Original | Odaily Planet Daily (@OdailyChina)
Author | Asher (@Asher_ 0210)
"Polymarket has such good liquidity. Besides farming points for potential token airdrops, why would I use other prediction market platforms?" This is a question I kept pondering while recently experiencing various prediction markets.
Indeed, the recent trademark application for "POLY" submitted by Blockratize, the parent company of Polymarket, during its token issuance plan, coupled with previous clear indications from Polymarket executives about plans to launch a native token and conduct an airdrop, has led to widespread market expectations that farming on Polymarket might be the next "big opportunity." However, unlike other emerging prediction markets, Polymarket currently lacks a clear points or task-based incentive system, making it difficult for users to dynamically adjust their "farming" strategies based on incentive feedback. To some extent, it remains in the hard mode of 'blind farming'.
In contrast, most of these emerging prediction market platforms have introduced points mechanisms, allowing users to have a clearer "path to an airdrop strategy" while participating in platform trading. Although many of these prediction market platforms are still in their early stages, often have bugs, and frequently draw criticism from community members, during the actual experience, one can indeed discover some differentiated highlights that are "distinct from Polymarket."
Below, I will introduce several highlights summarized from recent experiences with different prediction market platforms.
Highlight One: Position Funds No Longer "Lie Idle"; Prediction Positions Can Also Generate Continuous Returns
In traditional prediction markets (like Polymarket, Kalshi), after users buy YES/NO positions, the funds are typically locked until the event is settled. During this period, these funds cannot be used for other strategies nor generate any returns; they are essentially "idle funds" with significant opportunity cost.
predict.fun attempts to change this. The platform connects the collateral funds users employ for predictions to low-risk yield-generating strategies within the BNB Chain ecosystem, allowing positions to automatically generate stablecoin returns while held. According to an official announcement on January 8, 2026, predict.fun has partnered with Venus Protocol. Users' locked USDT collateral assets are automatically deposited into Venus's money markets to generate yield, thus continuously producing additional returns while waiting for the event outcome.
This means users' funds continue to "work" on-chain during the holding period, with common stablecoin annualized returns roughly in the 3%–5% range (depending on the underlying DeFi strategy and market conditions). More importantly, these returns are independent of the prediction outcome—regardless of whether the prediction ultimately succeeds or fails, the yield generated during the holding period can be claimed separately, adding an additional layer of passive income on top of the prediction profit or loss.
From a product mechanism perspective, this design transforms "dead money" in traditional prediction markets into "live money," making it one of predict.fun's most distinctive differentiating features currently. The platform has already opened the position yield claim function, allowing users to claim accumulated holding returns at a fixed time every Tuesday, giving long-term holdings a clearer compound return logic from a strategic perspective.
predict.fun Position Yield Claim Screenshot
Highlight Two: Short-Video Style Swiping Experience, Bringing Prediction Markets Closer to "Content Consumption Products"
Unlike the trading-terminal-like interface of traditional prediction markets, some emerging prediction market platforms are noticeably shifting their interaction design towards content platforms, attempting to lower the participation barrier and increase user dwell time. For example, on predict.fun's mobile interface, one screen corresponds to one prediction event. Users can quickly browse different markets by swiping up and down, an overall experience more akin to the information feed mode of short-video platforms. This design eliminates the need for users to actively search for events; instead, they naturally discover prediction topics of interest while continuously "scrolling through markets," significantly improving browsing efficiency and participation frequency.
Similarly, Probable employs a left-right swiping interaction, making the prediction experience closer to the information matching logic of social products. From a product perspective, the core of such designs is not merely UI optimization but an attempt to transform prediction markets from "low-frequency trading tools" into "high-frequency content consumption entry points."
Schematic Diagram of Mobile Interaction Methods for Two Prediction Market Platforms (Left: predict.fun; Right: Probable)
predict.fun founder Dingaling also mentioned in a Space that he hopes to build prediction markets into a usage scenario similar to short-video apps—where users can place bets while browsing hot events and fun topics in their daily routine, further enhancing community engagement and user stickiness through features like comments and interactions.
From an experiential standpoint, this information flow-style interaction is itself a highly attractive product innovation. Compared to the traditional method of actively searching for markets, swiping to browse allows users to continuously "scroll through markets" in fragmented time, naturally generating participation behaviors while consuming content, making the prediction market experience more lightweight and fluid.
Highlight Three: "Exclusive Event Markets" Centered on Community Hotspots, Strengthening Localized Sense of Participation
Beyond product mechanisms and interaction experiences, some emerging prediction market platforms are also beginning to experiment with differentiated approaches in market content design. That is, instead of simply replicating generic events available on Polymarket or Kalshi, they are launching more niche "exclusive event markets"围绕 (centered around) topics with high attention within the crypto community. For example, prediction events on predict.fun related to Binance and community hotspots, such as "Changes in Bitcoin Balance of Binance SAFU Fund Wallet on March 1st" and "Number of CZ's Tweets Between February 7 and 14, 2026," are topics closer to the daily discussions of crypto users.
predict.fun Launches Exclusive Prediction Events
Compared to traditional macro events or generic political/sports markets, these community-centric prediction events are more likely to stimulate user discussion and dissemination, and更容易 (more easily) generate participation heat within specific user groups. From a platform operation perspective, the continuous launch of exclusive events essentially builds a content supply with platform characteristics, making the prediction market not just a "trading venue" but也逐渐 (gradually becoming) a gathering place for community hotspot sentiment and narratives.
From the aforementioned events, it's evident that predict.fun is consciously pursuing differentiation at the "event supply" level, rather than simply replicating markets already present on Polymarket or Kalshi. Designing prediction events around CZ, the Binance ecosystem, and community discussion hotspots makes it easier for the platform to achieve virality and participation within specific user groups. This content strategy is also becoming an important operational direction for some emerging prediction markets.
It is worth noting that a significant portion of the currently highly active emerging prediction markets originate from the BNB Chain ecosystem, and their user base is noticeably skewed towards the Asian community. In this context, community culture, subculture, and even participation behaviors with more "fan circle" characteristics are gradually becoming important factors influencing prediction market event design and dissemination. Against this backdrop, for emerging prediction market platforms, the Asian community culture formed around differentiated event design and the more "fan circle"-like participation behaviors are becoming a direction worthy of focused study. The related impacts will be further discussed in subsequent articles.
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