logic of traditional prediction markets: user bets drive odds changes, and the odds implicitly reflect the market's expected probability of the event outcome.

"How Polymarket Moved Betting onto the Blockchain"

Another core feature of traditional betting is the static and one-way nature of its transactions. Once a bet is placed, the funds are locked until the event is settled upon completion. This process is irreversible. Bettors cannot adjust their positions during the event based on new information or changes in circumstances. There is no secondary market allowing bettors to "sell" their bets to lock in profits or minimize losses ahead of time. To break free from this limitation, prediction markets have introduced core mechanisms of financial markets, enabling a paradigm shift from "betting" to "trading." We'll continue using the example of "Will the Fed cut interest rates in September 2025?" to analyze the complete flow of funds.

Stage One: Market Creation

On Polymarket, anyone can permissionlessly create a prediction market. When a market is created, a smart contract automatically generates tradable shares corresponding to event outcomes, such as "Yes" and "No." The total supply of these shares is fixed, with the total value of each "Yes" and "No" share being 1 USDC. The market creator provides initial liquidity and receives corresponding shares to establish the initial price.

Stage Two: Opening Positions

Assume that initially, the market believes the probability of a rate cut is 40%: the price of a "Yes" share is 0.40. Alice believes the probability of a rate cut is underestimated and buys 100 "Yes" shares at a price of 0.40, spending $40 USDC. Alice's counterparty is Bob, who sells 100 "Yes" shares (or buys 100 "No" shares). Alice's $40 and Bob's $60 are locked in the smart contract as collateral. Alice receives 100 "Yes" shares, and Bob receives 100 "No" shares.

Phase Three: Market Volatility

Assuming the inflation report shows a more-than-expected economic slowdown. The likelihood of a rate cut increases, and the "Yes" share price rises to 0.75. Alice's share value increases from $40 to $75, resulting in a $35 unrealized gain.

Phase Four: Closing Position

Alice decides to sell her share to lock in a $35 profit. Trader James believes a rate cut is a sure thing and is willing to buy at a price of 0.75. Alice's sell order matches James's buy order, and the transaction executes. James pays $75 USDC directly to Alice. Alice's "Yes" share is transferred to James.

Alice's $35 profit comes from James paying a higher price. At this stage, there is no principal loss. Therefore, at settlement, a trader's profit comes from other traders, with the money you make being what the person who bought your share at a higher price pays and the money you lose being the difference paid to the taker when the share is sold at a lower price.

Phase Five: Event Settlement

Assuming Alice and Bob hold their shares until the end of the Fed meeting. The outcome is confirmed along with fund distribution logic: the oracle verifies the final result. If the "Yes" outcome occurs, the "Yes" share is valued at $1.00, and the "No" share is valued at zero. The winner redeems their respective shares for the funds locked in the smart contract. The loser forfeits their initial investment.

For instance, if the Fed announces a rate cut, and the "Yes" outcome happens, Alice redeems 100 "Yes" shares for $100 USDC. Alice profits $60, while Bob loses his entire $60. The $60 Alice gains is exactly the $60 Bob loses.

It is evident that on-chain prediction markets like Polymarket are peer-to-peer, lacking a traditional "house." Fund flows occur entirely between participants and are automatically and transparently managed by smart contracts. Trading profits stem from real-time shifts in other traders' event probability assessments, and settlement gains come directly from the capital invested by traders holding the opposing final view. The entire process achieves decentralized, trustless fund transfers, offering crypto users a more open world of "betting."

More importantly, when you are predicting the future, you are not just talking: you are betting with real money. This feature can be crucial for significant events. Fundamentally, the larger the total amount wagered, the more indicative the probability's realized results become, aligning more closely with the actual outcome.

Therefore, when you want to assess the truth of a piece of news, tracking prediction market probability changes can be very helpful. A prime example is last year's U.S. presidential election event. DragonFly partner Haseeb pointed out in a tweet analysis that the world's largest prediction market, Polymarket, had made a call well before mainstream news media, declaring a 97% chance of a Trump victory by midnight Eastern Time. Not only that, even before the polling models indicated a toss-up between Trump and Harris, Polymarket had already given its answer—Trump's probability of winning was over 60%.

The on-chain prediction market is no longer just a gambling platform: through blockchain technology and financial means, it is expected to become a new generation of information dissemination and validation channel.

「On-Chain vs Compliance, Why Kalshi Is Criticized」

Compared to Polymarket, another prediction market Kalshi recently sparked controversy by appointing 23-year-old crypto influencer John Wang as its Crypto Lead around August 25, 2025, to expand into the digital asset space. Upon the announcement, Kalshi's investors, including members of Paradigm and Multicoin Capital, responded very positively to this appointment.

Kalshi is another leader in the on-chain prediction market. In the past few months, they have achieved a $1 billion valuation, raised $100 million, partnered with xAI to introduce Grok to the prediction market, had a Trump family member as their strategic advisor... Meanwhile, Kalshi is also the first event derivative market fully regulated by the CFTC (Commodity Futures Trading Commission) in the United States.

However, there are some opposing voices within the native crypto community regarding Kalshi: Delphi Digital research team member Jordan pointed out that Kalshi's centralized structure is not suitable for crypto project promotion; Uniswap team member Niko also stated that Kalshi's previous actions during the election period spreading negative information to harm Polymarket's reputation and operations should not be respected.

Although there is some controversy within the community regarding Kalshi, from a data perspective, it has already become one of Polymarket's main competitors, and its future development should not be ignored.

「End」

The on-chain prediction market has not only broken the static limitations of traditional gambling but has also achieved a paradigm shift from "betting" to "trading" by introducing financial transaction mechanisms. With its transparent, decentralized nature, it has demonstrated strong vitality.

As its mechanisms mature and platforms like Polymarket and Kalshi continue to develop, the on-chain prediction market is moving forward irresistibly, becoming a significant force in future information pricing and risk hedging.

Disclaimer: The content of this article is for informational and educational purposes only and does not constitute any investment advice or financial advice; DeFi protocols involve high market risks and technical risks, and digital asset prices and returns are highly volatile. Participation in digital asset investment and DeFi protocols may result in losing the entire investment amount; readers should, before participating in any DeFi protocols, understand and comply with relevant local laws and regulations, conduct risk assessments and due diligence, and make decisions carefully.

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