Previously, PANews conducted in-depth research on prediction market strategies, and one important finding was: the biggest obstacle to whether many arbitrage strategies work may not be the mathematical formula of the strategy itself, but rather the liquidity depth of the prediction market itself.
Recently, after Polymarket announced the launch of US real estate prediction markets, this phenomenon seems even more apparent. After launch, daily trading volume for this series of markets is only a few hundred dollars, far from the expected activity. The real market heat is far below the discussion heat 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 several truths about liquidity in prediction markets.
PANews retrieved historical data from 295,000 markets on Polymarket to date and obtained the following results.
Short-term Markets: PVP Battlegrounds Comparable to MEME Coins
Among the 295,000 markets, 67,700 have cycles less than 1 day, accounting for 22.9%, and 198,000 have cycles less than 7 days, accounting for 67.7%.
Among these ultra-short-term prediction events, 21,848 are currently active markets, of which 13,800 have 0 trading volume in 24 hours, accounting for approximately 63.16%. In other words, on Polymarket, there are a large number of short-term markets in a state of illiquidity.
Does this state seem familiar?
During the peak mania for MEME coins, tens of thousands of MEME coins were issued on the Solana chain, and the vast majority of these tokens were similarly ignored or died out in the short term.
Currently, this state is repeating in prediction markets, except that compared to MEME coins, the event lifecycle of prediction markets is determined, while the lifecycle of MEME coins is unknown.
In terms of liquidity, more than half of these short-term events have liquidity of less than $100.
In terms of categories, these short-term markets are almost monopolized by sports and cryptocurrency price predictions. The main reason is that the judgment mechanisms for these events are relatively simple and mature, typically questions like whether a token rises or falls in 15 minutes or whether a team wins. However, possibly because the liquidity is far worse compared to crypto derivatives, the crypto category is not the hottest “short-term king.”
Sports events occupy absolute dominance. After analysis, sports events with prediction cycles less than 1 day on Polymarket have an average trading volume of $13.2 million, while crypto only has $440,000. This also means that if you hope to profit by predicting short-term cryptocurrency movements in prediction markets, there may not be sufficient liquidity to support it.
Long-term Markets: Sedimentation Pools for Large Capital
Compared to short-term markets with numerous event contracts and relatively short time cycles, markets with longer time cycles have far fewer numbers.
On Polymarket, there are 141,000 markets with cycles of 1-7 days, while those greater than 30 days are only 28,700. However, these long-term markets have accumulated the most capital. Markets greater than 30 days have average liquidity of $450,000, while those less than 1 day have only around $10,000 in liquidity. This shows that large capital prefers to be deployed in long-term predictions rather than participate in short-term gambling.
Among long-term markets (greater than 30 days), except for sports, other categories show higher average trading volume and average liquidity. The market category that attracts the most capital is US political prediction, with average trading volume of $28.17 million and average liquidity of $811,000. Second is the “other” category, which also performs well in attracting capital sedimentation with average liquidity of $420,000 (this “other” category covers popular culture, social topics, etc.).
In crypto market prediction, capital also leans toward long-term investing, such as predicting “whether BTC will break $150,000 by year-end” or whether a token price will fall below a certain level within months. In prediction markets, crypto prediction is more like a simple options hedging tool rather than a short-term speculation tool.
Polarization of Sports Markets
Sports predictions are currently one of the main daily active contributors on Polymarket, with current active numbers reaching 8,698, approximately 40%. However, looking at the distribution of trading volume, sports markets across different cycles show enormous disparities. On one hand, ultra-short-term predictions less than 1 day have average trading volume of $13.2 million, on the other hand mid-term (7-30 days) markets have average trading volume of only $400,000, while ultra-long-term markets (greater than 30 days) have average trading volume of $16.59 million.
From these data, it appears that users participating in sports predictions on Polymarket either pursue “instant results” or engage in “season grand betting,” with mid-term event contracts being less popular.
Real Estate Prediction Launch Facing “Cultural Mismatch”
After extensive data analysis, one apparent result is that prediction events with longer time horizons seem to have better liquidity. But sometimes when this logic is applied to specific or more granular categories, this characteristic breaks down. For example, the real estate prediction mentioned earlier, which should theoretically have relatively high certainty and prediction cycles greater than 30 days. In contrast, predictions about the outcome of the 2028 US election lead the entire market in both liquidity and trading volume.
This may reflect the “cold start dilemma” that new asset classes (especially niche, specialized categories) may face. Unlike simple, intuitive event predictions, real estate market participants require higher expertise and knowledge. Currently, the market still appears to be in a “strategy integration period” where retail participation enthusiasm only stays at the observation level. Of course, the naturally low volatility of real estate markets also exacerbates this cold start problem. Without frequent event-driven fluctuations, it reduces speculative capital enthusiasm. Under these combined factors, these relatively niche markets face the awkward situation where professional players have no counterparties and amateur players dare not enter.
