Since the publication of "Where Should Chinese Prediction Markets Explore?", prediction markets have gained global prominence and truly entered the mainstream. Similar to Bitcoin and stablecoins, once crypto products achieve Product-Market Fit (PMF), they are recognized by the market as a new sector and receive sustained capital injection.
Thanks to the natural platform monopoly effect of prediction markets, providing peripheral services around them has become a consensus within the circle, aiming to cultivate them as a natural incubator for capturing ecosystems outside the circle, thereby building a hierarchical ecosystem of core—periphery—outer layer.
After outlining the basic landscape and direction of prediction markets in the previous article, let us attempt to analyze their peripheral services. Beyond clones, tools, and rebates, what other directions can support high-market-value peripheral business models?
Premature Prediction Markets
The world may end, but progress marches on.
Prediction markets are markets with strong certainty amidst uncertainty. For events like the World Cup's dates and participating teams, or the U.S. midterm elections and presidential election, the pre-determined participants and basic dates and rules are highly controllable.
However, the World Cup's winning team cannot be pre-determined—otherwise, it would be rigged. Thus, it becomes an uncertain information game that evolves with the continuous addition of current information factors.
For example, during the 2024 U.S. presidential election, a significant number of bets were placed within the five days leading up to the expiration date. In on-chain transactions, users' bullish or bearish sentiments directly impact the long-short markets, converging into self-fulfilling prophecies.
Current prediction markets are developing in this direction. For instance, Coinbase's CEO noticed that people were predicting his statements and thus "cooperated" to align with the final outcome.
Image Caption: Predictions require data. Image Source: https://brier.fyi/
Before prediction markets, opinion polls and media played such roles. It was not that polls tested voters' tendencies but that polls guided people's choices. Thus, in a Western context, prediction markets are seen as information tools, with additional functions like insurance, hedging, and taxation layered on top.
Therefore, prediction markets are far more sensitive than trading tools. Just as TikTok faced bipartisan scrutiny not for being a "pacifier," prediction markets inherently cannot be fragmented:
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Information discovery requires博弈 based on real-time, accurate data to improve final accuracy. Information drives traffic to become more concentrated.
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The U.S. election market is highly mature. Only a Western context can achieve a relationship of "conflict without breakdown" with the political system, becoming a new information channel.
Based on this, Polymarket and Kalshi are "born mature" information hubs. This is also why U.S. capital continues to invest and drive up their valuations, rather than employing a horse-racing mechanism like Binance.
Of course, all this has little to do with us. What matters to us is how to ride the wave of the prediction market FOMO.
Image Caption: Prediction market periphery. Image Source: @zuoyeweb3
Overall, the market has evolved four models:
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Clone platforms outside Polymarket and Kalshi require Perp DEX-level investment and subsequent high compliance costs for the U.S. market. They will largely become TGE tracks with almost no real adoption rate.
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Asset-layer innovation for existing prediction platforms:
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DeFi-izing the betting assets on prediction markets. For example, Gondor allows them to be used as collateral for lending, and Space adds 10x leverage to them. Essentially, this is violently injecting DeFi factors.
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Innovative asset prediction markets like 42 Space, which generate prediction topics directly based on social media information flows, attempt to compete differently with existing platforms.
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Mainstream Web3/2 financial trading Super Apps like Coinbase/Robinhood, complementing their own transaction types.
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Tools customized for specific groups or needs in prediction markets, such as high-frequency trading, multi-platform arbitrage trading, or aggregated trading terminals, LP mining, or paid group tools, as well as prediction market data and information aggregation analysis platforms.
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KOL and rebate platforms, such as Based and Phantom wallet and other mobile trading platforms, as well as various social fission rebate KOLs or communities.
Among the above paradigms, the core prediction market requires excessive investment and, due to political considerations, almost offers no high-valuation prospects for new players. Secondly, tools and rebates will be cyclical, fluctuating with the capital investment and hot topics in prediction markets.
The only area worthy of business investment is the DeFi-ization of prediction platform assets. While waiting for results, the betting assets remain idle. This might be the most noteworthy high-quality asset for DeFi.
Win-Win-Win Cross-Market Arbitrage Mechanism
Use the Taobao traffic station approach to do DeFi, not the DeFi approach to do DeFi.
Providing traffic services to giants has always been like dancing on a knife's edge. On one hand, giants need third parties to boost platform traffic. On the other hand, giants do not want third parties to develop brand effects.
This was the dilemma of early e-commerce traffic stations. They had to maintain good relationships with the platform, sellers, and buyers. Sellers needed third-party traffic stations to enhance competitiveness; buyers wanted discounted prices.
Image Caption: Third-party services. Image Source: @zuoyeweb3
Traffic stations start with rebates. The platform develops corresponding sharing/purchase/rebate tools. As long as the natural traffic sellers gain from exposure outweighs the promotional discounts, the entire business can operate sustainably.
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Sellers need to rely on the platform to承接 natural traffic; self-operated brands and channels are too costly.
