Polymarket Report for the First Half of 2026: High-Frequency Traders or Super Forecasters?

If we only look at trading volume, the first half of 2026 for Polymarket resembles a platform competition; however, when we consider wallets, market categories, and settlement results together, the story is more akin to a division of labor diagram: Polymarket's U.S. market is rapidly growing, with sports and crypto markets facilitating quick capital flow, while retail users bear most of the profit and loss volatility.

Written by: Surf

Key Findings

The following conclusions are based on 787 million transactions from Polymarket's international market from January to June 2026, with 1,733,011 wallets, combined with data from Polymarket US.

1. The second Polymarket is rapidly gaining volume: The monthly trading volume of the U.S. market, regulated by the CFTC, increased from 5% of the international market in January to 47% in June, reaching 67% in July.
2. High-turnover categories are the fee engine: The sports and crypto markets contributed approximately 98% of the $184 million gross fees generated in the international market in the first half of the year; the crypto market generated $96.3 million in fees with about half the trading volume, surpassing the sports market's $83.5 million.
3. User numbers and trading volume are highly misaligned: Retail wallets account for about 90% of users, but bots and professional users contribute approximately 80% of the taker trading volume; only 5.9% of bot wallets completed about two-thirds of the transactions.
4. User acquisition does not rely on a single blockbuster: The largest single market for attracting new users brought in fewer than 7,000 new wallets, while the total number of new wallets was about 1.13 million; in any given month, the top 15 markets only accounted for 8% to 19% of new wallets.
5. No single market category significantly boosts platform retention: About 51% to 57% of monthly active wallets return the following month, but users often leave the category they initially entered and move to other categories on the platform.
6. The bot community overall is profitable, but the median is still at a loss: The bot sample collectively achieved about $108 million in net profit, but only 27% of wallets were profitable; among about 1.75 million wallets, only 146 maintained positive cash flow for six consecutive months.

Part One: A Panorama of Two Polymarket Markets

Polymarket US: The Second Market is Taking Shape

In the first half of 2026, Polymarket effectively became two trading venues, yet discussions mostly focus on just one. The international market, aimed at non-U.S. users, continues to operate on a chainless CLOB settled on Polygon, with a six-month unilateral trading volume reaching $17.9 billion; meanwhile, Polymarket US, which launched at the end of 2025 and is regulated by the CFTC, climbed from 5% of the international market's monthly trading volume in January to 47% in June, and reached 67% in July (approximately $2 billion against $3 billion).

The two markets share branding and basic order book mechanisms but do not share order books, user bases, or revenue structures. Like Kalshi, they use off-chain matching and a central limit order book, applying the same fee curve to takers that varies with price: fee = Θ·C·p(1−p). The difference lies in the settlement tracks: the international market publicly settles each transaction on Polygon, while the U.S. market clears through a private, regulated ledger.

When comparing across platforms, it is essential to standardize the metrics. In this article, volume refers to unilateral, taker-side, and only counted once actual trading dollars; nominal amounts and bilateral counts are typically 2 to 3 times higher. Recalculating July data with this metric, the common figures of $41 billion / $7 billion / $5 billion correspond to approximately $13.3 billion / $3 billion / $2 billion.

Figure 1｜Monthly unilateral trading volume of Polymarket's international and U.S. markets

The daily trading volume of the U.S. market increased from about $1 million at launch to $50 million to $100 million in July; daily transaction counts surpassed 1 million, and open interest once exceeded $150 million. Fees transitioned from a fixed basis point model in January to a price-sensitive formula implemented in April.

Figure 2｜Polymarket US: Daily venue-level metrics since launch

The scale of fees is also larger than estimated by community datasets: in June alone, the gross fees for takers were approximately $30 million. Based on the official rebate plan—25% returned to makers upon transaction, a full taker promotional rebate ending on April 30, and then tiered rebates based on trading volume—June's retained revenue was about $17 million, roughly double the fixed 25% assumption used by many trackers. Since the U.S. market lacks user-level data, the tiered qualifications for large takers can only reference the structure where the top 0.3% of takers in the international market contributed about 63% of the trading volume.

The Fee Economics of the International Market

What is actually being traded in the international market? Sports account for about half of the total trading volume; crypto accounts for about 30%, with the vast majority being five-minute micro-markets; world/geopolitical events account for about 15%. The concentration differences between categories are even more pronounced: the largest market in sports only accounts for 0.27% of its category, while in the science and technology category, a market asking "Will the U.S. confirm the existence of aliens before 2027?" accounts for about a quarter.

