Hotcoin Research | Prediction Market Boom: The Rise of a $50 Billion Sector and Opportunities in 2026

introduction

I. Overview of Forecast Markets

Definition of prediction market

The difference between prediction markets and gambling

• The price formation mechanisms differ : prediction markets use market-based pricing methods such as public order books or AMMs, where prices are generated through the interplay between trading parties. The platform does not pre-set odds or assume risk for the outcome; it only charges transaction fees. In contrast, traditional betting platforms set fixed odds, ensuring profits through "bookmaker advantage." The purpose of odds adjustments is to control risk rather than reflect the true probability.
• Their functions and uses differ : market prediction prices are data products that can be externally referenced and used for macroeconomic decision analysis, policy forecasting, corporate risk management, and even, conversely, influencing media narratives and decision-making references. Betting odds, on the other hand, are primarily used for entertainment and lack information discovery value.
• The participants have different structures : the main participants in the prediction market are information-driven traders, including researchers, macro traders, data analysts, and institutions, whose core goal is to profit from information gaps and price discovery; while gambling attracts more ordinary consumers and is often driven by emotions and preferences, with little correlation between participation motivation and information accuracy.

Predicting the reasons for explosive market growth

• Regulatory Breakthrough: In 2025, the U.S. CFTC gave a clear definition to prediction markets, recognizing them as legitimate commodity derivatives rather than gambling.
• The influx of capital and institutions: Progress in compliance has boosted investor confidence, leading to a surge in funding for prediction market projects in 2025. Polymarket and Kalshi are reportedly expected to complete multiple funding rounds totaling over $1 billion each in 2025. Furthermore, compliance advantages have helped Kalshi secure liquidity support from SIG, a well-known Wall Street market maker.
• Expanding Event Categories: Early prediction markets primarily focused on macroeconomic events such as political elections, but the field has now expanded to broader areas including economic indicators, crypto industry trends, and sporting events. In 2025, a constant stream of breaking news, major political events, and significant sporting competitions will provide a continuous catalyst for the prediction market, with the concentrated emergence of hot topics across various sectors.
• The maturity of technological conditions: advancements in blockchain scaling solutions (such as Layer 2 reducing gas fees), the development of on-chain settlement and automated market-making tools, and the application of AI in information analysis and assisted trading all make it easier for ordinary users to participate in prediction markets. Meanwhile, improvements in wallet experience, the opening of fiat currency deposit channels, and social distribution have simplified the onboarding process for new users.

II. Market Status Prediction: Sector Landscape and Data Performance

1. Overall Scale and Duopoly Structure

2. Market Sentiment and Capital Flows

III. Review of Representative Prediction Market Platforms

1. Kalshi – A compliant American-style prediction exchange

• Platform Overview: Kalshi launched in June 2021 and is the world's first CFTC-licensed prediction market exchange. Headquartered in the United States, it employs a centralized matching mechanism and compliant settlement. Users must complete KYC before trading in fiat currencies such as USD. It primarily uses Yes/No binary contracts, covering multiple categories including politics, economic data, climate, crypto, and sports. With the launch of its sports market, Kalshi experienced a surge in trading volume in the second half of the year. In 2025, Kalshi's trading volume reached $23.8 billion, representing a year-on-year increase of over 11 times; its historical cumulative trading volume is approximately $27.1 billion.
• Event Types: Sports events are the platform's main feature, accounting for over 85% of trading volume. It also offers political and economic forecasts (elections, macroeconomic indicators, etc.) and crypto market events. Starting in 2025, the scope will be expanded to include new types of contracts such as listed company financial report forecasts. This diversification of forecast themes enhances the platform's practical value for hedging and speculation.
• Mechanism and Revenue Model: Kalshi uses a Central Limit Order Book (CLOB) model for order matching. Kalshi profits by charging transaction fees, with rates varying slightly depending on the contract type (e.g., $0.01 per contract). To improve liquidity, Kalshi launched a market maker subsidy program in 2024-2025, investing at least $9 million to incentivize liquidity provision. It also collaborates with professional market makers such as SIG to improve order depth. Currently, Kalshi has not issued any tokens and primarily supports its operations through equity financing and trading revenue.

