Author：BlockBeats
Original title: "As someone who plays the market prediction game every day, I've witnessed these innovations and changes."
Original author: Asher, Odaily Planet Daily
"With Polymarket's high liquidity, why would anyone use other prediction market platforms besides farming points for token airdrops?"?" This is a question I've been pondering while experiencing several prediction markets recently.
Admittedly, Polymarket's parent company, Blockratize, recently filed a trademark application for "POLY" during its token issuance plan. Coupled with Polymarket executives' previous statements about plans to launch a native token and airdrop it, the market widely expects Polymarket to be the next big "freebie hunter." However, unlike other emerging prediction markets, Polymarket currently lacks explicit points or task incentives, making it difficult for users to dynamically adjust their "freebie hunting" strategies based on feedback from point incentives.It is still in a "blind play" difficulty mode to some extent..
In contrast, most of these emerging prediction market platforms have introduced a points system, giving users a clearer "airdrop strategy path" while participating in platform trading. Although most of these prediction market platforms are still in their early stages, have some bugs, and often draw complaints from community members, some distinctive features that "distinguish them from Polymarket" can indeed be found in actual use.
Below, I will introduce several highlights that I have summarized in my recent experience with different prediction market platforms.
Highlight 1: Funds in positions are no longer "lying idle"; even predicted positions can generate continuous returns.
In traditional prediction markets (such as Polymarket and Kalshi), after a user buys a YES/NO position, the funds are typically locked until the event is settled. During this period, these funds cannot participate in other strategies or generate any returns; essentially, they are "idle funds" with a significant opportunity cost.
predict.fun attempts to change this. The platform will integrate the collateral funds used by users for predictions into a low-risk, interest-bearing strategy within the BNB Chain ecosystem, allowing the positions to automatically generate stablecoin yields during the holding period. According to the official announcement on January 8, 2026...predict.fun has partnered with Venus Protocol.The USDT collateral assets locked by users will be automatically deposited into Venus's money market to earn interest, thus generating additional income while awaiting the outcome of events.
In other words,During the holding period, users' funds continue to "work" on the blockchain, with typical annualized returns for stablecoins ranging from 3% to 5%.(This depends on the underlying DeFi strategy and market environment). More importantly, this part of the return is independent of the prediction result—regardless of whether the final prediction is successful, the yield generated during the holding period can be claimed separately, which is equivalent to adding an additional passive income source in addition to the predicted profit and loss.
From a product mechanism perspective, this design is equivalent to transforming "dead money" in traditional prediction markets into "live money," which is also one of the most distinctive differentiating features of predict.fun. Currently, the platform has enabled the function of claiming holding profits, allowing users to claim accumulated holding profits at a fixed time every Tuesday, giving long-term holdings a clearer compound profit logic at the strategy level.
predict.fun portfolio profit chart
Highlight Two: The short video-style swiping experience brings the prediction market closer to a "content consumption product".
Unlike traditional prediction markets, which have a trading terminal-like interface,Some emerging prediction market platforms are beginning to clearly emulate content platforms in their interaction design.,Attempting to lower the barrier to entry and increase user dwell timeFor example, in the mobile interface of predict.fun, one screen corresponds to one prediction event. Users can quickly browse different markets by swiping up and down, and the overall experience is more similar to the information feed mode of a short video platform. This design allows users to discover prediction targets of interest naturally while constantly "browsing the market" without actively searching for events, significantly improving browsing efficiency and participation frequency.
Similarly, Probable uses a left-right swipe interaction method, making the prediction behavior more similar to the information matching logic of social products in terms of user experience. From a product perspective, the core of this type of design is not simply to optimize the UI, but to try to transform the prediction market from a "low-frequency trading tool" into a "high-frequency content consumption portal".
Illustrations of mobile interaction methods for two prediction market platforms (left: predict.fun; right: Probable)
Dingaling, the founder of predict.fun, also mentioned in Space that he hopes to build the prediction market into a usage scenario similar to short video apps—users can place bets while browsing trending events and interesting topics, and further enhance community participation and user stickiness through comments, interactions and other functions.
From an experiential perspective, this information flow-style interaction is itself a highly attractive product innovation. Compared to the traditional method of actively searching for the market, swiping allows users to continuously "browse the market" during fragmented time, naturally generating participation while browsing content, making the user experience of predictive markets more lightweight and seamless.
Highlight 3: A "dedicated event marketplace" centered around community hot topics enhances localized participation.
Beyond product mechanics and user experience, some emerging prediction market platforms are also exploring differentiated approaches in their market content design. Instead of simply replicating generic events already available on platforms like Polymarket or Kalshi, they are launching more niche-focused "exclusive event markets" centered around topics of high interest within the crypto community. For example, prediction.fun's prediction events related to Binance and community hot topics, such as "Changes in the Bitcoin balance of the Binance SAFU fund wallet on March 1st" and "Number of tweets by CZ between February 7th and 14th, 2026," fall into categories more closely aligned with the daily discussions among crypto users.
predict.fun launches exclusive event prediction service
Compared to traditional macro events or general political and sports events, these predictive events with a strong community element are more likely to spark user discussion and dissemination, and more likely to generate engagement within specific user groups. From a platform operation perspective, the continuous release of exclusive events is essentially building a content supply with platform-specific characteristics.This has transformed prediction markets from mere "trading venues" into hubs for community sentiment and narratives.
As seen from the above events, predict.fun is consciously differentiating itself at the "event supply" level, rather than simply replicating existing markets on Polymarket or Kalshi. By designing prediction events around CZ, the Binance ecosystem, and hot topics discussed in the community, the platform can more easily generate dissemination and engagement among specific user groups. This content strategy is also becoming an important operational direction for some emerging prediction markets.
It's worth noting that a significant portion of the more active emerging prediction markets currently feature projects from the BNB Chain ecosystem, and their user base is noticeably skewed towards the Asian community. Against this backdrop,Community culture, subcultures, and even more "fan-circle"-like participation behaviors are gradually becoming important factors influencing the design and dissemination of predictive market events.Against this backdrop, for emerging prediction market platforms, the Asian community culture formed around differentiated event design and the more "fandom-like" participation behaviors are becoming a key area of research, and the related impacts will be further discussed in subsequent articles.