Figure 3｜Polymarket International Market: Trading volume split by market category

The international market generated approximately $184 million in gross fees in the first half of the year, but this does not account for net income after deducting maker rebates and incentives. Although the crypto market has only about half the trading volume of sports, it generated $96.3 million in fees, surpassing sports' $83.5 million; the two categories combined account for 98% of total fees. The world/geopolitical category employs a deliberate zero-fee strategy.

Figure 4｜Polymarket International Market: Fee income and effective take rate by category

High-Turnover Categories as the Fee Engine

In July, Kalshi's open interest was about 2.3 times that of Polymarket's international market, but its trading volume was about 4.4 times; the corresponding daily turnover rates were approximately 0.44× versus 0.23×. Polymarket US has the smallest capital pool but runs the fastest with a daily turnover rate of about 0.64×. The answer lies not in the platform name but in what the market directory consists of.

Figure 5｜Open interest and trading volume comparison among the three markets: Capital scale does not equal fund turnover speed

Figure 6｜Comparing Kalshi and Polymarket by category in terms of trading volume/open interest

Sports and crypto are the fastest-turning categories, while world/geopolitical events are the slowest, with daily turnover rates of only about 0.01 to 0.03×. Both international markets have approximately $200 million to $300 million in capital tied up but only generate $2 million to $3 million in daily trading, leading them to set this category as zero-fee. About 88% of the open interest in Polymarket US is concentrated in sports, explaining why it can achieve higher turnover with less capital.

Kalshi's crypto market is a clear outlier: with about $17 million in open interest corresponding to about $96 million in daily trading, the daily turnover is close to 6×, with 98% of the market durations not exceeding one hour. Polymarket's crypto turnover appears to be only 0.31× because long-dated threshold markets account for most of the open interest, while five-minute fluctuation markets account for about 90% of the trading volume but lock almost no capital; on average, each such market only locks about $2,800 in collateral.

The same category tends to have similar speeds across different platforms: the daily turnover rates for sports on Kalshi, Polymarket International, and Polymarket US are approximately 0.57×, 0.67×, and 0.64×, respectively. This is more of a characteristic of the category rather than the platform.

User Growth in Polymarket International Market

The following user analysis only covers the Polygon CTF / NegRisk contracts in the international market, with a time frame from January 1 to June 30, 2026. Both Polymarket US and Kalshi settle internally, and the publicly traded flows are anonymized, making it impossible to create wallet profiles with the same depth.

Makers and Takers: Different Groups on Both Sides of the Order Book

In the first half of the year, there were 1,733,011 wallets trading in the international market. Almost all wallets have actively consumed liquidity at least once, but less than half have actually placed limit orders. The maker side is clearly more professional and smaller; the top thousand makers provide most of the static liquidity. The demand side is also highly concentrated: about 6% of highly active wallets accounted for 80% of taker transaction volume, while one-third of wallets traded only five times or less over six months.

Figure 7｜Wallet Structure in Polymarket International Market: Overlap and Concentration of Makers and Takers

User Growth Accounting: Activity Remains Flat

User growth is less optimistic than transaction volume: the number of monthly active wallets increased from 580,000 in January to 594,000 in June, essentially flat, despite about 1.1 million wallets trading for the first time during the same period. Each month, 43% to 49% of the previous month's active wallets stopped trading, with a loss of 358,000 in April, meaning the platform must continuously replenish the funnel with new and returning wallets.

There are three important caveats here. A wallet does not equal a user; some of the so-called churn may simply be users switching to new wallets; and the churn discussed in this article only indicates wallets that have stopped trading, not accounts that have been closed or have no funds remaining.

Figure 8｜User Growth Accounting: New Users, Returning Users, Retained Users, and Churn

Where New Users Come From: Not a Single Point Explosion

When we attribute each new wallet to the market it first encountered, we can see the seasonality of the user acquisition machine: the crypto market reached about 99,000 new wallets in March, geopolitical events reached about 68,000 in January, and sports reached about 91,000 during the World Cup in June. Events create peaks, but no single market bears the entire burden of new user acquisition.

Figure 9｜New Wallets by First Entry Category

The strongest single user acquisition market in the first half of the year was "Will China invade Taiwan by the end of 2026?", but it only brought in about 7,000 new wallets. The top ten included both geopolitical events and the World Cup, interest rates, and cultural events, indicating that effective user acquisition comes from a combination of markets rather than a single blockbuster.