2. Polymarket – Leader in Decentralized Prediction Markets

• Platform Overview: Launched in 2020, Polymarket is a leading decentralized prediction market platform on the Ethereum and Polygon networks. Users participate via a web interface connected to their crypto wallets, supporting both binary and multi-select event markets. Polymarket employs a hybrid mechanism of a publicly shared order book and automated market making, utilizing decentralized methods such as smart contract escrow and UMA oracles to determine outcomes. While the operations team and server front-end are relatively centralized, settlement is completed on-chain. Polymarket's estimated trading volume in 2025 was approximately $22 billion. Its historical cumulative trading volume is approximately $23.2 billion, with over 314,000 active users. The second half of 2025 saw a surge in Polymarket's trading volume due to a series of events, and its market depth at one point led other decentralized platforms.
• Event Types: The platform boasts a diverse range of themes, making it one of the most comprehensive in the industry. Sports, politics, and crypto are the three main pillars, accounting for approximately 39%, 34%, and 18% respectively. Additionally, it has created markets in areas such as economic data, technological development, and popular culture. Polymarket, in particular, closely follows crypto hot topics, such as "Will a certain coin's price break a new high?" and "Will a certain project be delivered on schedule?", providing crypto investors with unique hedging/speculative tools.
• Mechanism and Revenue Model: Polymarket's transactions are settled via on-chain smart contracts, using a shared order book to match prices, ensuring that the sum of the Yes and No prices is always 1 (Yes + No = $1). Initially, the platform offers zero transaction fees to stimulate growth, but it actually sustains operations through spreads and liquidity subsidies. Around 2025, Polymarket will gradually begin charging small fees to winning bidders for revenue generation and plans to open up more third-party front-end revenue-sharing models.

3. Opinion.trade – A civilian-oriented forecasting terminal for macroeconomics

• Platform Overview: Opinion operates on the BNB Chain blockchain and is a prediction market platform focused on global macroeconomic and financial indicators. Positioned as a "terminal for ordinary people," it aims to transform macroeconomic insights into tradable markets, allowing ordinary individuals to participate in macroeconomic information betting. The platform architecture integrates on-chain trading infrastructure, AI-assisted oracles, and DeFi modules, enabling users to create, trade, and resolve real-world economic events through decentralized means. Opinion's historical total trading volume has reached $13.1 billion, ranking third among all prediction markets. This high figure may be partly attributed to aggressive liquidity mining or wash trading activities.
• Event Types: Primarily focused on economic and financial forecasts, including macroeconomic indicators (inflation, employment, interest rates, etc.), policy changes in various countries, and market index trends. It also covers some political events and cryptocurrency market forecasts, but unlike entertainment-oriented platforms, Opinion emphasizes serious financial content. Its design aims to lower the barrier to entry for traditional financial terminals, allowing users to participate in macroeconomic trading similar to that previously only possible with Bloomberg terminals, with relatively small capital investments.
• Mechanism and Revenue Model: The platform utilizes AI-assisted oracles: leveraging artificial intelligence to acquire and judge event outcomes from authoritative data sources, improving the efficiency and accuracy of oracles. Revenue models include transaction fees and market creation fees. PredictionIndex labels Opinion as "pre-TGE," indicating a potential plan to issue tokens.

4. Limitless – High-Frequency Prediction Market Based on Base Chain

• Platform Overview: Limitless is a decentralized prediction market platform deployed on Coinbase's Base Chain, aiming to provide high-frequency, short-cycle prediction trading services. Limitless focuses on hourly and daily frequent markets, including various market predictions for crypto and traditional assets, providing users with trading conditions expressed in natural language. Base Chain's low fees and fast confirmation enable Limitless to support users frequently adjusting positions and achieving near real-time price discovery. Limitless currently has a cumulative trading volume of approximately $512 million, ranking 4th among prediction markets. Benefiting from user traffic from the Base ecosystem and Coinbase's endorsement, Limitless's trading volume has steadily increased since its launch in the second half of 2025.
• Event Type: Focuses on short-term market trend prediction. Coverage includes cryptocurrency prices (e.g., "Will BTC close above X today?"), intraday price movements in traditional stock and commodity markets, and the immediate impact of specific macroeconomic events. Limitless tends to design binary contracts (yes/no) or range contracts (e.g., which price range it falls within) for users to trade within very short periods. Additionally, the platform offers real-time predictions for sports events, such as the outcome of matches, allowing users to continuously buy and sell positions during the event.
• Mechanism and Revenue Model: Limitless operates entirely on the BaseChain, issuing collateralized Outcome Shares via smart contracts. Users purchase Yes or No shares; after the event, the correct party's share is redeemed at $1, while the incorrect party's share becomes zero. Trading employs a hybrid AMM + order book model, ensuring continuous liquidity while allowing users to place orders. Platform revenue primarily comes from transaction fees and market-making spreads. Its advantages lie in leveraging the low-fee BaseChain for a better user experience and potential collaborations with the Coinbase ecosystem.

