Deep Dive into 290,000 Market Data Points: Revealing 6 Truths About Polymarket Liquidity

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Author: Frank, PANews

Previously, PANews conducted in-depth research on strategies in prediction markets, one of the key findings being: whether many arbitrage strategies can succeed is likely not limited by their mathematical formulas, but by the liquidity depth of the prediction market itself.

Recently, after Polymarket announced the launch of the U.S. real estate prediction market, this phenomenon has become even more apparent. Since launch, the daily trading volume of these markets has only been a few hundred dollars, far from the expected lively activity. The actual market interest is much lower than the discussion on social media. This seems absurd and abnormal, so it may be necessary to conduct a comprehensive investigation into the liquidity of prediction markets to reveal some truths about liquidity within these markets.

PANews retrieved historical data from 295,000 markets on Polymarket and derived the following results.

1. Short-term Markets: A PVP Battlefield Comparable to MEME Coins

Among the 295,000 markets, 67,700 have durations less than 1 day, accounting for 22.9%, and 198,000 have durations less than 7 days, accounting for 67.7%.

Within these ultra-short-term prediction events, 21,848 are currently active markets, with 13,800 having 24-hour trading volumes of zero, accounting for about 63.16%. In other words, on Polymarket, many short-term markets are in a state of no liquidity.

Does this situation seem familiar?

During the peak of MEME coin frenzy, thousands of MEME coins were issued on the Solana chain, most of which were ignored or quickly faded away.

Currently, this state is also reflected in prediction markets, but unlike MEME coins, the event lifecycle in prediction markets is certain, whereas MEME coin lifecycles are unknown.

In terms of liquidity, over half of these short-term events have less than $100 in liquidity.

In terms of categories, these short-term markets are almost entirely dominated by sports and crypto predictions. The main reason is that these events have relatively simple and mature judgment mechanisms, such as a token’s 15-minute price change or a team’s victory. However, compared to crypto derivatives, the liquidity is so poor that crypto categories are not the hottest “short-term kings.”

Sports events, on the other hand, dominate completely. Analysis shows that the average trading volume for sports events with durations less than 1 day on Polymarket reaches $1.32 million, while crypto events average only $44,000. This indicates that if you hope to profit by predicting short-term movements of cryptocurrencies in prediction markets, there may not be enough liquidity to support it.

2. Long-term Markets: A Pool for Large Capital

Compared to the numerous short-term event contracts, markets with longer durations are much fewer.

On Polymarket, there are 141,000 markets with durations of 1 to 7 days, while markets longer than 30 days total only 28,700. However, these long-term markets accumulate the most funds. The average liquidity for markets longer than 30 days reaches $450,000, while those within 1 day have only about $10,000 in liquidity. This suggests that large capital prefers to position itself in long-term predictions rather than participate in short-term speculation.

In long-term markets (over 30 days), aside from sports, other categories show higher average trading volumes and liquidity. The most popular category for funds is U.S. politics, with an average trading volume of $28.17 million and an average liquidity of $811,000. The “Others” category, which includes pop culture, social topics, etc., also attracts significant capital, with an average liquidity of $420,000.

In crypto prediction markets, funds tend to favor long-term bets, such as whether Bitcoin will break $150,000 by year-end or whether a token’s price will fall below a certain level in a few months. In prediction markets, crypto predictions resemble simple options hedging tools rather than short-term speculative instruments.

3. Polarization in Sports Markets

Sports predictions are currently one of the main sources of daily active users on Polymarket, with about 8,698 active markets, roughly 40%. However, the trading volume distribution shows a huge gap across different durations. Short-term (less than 1 day) predictions have an average trading volume of $1.32 million, while mid-term (7–30 days) markets average only $400,000, and long-term (over 30 days) markets reach an average of $16.59 million.

These data suggest that users participating in sports predictions on Polymarket are either seeking “instant results” or engaging in “season-long bets,” with mid-term event contracts being less popular.

4. Real Estate Predictions Face “Mismatch”

After extensive data analysis, a superficial conclusion is that longer-term prediction events seem to have better liquidity. However, when examining specific or more niche categories, this trait sometimes fails. For example, the real estate prediction market, which is a relatively high-certainty market with a duration over 30 days, is an example. Conversely, predictions like the 2028 U.S. presidential election outperform in liquidity and trading volume.

This may reflect the “cold start dilemma” faced by new asset classes (especially niche, specialized categories). Unlike simple event predictions, real estate market participation requires higher expertise and knowledge. Currently, the market appears to be in a “strategy refinement period,” with retail participation mainly observing. Moreover, the inherently low volatility of real estate markets, lacking frequent event-driven fluctuations, further dampens speculative interest. Overall, these relatively niche markets face the dilemma of a lack of professional counterparties and amateur players’ reluctance to enter.

5. “Short-term” or “Long-term Accumulation”?

Based on the above analysis, we can categorize prediction markets into two types: ultra-short-term markets like cryptocurrencies and sports, which can be called short-term markets, and categories like politics, geopolitics, and technology, which are more long-term accumulation markets.

These two types of markets correspond to different investor groups. Short-term markets are more suitable for small capital or those needing high capital turnover, while “accumulation” markets are better suited for large capital and higher certainty.

However, when dividing markets by trading volume, markets with the capacity for capital accumulation (over $10 million) account for 47% of total trading volume, despite only having 505 contracts. Conversely, markets with trading volumes between $10,000 and $100,000 make up the majority in number, with 156,000 contracts, but only account for 7.54% of total volume. For most prediction contracts lacking top-tier narratives, “going live and then zeroing out” is the norm. Liquidity is not evenly distributed but concentrated around a few super-events.

6. The Rise of the “Geopolitics” Sector

From the “current active / historical total” ratio, the growth momentum of a category can be observed. The fastest-growing sector is undoubtedly “geopolitics,” with only 2,873 historical event contracts but 854 active ones, accounting for 29.7%, the highest among all sectors.

This data indicates that the number of new “geopolitics” contracts is rapidly increasing, making it one of the most concerned topics among prediction market users. This is also reflected in recent frequent insider address disclosures related to geopolitics contracts.

Overall, behind the liquidity analysis of prediction markets, whether as a “high-frequency casino” like sports or as a “macro hedge” like politics, the core of capturing liquidity lies in either providing instant dopamine feedback or offering deep macro strategic space. Markets lacking narrative density, with overly long feedback cycles and no volatility, are doomed to struggle in a decentralized order book.

For participants, Polymarket is evolving from a “predict everything” utopia into an extremely professional financial tool. Recognizing this is more important than blindly searching for the next “100x prediction.” In this arena, only places with abundant liquidity will reveal value; where liquidity is scarce, traps await.

This may be the greatest truth about prediction markets that data reveals to us.