(Data source: Dune, as of 11:00 AM, Feb 26)
2.2 Revenue Comparison: Validated Dynamic Fees vs. Nascent Taker Fees The fee logic of the two platforms is fundamentally different. Kalshi Uses probability-weighted dynamic fees: charges trading fees based on contract price, with the fee rate fluctuating with the contract price, peaking at 50 (i.e., 50/50 probability) and decreasing towards the 0 or 99 extremes. For a $100 trade, the maximum fee is approximately $1.74, with an effective fee rate of about 1.2%. Revenue was $24 million in 2024 and $260 million in 2025, a year-on-year increase of 994%. However, revenue is highly concentrated during sports seasons: the NFL season (Sep-Nov) alone contributed $138 million, and December’s $63.5 million set a new monthly record. Revenue significantly drops during off-seasons, showing clear seasonal characteristics. Polymarket Looking back at Polymarket, they took a completely opposite path. Until the end of 2025, Polymarket was operating at a loss, offering zero fees throughout, trading free access for users. It wasn’t until this February that they formally implemented dynamic Taker Fees in sports markets. In the first week after introducing fees, Polymarket’s fee revenue exceeded $1 million. Data from DefiLlama shows Polymarket’s revenue over the last 30 days is $3.18 million, with the revenue curve only truly starting to climb from January this year. It’s worth noting that daily-settled markets might become a future revenue source for Polymarket. High-frequency, short-cycle markets generate more transactions, and similar to Meme trading, users in these markets are less sensitive to fees. Comparing the two: Kalshi’s fee model is validated but reliant on sports seasons. Polymarket’s fee structure is just beginning; its annual revenue, though a fraction of Kalshi’s, signifies that Polymarket’s phase of trading zero fees for liquidity is over. Now, they are starting to seriously build a business. 2.3 User Profile: Licensed Elites vs. Global Retail Traders The user structures of the two platforms are largely shaped by their regulatory environments. Kalshi holds a CFTC license, allowing it to legally serve US users, with its business primarily concentrated in the domestic US market. Polymarket re-entered the US market through the acquisition of QCEX at the end of 2025. In the years prior, it was mainly active overseas. This period of “exile” ironically helped it accumulate a broader international user base. The differences in their user bases are also evident from their revenue structures. 89% of Kalshi’s revenue comes from sports markets. User behavior is closer to traditional sports betting: high trading frequency, relatively smaller average transaction size, and activity fluctuating with seasons. User numbers surge when the NFL season starts and trading volume noticeably declines after the season ends, showing pronounced seasonal patterns. Polymarket’s structure is completely different. Politics and macro markets occupy a core position, attracting many institutional-level traders to hedge macro risks here. The average bet size is significantly larger. During the 2024 US election, a French trader placed a single bet exceeding $50 million, ultimately profiting $85 million. Such scale is almost unheard of in sports betting markets. 2.4 Channel Moat: Distribution Partners vs. Developer Ecosystem By the end of 2025, both Robinhood and Coinbase had launched prediction market features on their platforms, partnering with Kalshi. It’s not just brokerages integrating; sports platforms like PrizePicks and Underdog also directly funnel their existing sports betting users to Kalshi. In December, Kalshi, along with Coinbase, Robinhood, and Crypto.com, co-founded the Prediction Markets Alliance. The logic is quite straightforward. Kalshi holds the Designated Contract Market (DCM) license issued by the CFTC. For licensed financial institutions, integrating its system is akin to connecting to a traditional futures exchange—the process is clear, compliance costs are lower, and risks are manageable. Polymarket is taking a completely different direction. They aren’t focusing on channel distribution but are more like building underlying infrastructure, hoping others will develop products around it. The most evident step in this strategy was an acquisition five days ago: Polymarket bought Dome, a project from the Y Combinator Fall 2025 batch. Dome provides a prediction market API; developers write code once and can simultaneously access data and liquidity from multiple platforms like Polymarket and Kalshi. With Vibe Coding currently trending, developers can directly call Dome’s API to build trading bots, data dashboards, and embedded market components. AI Agents can also use this API to automatically execute prediction trading strategies. Placing the two routes side by side makes it clear. Kalshi is expanding channels, relying on partners to bring users and trading volume. Polymarket is building the foundation, hoping developers will grow applications on top of it. One path leans more towards commercial network expansion, the other bets on the spontaneous formation of an ecosystem. Once the underlying layer truly achieves network effects, it will be very difficult for latecomers to replicate. 