5. Azuro – Decentralized Prediction Market Infrastructure Protocol

• Platform Overview: Azuro is a decentralized protocol focused on providing infrastructure for prediction markets. Unlike direct-to-user trading platforms, Azuro provides toolkits for developers, DApps, and operators, enabling them to quickly build various prediction applications. Azuro is deployed on multiple EVM-compatible chains ( Ethereum mainnet, Base, BNB chain, etc.) and uses a vAMM (virtual automated market maker) + "Liquidity Tree" fund management model to support liquidity in large-scale markets. Its goal is to become the Uniswap of the prediction market space, providing general-purpose infrastructure for others to build front-ends and customize gameplay. Azuro itself reports a total "processed" prediction trading volume of approximately $444 million, ranking 5th in the industry.
• Event Type: Azuro initially focused on sports betting/prediction, offering a betting market covering events such as football, basketball, and esports. Later, through community governance, the protocol expanded to support other categories such as politics and crypto pricing, but currently, most of its applications remain concentrated in sports and gaming betting. Azuro's design allows for diverse odds structures, not limited to a simple binary market; for example, it can support complex betting options such as scores and point spreads, thereby attracting traditional betting users.
• Mechanism and Revenue Model: Azuro's unique feature lies in its virtual AMM + liquidity tree model. Liquidity providers deposit funds into Azuro's pools, and the protocol algorithmically allocates these funds among different odds options, essentially automatically making markets for all options. This ensures that even if no one actively places orders for certain options, liquidity still exists for users to bet. Azuro collects transaction fees through smart contracts and settles them periodically to LPs and the protocol treasury. Revenue sources include marginal fees from player bets and a share of the revenue from LPs providing liquidity. The Azuro protocol has issued a governance token, AZUR, which holders can participate in DAO governance and receive a share of platform fees. However, the low price of AZUR indicates market skepticism regarding its tokenization and profitability prospects.

IV. Risks and Challenges Facing the Forecast Market

1. Regulatory compliance risks: Legal gray areas are an unavoidable hurdle for prediction markets. Even with federal CFTC approval in the US, some states and countries still consider prediction markets illegal gambling. For example, Kalshi, despite its license, has faced scrutiny from some state prosecutors who questioned whether its event contracts violated local anti-gambling regulations. Future shifts in regulatory direction could significantly impact platform operations. For decentralized platforms, meeting regulatory requirements (such as KYC and restrictions on sensitive event types) without sacrificing trustlessness remains a challenge.
2. Insider trading and manipulation: Because prediction markets are directly linked to real-world events, there is a risk of being exploited by insiders. Those with access to non-public information can profit by betting in prediction markets, causing market pricing distortions and unfairness. This not only carries legal risks but also damages the confidence of ordinary participants. Furthermore, the risk of manipulation by large investors must be guarded against: theoretically, those with substantial funds can create a false sense of probability by continuously raising/lowering contract prices, influencing others' decisions and even media interpretations.
3. The challenge of building liquidity: Compared to ordinary token trading using AMM (Automated Market Maker), prediction markets are closer to an order book model, requiring active order management. Furthermore, they experience significant price fluctuations, placing high demands on market makers. New platforms often struggle to attract sufficient market-making funds, resulting in a poor user experience. Without liquidity, there is no continuous trading, and consequently, no user retention. This liquidity barrier leads to a significant Matthew effect in the industry: leading platforms have ample funds, creating a virtuous cycle, while smaller platforms are trapped in a vicious cycle of "no liquidity → no users → even more liquidity shortage."
4. Market Mechanisms and Technological Risks: On-chain prediction markets also face technological risks such as smart contract vulnerabilities and oracle attacks. Historically, Augur has encountered problems with market abuse (users creating meaningless markets for arbitrage) and inaccurate oracle results due to low participation. Currently, some platforms use centralized oracles or human arbitration results, which raises trust risks and may lead to asset disputes and user losses. In addition, high-frequency prediction markets require high-performance on-chain support; congestion or failures in the underlying public chain can also impact transaction continuity.
5. Homogeneous Competition and Profit Models: Currently, many new projects essentially copy the Polymarket or Kalshi models, lacking differentiated selling points and easily getting bogged down in homogeneous competition when vying for users. Intense competition forces companies to launch aggressive measures such as high subsidies and zero transaction fees, attracting traffic in the short term but hindering long-term profitability. In fact, most prediction market platforms are still unprofitable, relying on funding to burn through cash for operation. How to establish a sustainable profit model without compromising user experience remains to be explored.