Figure 10｜Top Ten User Acquisition Markets with the Most New Wallets in the First Half of the Year

On a monthly basis, the top 15 user acquisition markets accounted for only 8% to 19% of the new wallets that month, with the first place never exceeding about 3%. The most concentrated months were January and June, corresponding to news from Iran, the Taiwan market, and the World Cup.

Figure 11｜Monthly User Acquisition Dispersion: Contributions from Top 15 Markets and the First Market

Retention: Users Stay on the Platform, Not Necessarily in the Original Category

About half of the monthly active wallets return the following month, with the platform's monthly retention rate around 51% to 57%; however, loyalty to a specific category is noticeably weaker. Users may leave the category they initially entered but reappear in another category, indicating that cross-category recommendations and cross-selling may be at play.

Figure 12｜Comparison of Platform Retention and Category Retention

The one-month retention for different entry categories is highly concentrated at 44% to 49%, with three-month retention around 25% to 32%. The only significant low point is the crypto entry, with one-month retention around 37%, which is about 30% lower than other categories; a possible explanation and speculation is that automated operations in crypto trading more frequently rotate new wallets, causing the apparent retention rate to be depressed.

Figure 13｜New Wallet Retention by Entry Category

User Market Participation Category Matrix: Geopolitics as the Connecting Layer

The diagonal of the matrix represents the number of independent wallets in each category, while the non-diagonal percentages indicate the proportion of smaller categories that also trade another category. Although sports and crypto have the largest two groups of users, their overlap is only 49%, indicating two audiences with substantial differences. The overlap between world/geopolitics and other categories is generally higher (except for weather), acting as a core product that connects various interests on the platform.

Figure 14｜Cross-Category User Overlap and Cross-Selling Rate

User Category Stickiness × Diffusion Chart: Different Entry Points Bring Different Quality Users

By placing entry retention and cross-category expansion on the same chart, six categories cluster in the loyalty range of 43% to 49%, but with different expansion capabilities: sports users tend to stay stable in their primary category, while science and technology attract users who explore an average of 3.6 other categories. Crypto falls in the lower left corner: one-month retention is about 37%, and expansion is also the lowest. Five-minute casinos bring transaction volume, not long-term retention or cross-category exploration.

*Figure 15｜Coordinates of Each Category in "Loyalty × Expansion"

Part Three: Market Microstructure: User Profiles, Entry Timing, and Profitability

Distribution of User Profiles: Market Category Breadth and Frequency Linked to Transaction Scale

We depict users from three perspectives: how many categories they cover, the size of individual transactions, and how frequently they trade. The broader the category coverage, the higher the average transaction volume per wallet; wallets covering all seven categories account for only about 1%, but their average taker transaction volume in the first half of the year is about $59,000, seven times that of wallets focused on a single category at $8,300.

The frequency dimension shows a typical 80/20: about 6% of "high-frequency users" contribute 79% of the transaction volume, while wallets that only trade once account for about 8% of the user base.

Figure 16｜Specialization and Participation: Category Breadth, Wallet Proportion, and Transaction Volume

In most categories, the relationship between wallets and individual markets is primarily based on one to two transactions; sports have the highest proportion of single transactions, reaching 46%. In contrast, world/geopolitics has only 20% of relationships as single transactions, indicating that users return to the same market repeatedly as news progresses.

Figure 17｜Transaction Counts for Each Wallet-Market Relationship

Three Types of Participants: Bots, Professional Users, and Retail Users

We use behavioral signals such as trading frequency, consistency of order amounts, breadth of coverage, and average ticket size for heuristic classification. This classification is not a definitive judgment of real identity; threshold changes can also affect distribution; it is more suited to answer "who is trading in what way" rather than "who exactly is who."

Bot-like wallets account for about 5.9% of users but complete about two-thirds of the transaction volume: approximately 102,000 wallets contributed $11.9 billion in transactions and 89% of transaction events; about 1.54 million retail wallets contributed $4.1 billion. Professional/informed users account for about 5%, contributing 6.6% of taker transaction volume, consistent with their characteristic of providing more liquidity and consuming fewer orders actively.