“Short-term” or “Sedimentation”?
Through the above analysis, we can re-categorize different classifications of prediction markets, where ultra-short-term markets like cryptocurrencies and sports can be called short-term markets, while categories like politics, geopolitics, and technology lean more toward long-term sedimentation markets.
Behind these two types of markets are different investor groups. Short-term markets are obviously more suitable for those with small capital amounts or higher capital turnover requirements. While “sedimentation” markets are more suitable for those with large capital amounts and relatively higher certainty.
However, when markets are divided by transaction amount, markets with capital sedimentation capacity (greater than $10 million) represent 47% of total trading volume, although their contract numbers are the smallest, only 505. Markets with trading volume between $10,000 and $1 million account for the vast majority in quantity with total contracts reaching 156,000, but trading volume is only 7.54%. For the vast majority of prediction contracts lacking top-tier narrative capability, “going to zero upon launch” is the norm. Liquidity is not evenly distributed sunshine, but rather spotlights concentrated around a tiny number of mega events.
“Geopolitics” Sector Rising
From “current active numbers / historical numbers,” one can see the growth momentum of a category. Currently, the sector with the highest growth efficiency is undoubtedly “geopolitics,” with only 2,873 historical total event contracts, but current active numbers reach 854, with an active rate of 29.7%, the highest among all sectors.
This data suggests that currently, new contracts in the “geopolitics” category are rising rapidly and are among the topics users are most concerned about in prediction markets. This can be partially glimpsed from recent “geopolitics”-related contracts frequently revealing insider addresses.
Overall, behind the liquidity analysis of prediction markets, whether it’s the sports sector as a “high-frequency casino” or the political sector as a “macro hedge,” the core of their ability to capture liquidity is either to provide immediate dopamine feedback or to provide deep macro gaming space. Those “tasteless” markets lacking narrative density, with overly long feedback cycles and lacking volatility, are destined to struggle to survive in decentralized order books.
For participants, Polymarket is evolving from a utopia of “predicting everything” into an extremely specialized financial tool. Recognizing this is more important than blindly seeking the next “100x prediction.” In this sector, value is only discovered where liquidity is abundant; where liquidity is depleted, only traps remain.
This may well be the greatest truth about prediction markets that the data tells us.
深掘29万件市場データ：Polymarketの流動性に関する6つの真実
Author: Frank, PANews
Previously, PANews conducted in-depth research on prediction market strategies, and one important finding was: the biggest obstacle to whether many arbitrage strategies work may not be the mathematical formula of the strategy itself, but rather the liquidity depth of the prediction market itself.
Recently, after Polymarket announced the launch of US real estate prediction markets, this phenomenon seems even more apparent. After launch, daily trading volume for this series of markets is only a few hundred dollars, far from the expected activity. The real market heat is far below the discussion heat 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 several truths about liquidity in prediction markets.
PANews retrieved historical data from 295,000 markets on Polymarket to date and obtained the following results.
Among the 295,000 markets, 67,700 have cycles less than 1 day, accounting for 22.9%, and 198,000 have cycles less than 7 days, accounting for 67.7%.
Among these ultra-short-term prediction events, 21,848 are currently active markets, of which 13,800 have 0 trading volume in 24 hours, accounting for approximately 63.16%. In other words, on Polymarket, there are a large number of short-term markets in a state of illiquidity.
Does this state seem familiar?
During the peak mania for MEME coins, tens of thousands of MEME coins were issued on the Solana chain, and the vast majority of these tokens were similarly ignored or died out in the short term.
Currently, this state is repeating in prediction markets, except that compared to MEME coins, the event lifecycle of prediction markets is determined, while the lifecycle of MEME coins is unknown.
In terms of liquidity, more than half of these short-term events have liquidity of less than $100.
In terms of categories, these short-term markets are almost monopolized by sports and cryptocurrency price predictions. The main reason is that the judgment mechanisms for these events are relatively simple and mature, typically questions like whether a token rises or falls in 15 minutes or whether a team wins. However, possibly because the liquidity is far worse compared to crypto derivatives, the crypto category is not the hottest “short-term king.”
Sports events occupy absolute dominance. After analysis, sports events with prediction cycles less than 1 day on Polymarket have an average trading volume of $13.2 million, while crypto only has $440,000. This also means that if you hope to profit by predicting short-term cryptocurrency movements in prediction markets, there may not be sufficient liquidity to support it.
Compared to short-term markets with numerous event contracts and relatively short time cycles, markets with longer time cycles have far fewer numbers.