V. Market Outlook for 2026: Opportunities and Trends

1. The market continues its rapid growth, with major events catalyzing market movements. The surge in 2025 may just be the beginning, with the sector expected to expand several times, or even tenfold, in 2026. This year coincides with several globally significant events: the US midterm elections in November are expected to attract massive betting funds; the 2026 World Cup will be held in the summer, a global sporting event for which platforms like Kalshi have already planned their markets, and sports-related trading volume is expected to surge. Furthermore, the volatile global economic situation, the Federal Reserve's interest rate policies, and breakthroughs in cutting-edge technologies are all likely to be key events, continuously injecting trading momentum into the prediction market.
2. Industry consolidation is intensifying, further solidifying the oligopoly. "The strong get stronger" is likely to be the dominant theme in 2026. Kalshi and Polymarket, the two giants, will most likely continue to dominate the market and leverage their resource advantages to expand their competitive moat: Kalshi may seek more traditional financial collaborations, such as partnering with securities firms and asset management institutions to launch data products or derivatives based on prediction markets; Polymarket may embrace more of the Web3 ecosystem, such as deep integration with decentralized social platforms and information oracle networks, increasing user stickiness and traffic entry points. Among emerging platforms, we can expect to see Opinion solidify its position in the macro forecasting vertical, Limitless establish itself in the high-frequency market, and Probable leverage its BNB chain traffic to rise to prominence. However, overall, the vast majority of trading volume will still be concentrated in the hands of a few leading platforms.
3. More mainstream players are entering the market, deepening cross-industry integration. In 2026, we may see traditional financial and technology giants more actively participating in prediction markets. Coinbase, Robinhood, and others announced their entry into prediction markets in 2025. Some large hedge funds may also try to use prediction markets for strategic trading or hedging. At the same time, media and data agencies will cite prediction market data more frequently. This cross-industry integration not only enhances the exposure and credibility of prediction markets but also provides platforms with new monetization channels, such as licensing data to third parties.
4. The emergence of innovative products and derivatives is enriching the market. As the industry matures, prediction markets are expected to spawn a variety of innovative products. For example, data derivatives based on prediction market prices: some platforms or financial institutions may issue prediction index ETFs, event options, etc., securitizing prediction market results to facilitate public investment. There are also conceptual futures and insurance-like predictions. In the DeFi field, prediction market result tokens may be used for collateralized lending, yield aggregation, etc., becoming new financial Lego components. In the sports and entertainment field, NFTs or fan tokens may also be combined with prediction markets to form new social betting gameplay. These derivative innovations will attract investors with different preferences, thereby further expanding the market size.
5. The deep integration of AI and prediction markets is enhancing efficiency. Artificial intelligence technology is expected to be more deeply applied to all aspects of prediction markets by 2026. On one hand, AI can be used for information gathering and analysis, helping prediction market participants make better decisions. For example, AI robots can collect relevant news and social media sentiment online, providing traders with suggestions on the probability of events. On the other hand, AI will participate more in market making and arbitrage. High-frequency algorithms, based on machine learning models, can identify pricing discrepancies between prediction markets and traditional markets in real time for arbitrage, making prices more efficiently reflect true probabilities. Furthermore, AI can help improve oracle systems, such as using natural language processing to automatically interpret news event outcomes or detect subtle differences in outcome statements, reducing the need for human arbitration.

Conclusion

about Us

Risk Warning