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Buyers need the platform for after-sales and rights protection; the payment process also requires platform guarantees.
Referring to the e-commerce platform battle among Taobao—JD.com—Pinduoduo, the market for new e-commerce platforms is overly narrow. The e-commerce market inherently requires a dual structure of "brand merchants + long-tail traffic." Newcomers capturing brand merchants or focusing on niche markets cannot achieve economies of scale.
Ultimately, Taobao relied on Tmall to cater to high-end segments while retaining a full range of customers. Pinduoduo relied on the national-level app WeChat to引流, encircling the world from rural China. Only JD.com, focused on brands, found itself in a dilemma.
Let's compare this to the rebate mechanism of exchanges. Rebate KOLs and exchanges pursue the number of retail followers. Retail profits and losses do not affect the copy-trading mechanism, which is inconsistent with e-commerce rebates. Users themselves have an initial demand to purchase goods; giving users discounts benefits the promotion efforts of traffic stations and sellers.
From this perspective, the Builder mechanisms of Hyperliquid and Polymarket do not solve the above problems. The growth promoted around them can only be growth in trading volume.
This is not to say that growth in trading volume is unimportant, but it still results in wasted idle capital. Moreover, more trading volume leads to more idle capital, which is not a good thing for the financial industry, which pursues capital efficiency.
If we cannot跳出 the growth logic限制 of CEX/DEX, prediction markets will quickly peak because public events available for trading are ultimately limited. Smaller, more instantaneous events will favor the house's advantage, truly leading them down the exchange track.
Information博弈 is the essence of prediction markets. During the process of betting —> expiration, funds become idle. How to "utilize" this idle capital is the underlying motivation for the mutual attraction between prediction markets and DeFi.
Image Caption: Adding leverage to prediction assets. Image Source: @zuoyeweb3
Do not attempt to interfere with the user's normal betting experience. In current discussions about adding leverage in prediction markets, there are two main trends:
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The interceptive operation represented by Gondor, where users deposit their positions into DeFi staking after betting. Regardless of liquidity management and APY calculation, simply changing the user's purpose is already doubly difficult and easily leads down the path of high-interest吸储.
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Messari's Kaleb Rasmussen attempted to price the "Jump Risk" of prediction market prices. As mentioned earlier, prediction market prices can instantly converge to 1 or 0. The mathematical discussion is brilliant, but the practical financial engineering implementation is quite challenging.
Based on existing practices, I boldly propose a simpler combination method for achieving transparent DeFi leverage without interfering with the user experience, for the reference of founders: a cross-market arbitrage mechanism模仿淘客, arbitraging between prediction market audiences and DeFi audiences.
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The platform provides prediction market order-placing services. Users place orders for 0 or 1 positions at a discounted price, obtaining better market prices. The platform gains lower financing costs, and prediction markets like Polymarket gain more traffic.
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The platform or prediction market LPs/MMs act as vault managers. After users place bets, they deposit into protocol vaults cooperating with the prediction market, such as Morpho, to earn DeFi stack yields.
In the above process, the user's betting experience is not interfered with at all. As long as the platform's discounted price cost is less than the收益 from the DeFi stack, scale effects will take effect. Users will ultimately receive their betting losses or profits, but unlike trading rebate mechanisms, users place orders based on their own judgments.
Unlike the infinite issuance of xUSD引爆 leverage, Polymarket's USDC actually exists. The only risk point is the manager's operational skill.
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Prediction market platform: Embeds itself into the broader DeFi stack without compromising user experience while increasing platform trading volume.
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Managers + LPs/MMs: Utilize idle capital. Capital with确定的到期日 can build new models超越 short-term arbitrage.
Like the rebates of e-commerce third-party traffic stations, buyers will still have transactional relationships with the platform and sellers. The Yes/No bettors in prediction markets will also have transactional relationships with Polymarket, unrelated to the vault managers.
Moreover, Polymarket remains at the core of the entire transaction环节. Thanks to Morpho's open architecture, even if bad debts occur, they follow normal liquidation procedures, minimizing the platform's responsibility.
Conclusion
Use DeFi thinking to arbitrage "traffic," not traffic thinking to buy DeFi volume!
The real value of prediction markets lies in their idle capital, with clear expiration dates and corresponding asset reserves. If Polymarket wants to beat Kalshi in capital efficiency, scale expansion has reached a阶段性极限.
In other words, compared to trading assets, Wall Street and the crypto circle's pricing of information is currently in an irrational狂热 phase. Whether it's TGE or IPO, issuing stablecoins or building L1/L2s, these are all expected常规动作.
Before the uncertain date of TGE/IPO, Polymarket deterministically needs a strong peripheral ecosystem to繁荣 trading volume and compete with Kalshi. The programmability and composability of on-chain funds for capital are the solution for Polymarket's peripheral traffic.
The biggest financial opportunity in 2026 is the cyclically fluctuating midterm elections and the World Cup. FIFA讨好 Trump, regulators greenlight DeFi and gambling—it is undoubtedly a big financial year.
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