On Polymarket, there are 141,000 markets with cycles of 1-7 days, while those greater than 30 days are only 28,700. However, these long-term markets have accumulated the most capital. Markets greater than 30 days have average liquidity of $450,000, while those less than 1 day have only around $10,000 in liquidity. This shows that large capital prefers to be deployed in long-term predictions rather than participate in short-term gambling.
Among long-term markets (greater than 30 days), except for sports, other categories show higher average trading volume and average liquidity. The market category that attracts the most capital is US political prediction, with average trading volume of $28.17 million and average liquidity of $811,000. Second is the “other” category, which also performs well in attracting capital sedimentation with average liquidity of $420,000 (this “other” category covers popular culture, social topics, etc.).
In crypto market prediction, capital also leans toward long-term investing, such as predicting “whether BTC will break $150,000 by year-end” or whether a token price will fall below a certain level within months. In prediction markets, crypto prediction is more like a simple options hedging tool rather than a short-term speculation tool.
Sports predictions are currently one of the main daily active contributors on Polymarket, with current active numbers reaching 8,698, approximately 40%. However, looking at the distribution of trading volume, sports markets across different cycles show enormous disparities. On one hand, ultra-short-term predictions less than 1 day have average trading volume of $13.2 million, on the other hand mid-term (7-30 days) markets have average trading volume of only $400,000, while ultra-long-term markets (greater than 30 days) have average trading volume of $16.59 million.
From these data, it appears that users participating in sports predictions on Polymarket either pursue “instant results” or engage in “season grand betting,” with mid-term event contracts being less popular.
After extensive data analysis, one apparent result is that prediction events with longer time horizons seem to have better liquidity. But sometimes when this logic is applied to specific or more granular categories, this characteristic breaks down. For example, the real estate prediction mentioned earlier, which should theoretically have relatively high certainty and prediction cycles greater than 30 days. In contrast, predictions about the outcome of the 2028 US election lead the entire market in both liquidity and trading volume.
This may reflect the “cold start dilemma” that new asset classes (especially niche, specialized categories) may face. Unlike simple, intuitive event predictions, real estate market participants require higher expertise and knowledge. Currently, the market still appears to be in a “strategy integration period” where retail participation enthusiasm only stays at the observation level. Of course, the naturally low volatility of real estate markets also exacerbates this cold start problem. Without frequent event-driven fluctuations, it reduces speculative capital enthusiasm. Under these combined factors, these relatively niche markets face the awkward situation where professional players have no counterparties and amateur players dare not enter.
Through the above analysis, we can re-categorize different classifications of prediction markets, where ultra-short-term markets like cryptocurrencies and sports can be called short-term markets, while categories like politics, geopolitics, and technology lean more toward long-term sedimentation markets.
Behind these two types of markets are different investor groups. Short-term markets are obviously more suitable for those with small capital amounts or higher capital turnover requirements. While “sedimentation” markets are more suitable for those with large capital amounts and relatively higher certainty.
However, when markets are divided by transaction amount, markets with capital sedimentation capacity (greater than $10 million) represent 47% of total trading volume, although their contract numbers are the smallest, only 505. Markets with trading volume between $10,000 and $1 million account for the vast majority in quantity with total contracts reaching 156,000, but trading volume is only 7.54%. For the vast majority of prediction contracts lacking top-tier narrative capability, “going to zero upon launch” is the norm. Liquidity is not evenly distributed sunshine, but rather spotlights concentrated around a tiny number of mega events.
From “current active numbers / historical numbers,” one can see the growth momentum of a category. Currently, the sector with the highest growth efficiency is undoubtedly “geopolitics,” with only 2,873 historical total event contracts, but current active numbers reach 854, with an active rate of 29.7%, the highest among all sectors.
This data suggests that currently, new contracts in the “geopolitics” category are rising rapidly and are among the topics users are most concerned about in prediction markets. This can be partially glimpsed from recent “geopolitics”-related contracts frequently revealing insider addresses.
Overall, behind the liquidity analysis of prediction markets, whether it’s the sports sector as a “high-frequency casino” or the political sector as a “macro hedge,” the core of their ability to capture liquidity is either to provide immediate dopamine feedback or to provide deep macro gaming space. Those “tasteless” markets lacking narrative density, with overly long feedback cycles and lacking volatility, are destined to struggle to survive in decentralized order books.
For participants, Polymarket is evolving from a utopia of “predicting everything” into an extremely specialized financial tool. Recognizing this is more important than blindly seeking the next “100x prediction.” In this sector, value is only discovered where liquidity is abundant; where liquidity is depleted, only traps remain.
This may well be the greatest truth about prediction markets that the data tells us.