The Golden Age of Prediction Markets: Polymarket Rages, Kalshi Arrives

From the 2024 US Presidential Election to the 2025 AI boom and sports events, prediction markets are exploding. Polymarket's trading volume surged over 300% during the election, with the on-chain "collective intelligence" pricing capability gaining unprecedented attention. According to Polymarket Analytics data, the cumulative trading volume of leading on-chain prediction markets has surpassed $1 billion, with nearly 30,000 markets created, covering diverse topics like 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 actively entering the space. These markets are attracting more users and capital, evolving beyond mere entertainment betting to become a new tool for information verification: when users put real money in, the prices themselves reflect the probabilistic judgments of collective intelligence.

This characteristic is particularly prominent in major events. For instance, in the 2024 US Presidential Election, Polymarket priced the probability of Trump's victory at 97% earlier than mainstream media; even when polls indicated a 50/50 chance for Trump and Harris, the market had already given its answer – over 60% probability for Trump's win. The capital staked transforms probabilities from abstract concepts into concrete, referenceable signals.

So, how do these markets actually operate? And how do on-chain prediction mechanisms differ from the traditional models we are familiar with?

What is On-chain Prediction Markets

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

Suppose there's a market for "Will the Federal Reserve cut interest rates in September?", with only two possible outcomes: "Yes, they will cut rates" and "No, they won't cut rates."

Bob believes the economy is weakening and a rate cut is highly probable, so he stakes $60 on "will cut rates." Alice and James, on the other hand, stake $20 and $12 respectively on "will not cut rates." In this scenario, a total of $92 is staked in the market, with $60 on "will cut rates" and $32 on "will not cut rates." On traditional platforms, users don't see "probabilities" directly, but rather "odds." For example, the platform might offer odds of 1.53x for "will cut rates" and 2.88x for "will not cut rates."

Behind these odds lies the probability derived from the capital distribution:

• "Will cut rates" ≈ $60 ÷ $92 ≈ 65%
• "Will not cut rates" ≈ $32 ÷ $92 ≈ 35%

The side with more staked capital has lower odds, yielding less return if victorious; the side with less staked capital has higher odds, promising greater returns if successful. For instance, if rates are indeed cut, the $60 staked capital will win $92, implying odds of about 1.53x; if rates are not cut, the $32 staked capital will win $92, implying odds of about 2.88x.

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

How Polymarket Brings Betting On-chain

Another core characteristic of traditional betting is its static and unidirectional nature. Once a bettor places a bet, their funds are locked until the event concludes and settles. This process is irreversible. Bettors cannot adjust their positions based on new information or evolving circumstances during the event. There is no secondary market allowing bettors to "sell" their wagers to lock in profits or mitigate losses prematurely. It is precisely to overcome this limitation that prediction markets have introduced core mechanisms from financial markets, achieving a paradigm shift from "betting" to "trading." We continue to use the example of the "Will the Federal Reserve cut interest rates in September 2025?" market to analyze the complete flow of capital.

Phase One: Market Creation

On Polymarket, anyone can permissionlessly create a prediction market. When a market is created, the smart contract automatically generates tradable shares corresponding to the event's outcomes, such as "Yes" and "No." The total supply of these shares is fixed, and the total value of each "Yes" and "No" share pair is 1 USDC. Market creators provide initial liquidity and receive corresponding shares, thereby determining the initial price.

Phase Two: Opening a Position

Suppose, in the initial market phase, the market believes there's a 40% probability of a rate cut: the "Yes" share price is 0.40. Alice believes the probability of a rate cut is underestimated, so she 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

Suppose an inflation report shows a larger-than-expected economic slowdown. The likelihood of a rate cut significantly increases, and the "Yes" share price rises to 0.75. Alice's held shares, initially worth $40, now are valued at $75, showing a floating profit of $35.

Phase Four: Closing a Position

Alice decides to sell her shares to lock in the $35 profit. Trader James believes a rate cut is a certainty and is willing to buy at a price of 0.75. Alice's sell order is matched with James's buy order. James pays $75 USDC directly to Alice. Alice's "Yes" shares are transferred to James.

Alice's $35 profit comes from the higher price paid by James. At this stage, no principal has been lost. Therefore, before settlement, a trader's profit comes from other traders. The money you earn is paid by those who buy your shares at a higher price, and the money you lose is the difference you pay to the buyer when you sell shares at a lower price.

Phase Five: Event Settlement

Suppose Alice and Bob hold their shares until the Federal Reserve meeting concludes. Outcome confirmation and fund distribution logic: The oracle confirms the final outcome. If "Yes" occurs, "Yes" shares are valued at $1.00, and "No" shares become worthless. Winners redeem their corresponding shares for the funds locked in the smart contract. Losers forfeit their staked principal.

For example, if the Federal Reserve announces a rate cut (the "Yes" outcome occurs), Alice will redeem her 100 "Yes" shares for $100 USDC. Alice makes a profit of $60, and Bob loses his entire $60. The $60 Alice earns is precisely the $60 Bob loses.

As can be seen, on-chain prediction markets like Polymarket are peer-to-peer (P2P), without a "house" found in traditional betting platforms. Funds flow entirely between participants, managed automatically and transparently by smart contracts. Trading profits arise from real-time changes in other traders' probabilistic judgments of an event, while settlement profits come directly from the principal staked by traders holding the opposing final view. The entire process achieves decentralized, trustless fund flow, offering crypto users a more open world of "staking."

Permissionless vs. Compliance: Why Kalshi Faces Scrutiny

Compared to Polymarket, Kalshi, another leading prediction market platform, recently garnered attention for hiring 23-year-old crypto influencer John Wang as its Head of Crypto. This appointment, around August 25, 2025, aims to expand its digital asset footprint. Upon announcement, Kalshi's investors, including members from Paradigm and Multicoin Capital, responded very positively to the appointment.

Kalshi is another major player in the prediction market space. In recent months, they completed a $100 million funding round at a $1 billion valuation, partnered with xAI to integrate Grok into their prediction market, and have a Trump family member serving as a strategic advisor. Kalshi is also the first fully CFTC-regulated event contracts market in the United States.

However, within the native crypto community, there are dissenting voices regarding Kalshi. Jordan, a member of research firm Delphi Digital, pointed out that Kalshi's centralized structure is unsuitable for promotion as a crypto project. Niko, a Uniswap team member, also stated that Kalshi's previous actions during the election, where they allegedly damaged Polymarket's reputation and operations by spreading negative information, should not be condoned.

Despite some controversy surrounding Kalshi within the community, data suggests it has become one of Polymarket's main competitors, and its future development should not be underestimated.

End

On-chain prediction markets not only break the static limitations of traditional betting, achieving a paradigm shift from "betting" to "trading" by introducing financial trading mechanisms, but also demonstrate strong vitality through their transparent and decentralized nature.

As their mechanisms mature and platforms like Polymarket and Kalshi continue to develop, on-chain prediction markets are becoming an unstoppable force and an important tool for future information pricing and risk hedging.

Disclaimer: This content is for educational purposes only and does not constitute financial advice. DeFi protocols carry significant market and technical risks. Token prices and yields are highly volatile, and participating in DeFi may result in the loss of all invested capital. Always do your own research, understand the legal requirements in your jurisdiction, and evaluate risks carefully before getting involved.