This article analyzes the historical data of approximately 300,000 markets on Polymarket, revealing the true state of liquidity in prediction markets: short-term markets like MEME coins lack liquidity, long-term markets become pools of large capital, and sports markets show polarization.
(Background: Polymarket refused to pay out the winnings for the “U.S. invasion of Venezuela” bet)
(Additional context: Can we track the next insider trader on Polymarket? Yes, and the threshold is not high)

Table of Contents

• 1. Short-term markets: PVP battleground comparable to MEME coins
• 2. Long-term markets: pools of big capital
• 3. Polarization in sports markets
• 4. Real estate prediction faces “culture shock”
• 5. “Short-term” or “Long-term”?
• 6. “Geopolitical” sector on the rise

Previously, PANews conducted an in-depth study on prediction market strategies, one key finding being: the biggest obstacle to the effectiveness of many arbitrage strategies may not be the mathematical formulas but the liquidity depth of the prediction markets themselves.

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 lively scene expected. The actual market activity is much lower than the discussion on social media. This seems absurd and abnormal, prompting us to conduct a comprehensive investigation into the liquidity of prediction markets to uncover some truths about liquidity in these markets.

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

1. Short-term markets: PVP battleground comparable to MEME coins

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

Within these ultra-short-term prediction events, 21,848 are ongoing markets, of which 13,800 have a 24-hour trading volume of zero, about 63.16%. In other words, on Polymarket, there are many short-term markets in a state of no liquidity.

Does this situation seem familiar?

At the peak of MEME coin frenzy, thousands of MEME coins were issued on Solana, most of which were ignored or quickly failed.

Currently, this state is also reflected in prediction markets, but compared to MEME coins, the event life cycle in prediction markets is definite, whereas MEME coins have an unknown lifespan.

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

Categorically, 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 which team will win. However, perhaps due to the extremely poor liquidity compared to crypto derivatives, the crypto category is not the most popular “short-term king.”

Sports events, on the other hand, dominate absolutely. Analysis shows that prediction cycles under 1 day in sports markets have an average trading volume of $1.32 million, while crypto markets only average $44,000. This indicates that if you hope to profit by predicting short-term crypto price movements in prediction markets, there may not be enough liquidity to support it.

2. Long-term markets: pools of big capital

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

On Polymarket, markets with a cycle of 1~7 days number 141,000, while those over 30 days only 28,700. However, these long-term markets accumulate the most capital. The average liquidity for markets over 30 days reaches $450,000, while those within 1 day have only about $10,000. This indicates that big 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 capital-intensive category is U.S. politics, with an average trading volume of $281.7 million and an average liquidity of $811,000. The “Others” category also attracts good capital, with an average liquidity of $420,000 (covering pop culture, social topics, etc.).

In crypto prediction markets, funds also lean toward long-term bets, such as predicting 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. Crypto predictions tend to serve more as simple options hedging tools rather than short-term speculation.

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, looking at the distribution of trading volume, there are huge differences across cycles. On one hand, ultra-short-term predictions under 1 day have an average trading volume of $1.32 million; on the other hand, mid-term (7~30 days) markets average only $400,000, while long-term markets (over 30 days) reach an average of $16.59 million.

From these data, users participating in sports predictions on Polymarket tend to either pursue “immediate results” or engage in “season-long bets,” with mid-term event contracts being less popular.

4. Real estate prediction faces “culture shock”

After extensive data analysis, a superficial conclusion is that longer-term prediction events seem to have better liquidity. But when this logic is applied to specific or more subdivided categories, this trait sometimes fails. For example, the real estate prediction mentioned earlier is a relatively high-certainty market with a cycle over 30 days. Conversely, predictions like the 2028 U.S. presidential election results lead the market in liquidity and trading volume.

This may reflect the “cold start dilemma” faced by new asset classes (especially niche, highly specialized categories). Unlike simple event predictions, real estate market participation requires higher professionalism and cognition. Currently, the market is still in a “strategy refinement period,” with retail participation mainly spectating. Moreover, the inherently low volatility of real estate markets further exacerbates this cold start problem—without frequent event-driven volatility, speculative enthusiasm diminishes. Combining these factors, such relatively niche markets face an awkward situation where professional players have no counterparties, and amateurs dare not enter.

5. “Short-term” or “Long-term”?

Based on the above analysis, we can reclassify prediction markets: markets like crypto and sports, with ultra-short cycles, can be called short-term markets, while categories like politics, geopolitics, and technology lean toward long-term, accumulated markets.

Behind these two types of markets are different investor groups. Short-term markets are more suitable for small capital or those needing higher capital turnover. “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, though they only have 505 contracts. Markets with trading volumes between $100,000 and $1 million constitute the majority in number, with 156,000 contracts, but only 7.54% of total trading 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. “Geopolitical” sector on the rise

From the ratio of “current active number / total historical number,” we see the growth momentum of a category. The fastest-growing sector is undoubtedly “geopolitics.” There are only 2,873 historical geopolitical event contracts, but currently 854 are active, with an active ratio as high as 29.7%, the highest among all sectors.

This data indicates that the number of new geopolitical contracts is rapidly increasing, making it one of the hottest topics among prediction market users. This can also be glimpsed from recent frequent insider addresses exposed in several “geopolitical” related contracts.

Overall, behind the liquidity analysis of prediction markets, whether as “high-frequency gambling” in sports or as “macro hedging” in politics, the core ability to capture liquidity lies in either providing immediate dopamine feedback or offering deep macro strategic space. Markets lacking narrative density, with feedback cycles that are too long and without volatility, are destined to struggle to survive in a decentralized order book.

For participants, Polymarket is evolving from a “predict everything” utopia into highly specialized financial tools. Recognizing this is more important than blindly seeking the next “100x prediction.” In this arena, only places with abundant liquidity will have value discovered; where liquidity is scarce, traps await.

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