Figure 18 | Trader Demographics: Discrepancy Between Wallet Numbers and Trading Volume

In terms of categories, bots dominate the crypto and sports markets, accounting for approximately 80% and 72% of trading volume, respectively; in the middle ground where humans still have more influence over prices—geopolitics, finance, and culture—the shares of the three groups are closer.

Figure 19 | Trading Volume Shares by Category

However, the volume advantage comes from a very thin layer of bots. In terms of wallet numbers, each category is still overwhelmingly dominated by retail users; the proportion of bots in the crypto and weather markets is significantly higher, with about 5% of the population share replaced by automated behavior.

Figure 20 | Wallet Demographics by Category

Are Market Users Sensitive to Fees?

Different categories implemented fees at different times, creating a natural experiment; a zero-fee world/geopolitics can serve as a control group. The results show that after the introduction of fees, the composition of trading volume changes significantly, especially in the crypto, culture, and weather markets: the trading volume share of professional/informed users declines rapidly, while the shares of retail and bots remain relatively stable, demonstrating greater insensitivity to fees.

Figure 21 | Trading Volume Shares Before and After Fee Implementation

The change in wallet shares is much smaller than that in trading volume shares, but the pattern is consistent: the loss of professional/informed wallets in the aforementioned three categories is most pronounced. Fees change "who is increasing their bets," but do not necessarily immediately change "who is still in the game."

Figure 22 | Wallet Shares Before and After Fee Implementation

Timing of Entry: Most Arrive Late

In the lifecycle of a market, entering late is the norm, but the degree of tardiness varies across different information games. Sports and crypto are the most delayed in terms of competitive entry: the median entry point for each group falls within 92%-95% of the market lifecycle, creating significant adverse selection pressure on retail users. Culture is around 85%-90%; weather, on the other hand, enters the earliest, with a retail median of about 61% and bots around 51%, consistent with the results of markets that can be priced earlier. The weather market is also the category where professional users enter relatively latest, with a median of about 83%.

The timing analysis only includes markets visible throughout their complete lifecycle: markets settle in the first half of the year, and wallets are tracked from the first transaction, including positions entered before 2026.

Figure 23 | Weighted Entry Points of Each Group in the Market Lifecycle

The markets with the largest trading volumes in each category show a more intuitive intraday rhythm: retail user trading often spans the entire market cycle; professional/informed users and bots are more likely to suddenly increase volume when information arrives or concentrate their bets close to settlement.

Figure 24 | Daily Trading Volume of Leading Markets by Category

Who is Actually Making Money?

Summing up the cash flows of all positions in the markets settled in the first half of the year, the accounts before fees are close to zero: of about 1.97 million wallets with settled positions, 34% ultimately ended up positive. The big winners totaled approximately +$666 million, while the big losers totaled about -$530 million, resulting in a net of approximately zero across all groups. This verifies that the calculation here is based on gross PnL before fees; after deducting approximately $184 million in fees from the first half of the year, the aggregated result will turn negative.

Figure 25 | Realized PnL Before Fees by Group

Breaking it down by group, the flow of funds is very clear: retail and professional users jointly provide the counterparty for the positive returns of the bot group. Bots are the only group that is overall net profitable, totaling about +$108 million, but only 27% of bot wallets are profitable, with the median bot wallet still at a loss. Profits are carried by a few large-scale operations, and sustained profitability is extremely rare.

Professional users have the highest profitability rate, with about 42% of wallets being positive; retail is about 35%, and bots about 27%. However, professional users still incurred a total loss of about $26 million. Since this does not account for various incentives and rebates, we cannot conclude that professional users' final net earnings are negative. The retail group totaled about -$74 million.

Figure 26 | Profitability Ratios and Win Rates by Group

Figure 27 | Net Realized PnL by Group: Who Pays and Who Receives

Among approximately 1.75 million wallets, only 146 wallets maintained positive cash flow for six consecutive months; even among wallets that had previously been profitable, over 90% of profits for many were concentrated in a single month. The profitability in the prediction market resembles sporadic spikes rather than a stable stream of income.

Figure 28 | Profitability Continuity: Distribution of Months with Positive Cash Flow

Methodology and Criteria:

The data in this article is calculated by Surf AI. PnL only accounts for markets settled in the first half of 2026, and the realized results before fees are calculated based on the cash flow of wallets in these markets; maker rebates, promotional incentives, and other planned subsidies are not included in the gross PnL. Group labels are classified based on behavioral heuristics for comparing trading styles and should not be interpreted as definitive identification of the actual wallet owners.

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