In terms of product structure, Gate Prediction Market has integrated with the Polymarket on-chain prediction market ecosystem. Users can participate in corresponding markets directly through the entry point in the Gate App and complete related operations using USDT in their accounts. This structure lowers the barrier to participating in on-chain prediction markets, allowing users to access an on-chain event trading system without having to manage complex wallet interactions separately.
Compared with traditional trading products, the core of a prediction market is not simply “betting on an outcome.” Instead, it reflects the market’s expectations for future events through price movements. A sports match, a policy decision, or a price range for a crypto asset can all be converted into tradable event markets.
As prediction markets continue to evolve, their product functions are no longer limited to simple event lists. They are beginning to incorporate trending event discovery, information aggregation, leaderboards, strategy tracking, and trading behavior analysis, gradually expanding toward the model of an “information trading platform.”
Source: www.gate.com/prediction
Traditional prediction market platforms usually operate under a centralized structure. The platform itself is responsible for core processes such as event creation, rule setting, odds configuration, and fund settlement. This model is relatively similar to traditional prediction platforms or centralized event trading systems. The platform acts as both the market operator and the outcome adjudicator, so users must rely on the platform for final settlement and fund management.
Under this structure, the platform usually has strong control over the market, including deciding which events can be listed, how outcomes are defined, and when settlement is completed. Since the underlying data and trading logic are mainly stored in the platform’s internal system, ordinary users usually cannot directly verify the back end status. As a result, transparency depends more on the platform’s own reputation and operational capabilities.
Traditional prediction platforms also tend to organize events in a relatively fixed way. Most products use static category sections, such as sports, politics, or finance. After entering the platform, users often need to browse different sections manually to find markets they are interested in, while the platform itself rarely plays a strong role in “trending event discovery” or “trend aggregation.”
At the same time, traditional prediction platforms are more oriented toward “single event participation.” After users complete one prediction trade, they often have limited access to further strategy analysis or market observation tools. Many platforms offer relatively simple displays for asset management, trading records, and returns. They lack leaderboards, trader labels, and behavior analysis systems, so the overall experience feels more like one off event trading than a continuously evolving trading ecosystem.
Differences Between On-Chain Prediction Markets and Centralized Event Trading
One of the biggest differences between on-chain prediction markets and traditional centralized prediction platforms lies in the underlying trading and fund management structure. Traditional platforms usually custody user assets through the platform itself and maintain orders and settlement logic through centralized databases, while on-chain prediction markets rely more heavily on smart contracts to execute trades and record market states.
In on-chain prediction markets, market states, trading records, and fund flows can usually be publicly verified. Users’ trading activity is written directly to the blockchain, and funds are managed by on-chain contracts rather than relying entirely on the platform’s internal system. This structure improves transparency and reduces users’ dependence on the custody capabilities of a single platform.
| Comparison Dimension |
Centralized Prediction Platforms, Traditional Model |
on-chain Prediction Markets |
Main Advantages, on-chain Prediction Markets |
| Fund management structure |
The platform centrally custodies user assets and manages them through a centralized database |
Smart contracts execute automatically, and funds are managed directly by on-chain contracts |
Reduces custody risk and improves fund security |
| Trade execution and records |
Relies on the platform’s internal system and centralized servers |
Trades are written directly to the blockchain and executed and settled through smart contracts |
The entire process is open and transparent, and can be publicly audited and verified |
| Transparency |
Relatively low, with trading and settlement processes not fully public |
High, with all market states, trading records, and fund flows publicly visible |
Reduces black box operations and strengthens user trust |
| Market openness |
Event listings require platform review, and expansion is slower |
Open market structure, with greater flexibility in event listings |
Faster information aggregation and broader market coverage |
| Price mechanism |
Traditional odds or prediction contest model |
Price represents “market implied probability,” such as 0.7 = 70% probability of occurrence |
Turns prediction into information aggregation and probability trading, with stronger information discovery value |
Another clear difference is market openness. on-chain prediction markets usually offer greater flexibility in event listing because their structure is closer to an open information market. By contrast, traditional centralized platforms often expand events more slowly because they require review, maintenance, and unified management.
In addition, the price mechanism in on-chain prediction markets differs from that of traditional prediction products. In most on-chain prediction markets, event prices are usually viewed as “market implied probabilities.” For example, if the price of an outcome is 0.7, it often means the market believes the probability of that event occurring is about 70%. This “price as probability” logic has gradually transformed prediction markets from traditional prediction contests into a structure for information aggregation and probability trading.
Polymarket is one of the most representative projects in today’s on-chain prediction market sector. Its core feature is the use of blockchain and smart contracts to build open event trading markets. Unlike traditional prediction platforms, Polymarket places greater emphasis on on-chain transparency, a non custodial structure, and global participation, which is why it is often seen as an important part of information finance, or InfoFi.
Compared with traditional prediction platforms, which mainly operate around fixed events, Polymarket covers a wider range of markets, including political elections, macroeconomics, sports events, technology trends, and crypto assets. Because on-chain markets can update quickly, the platform is often able to aggregate global trending events and shifts in market sentiment more promptly.
After Gate Prediction Market integrated with Polymarket , it formed a combined structure of “centralized entry point + on-chain market.” Users can participate in on-chain prediction markets more conveniently through the Gate App without fully relying on native on-chain wallets or complex interaction processes. To some extent, this model lowers the usability barrier for on-chain prediction markets.