2.5 Marketing Strategy: Brand Exposure vs. Community Virality The marketing approaches of the two are highly consistent with their respective user structures. Kalshi focuses on brand exposure, with a very traditional, direct approach. During the New York City mayoral election, they plastered real-time odds advertisements across Times Square, Penn Station, and subway trains, putting prediction probabilities directly on street screens. For the NBA Finals, Kalshi used AI tools to produce a $2,000 TV commercial in two days, airing it during prime time, garnering over 3 million views on X. Additionally, through partnerships with CNN and CNBC, Kalshi’s data appears directly in news broadcast graphics. For the average viewer, this equates to official endorsement, naturally boosting trust. Polymarket’s approach is completely different, leaning more towards community-driven propagation. They designed a detailed referral mechanism. Users share a unique link; for every click generated, the referrer earns $0.01. If the referred person deposits over $20, it triggers a $10 CPA (Cost Per Acquisition) reward. When clicks and trading volume reach certain thresholds, additional distribution rewards are unlocked. The entire structure incentivizes referrers to continuously attract new users, similar to the affiliate link玩法 in meme trading platforms. Furthermore, Polymarket is deliberately cultivating its own content ecosystem, such as supporting accounts like @BrosOnPM. These KOLs primarily serve prediction market builders and traders, producing daily content, helping developers connect with traffic, and fostering internal community circulation. 3. So, Who is the Ultimate Champion? The previous section described what the two companies look like now, but the current landscape does not equal the future one. The prediction market is still in its early stages, with too many variables—regulation is undecided, competitors are pouring in, and business models are not yet fully validated. Rather than giving a definitive conclusion, it’s more valuable to outline the key questions that will truly determine the winner. Both are Expanding into Each Other’s Core Territories Judging from their actions, both platforms are aware of their weaknesses and are starting to address them. When Polymarket re-entered the US market, the first batch of contracts it launched were all sports-related. They later signed official partnerships with MLS, NHL, and the New York Rangers, using these league brands to endorse their sports markets. A platform that started with politics is now desperately trying to squeeze into the sports circle. Our analysis suggests two main reasons: Political markets might be less favored by US regulators for the time being, while sports markets are more easily accepted. To capture Kalshi’s market share in the US. Kalshi hasn’t been idle either. They signed deals with CNN and CNBC, getting their odds data displayed in on-screen graphics during live news broadcasts. A platform that started with sports is now trying to penetrate the political赛道, attempting to establish media-level credibility. But the risks for the two are not on the same scale. Polymarket has real trading volume in both politics and sports, while almost all of Kalshi’s trading volume is concentrated in sports. This structural difference becomes a significant issue when discussing regulatory risks later. The Biggest Channel Partner, or the Most Dangerous Competitor? Robinhood is one of Kalshi’s most important retail distribution channels, contributing over half of its trading volume in 2025. Coinbase has also launched prediction markets across all 50 US states, also clearing through Kalshi. But both have almost simultaneously made the same move: Robinhood formed a joint venture with Susquehanna to acquire MIAXdx. Coinbase acquired The Clearing Company. Both companies are building their own CFTC-qualified exchange infrastructure, expected to be operational in 2026. Once built, they can choose to continue partnering with Kalshi and sharing revenue, or they can choose to keep all the profits for themselves. By then, they will already have user data, trading habits, and liquidity积累. For Kalshi, this is not just a risk that channel partners might leave one day; it has become a specific threat with a timeline. Kalshi’s channel moat is essentially a time-limited first-mover advantage. Polymarket’s Fees: A Critical Step in Validating Its Business Model Polymarket’s trading volume exceeded $33.8 billion in 2025, yet its revenue was close to zero. But a $9 billion valuation ultimately needs revenue to support it; 2026 is the time to deliver. Fee implementation started with a pilot in cryptocurrency markets, then expanded to sports events on February 18, 2026. The logic behind this choice is clear: both are daily-settled markets with high trading frequency, relatively small average transaction sizes, fast user turnover, and lower sensitivity to fees compared to long-cycle political/macro contracts Эта статья взята из интернета: Polymarket vs Kalshi: Who is the King of Prediction Markets? 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