Compared with traditional prediction platforms, this structure not only improves market openness, but also strengthens trending event aggregation capabilities and market transparency. However, on-chain prediction markets may still be affected by liquidity fluctuations, on-chain congestion, and changes in the regulatory environment, so their operating logic differs significantly from traditional centralized event trading systems.
Differences in Trending Event Discovery and Trend Aggregation Mechanisms
Traditional prediction platforms usually organize event content through fixed sections and manual recommendations. Users mainly rely on navigation bars or keyword searches to find markets. In an environment where trending topics change quickly, this structure often struggles to reflect real time market attention in a timely way.
By contrast, the new generation of prediction market products has begun to place greater emphasis on “trending event discovery.” One of the key directions of Gate Prediction Market’s latest upgrade is to strengthen its search system and trend aggregation capabilities, allowing the platform to serve not only as a trading venue but also as an entry point for information flow.
The new search system supports fuzzy keyword matching, highlighted search results, and category based recommendations, helping users find events of interest more quickly. At the same time, the “Live & Trending” section aggregates real time trading hotspots and highly watched events, allowing users to observe changes in market sentiment more promptly.
In addition, the platform has added features such as recent browsing, search history, secondary categories, and breaking event sections, further strengthening users’ ability to continuously track trending events. Compared with the static navigation model used by traditional platforms, this dynamic trend aggregation structure places greater emphasis on information discovery efficiency, trend response speed, and real time market observation.
Differences in Leaderboards, Label Systems, and Strategy Features
Traditional prediction platforms usually focus more on the events themselves and provide fewer complete tools for analyzing trading behavior. Although users can participate in prediction trading, they often have difficulty observing the strategy performance of other traders and lack a systematic data tracking framework.
Gate Prediction Market, by contrast, is beginning to strengthen its leaderboards, user labels, and strategy observation capabilities. The new leaderboard covers multiple dimensions, including profit and loss, trading volume, and highest profit. It also centrally displays key data such as position value, total profit and loss, and trading size, making trading behavior in the market more observable.
This structure gives prediction markets the characteristics of a “strategy data platform.” Users can not only participate in event trading, but also observe highly active traders in the market, analyze different trading styles, and use leaderboards to understand fund flows and shifts in market sentiment.
The system also plans to add label features such as smart money, whales, and suspected insiders, along with data tools such as profit and loss curves and historical position trends. These features further strengthen the “behavior analysis layer” within prediction markets and are helping prediction markets evolve from simple event trading platforms into comprehensive product structures that combine information discovery, strategy observation, and market behavior analysis.
Differences in Interaction Efficiency and Participation Barriers for Prediction Market Products
Although on-chain prediction markets offer advantages in transparency and openness, native on-chain interaction processes are usually more complex. Users often need to create their own wallets, manage private keys, complete cross chain deposits, and understand on-chain gas and confirmation mechanisms. These steps can raise the participation barrier for ordinary users.
Gate Prediction Market simplifies some on-chain processes through its account system and product entry point integration. Users can enter the relevant markets directly through the entry point in the Gate App and use USDT in their accounts to participate in event trading, without frequently carrying out native on-chain operations.
At the same time, after the platform upgrade, features such as category browsing, quick filtering, one click order placement, and historical record filtering have also been improved, making the trading path more streamlined. In asset management, the system supports categorized displays for records such as buys, sells, refunds, and claims, further improving the clarity of fund changes and position management.
In sports prediction markets, the platform has also added derivative formats such as spreads and totals, while supporting slide based score selection and quick order placement. This design lowers the learning cost of more complex formats and is helping prediction markets move toward greater efficiency, lower barriers, and a stronger interaction experience.
Summary
Prediction markets are evolving from traditional event prediction platforms into a new type of market structure that combines trending event discovery, information aggregation, probability trading, and strategy observation. Compared with traditional prediction platforms, on-chain prediction markets place greater emphasis on public transparency, non custodial structures, and global participation, while also strengthening the role of market prices as “probability signals.”
The emergence of on-chain prediction market projects such as Polymarket has given prediction markets stronger information aggregation attributes. Gate Prediction Market, meanwhile, has further lowered the usability barrier for on-chain prediction markets by integrating with the Polymarket ecosystem and strengthening search, trending event aggregation, leaderboards, and strategy observation features.
From the perspective of industry development, prediction markets may not only serve as event trading tools in the future. They may also gradually become an important information infrastructure connecting trending information, market sentiment, and trading behavior.
FAQs
Does Gate Prediction Market operate based on on-chain prediction markets?
Gate Prediction Market has integrated with the Polymarket ecosystem, allowing users to participate in some on-chain prediction markets through the Gate App entry point.
Polymarket uses blockchain and smart contracts to operate and settle markets, giving it stronger transparency and openness.
Why do prediction markets emphasize “price as probability”?
In binary outcome markets, price can usually be understood as the combined expectation of market participants regarding the probability that an event will occur.
Why has Gate Prediction Market added leaderboards and a label system?
These features help users observe market behavior, track trading strategies, and improve information discovery efficiency within prediction markets.
Are there risks in on-chain prediction markets?
on-chain prediction markets may face risks such as regulatory uncertainty, insufficient liquidity, market volatility, and disputes over event resolution.
