Previously, PANews conducted in-depth research on prediction market strategies, and one important finding was: the greatest obstacle to whether many arbitrage strategies work may not be the mathematical formula of the strategy itself, but rather the depth of liquidity in the prediction market itself.
Recently, after Polymarket announced the launch of U.S. real estate prediction markets, this phenomenon has become even more apparent. After launch, the daily trading volume of this series of markets is only a few hundred dollars, completely lacking the anticipated activity. The actual market heat falls far short of the discussion volume on social media. This seems both laughable and abnormal, so it may be necessary for us to conduct a comprehensive investigation into prediction market liquidity to reveal several truths about liquidity in prediction markets.
PANews retrieved historical data from 295,000 markets on Polymarket to date, yielding the following results.
1. Short-term Markets: PVP Battlefields Comparable to MEME Coins
Among the 295,000 markets, 67,700 have cycles of less than 1 day, accounting for 22.9%, and 198,000 have cycles of less than 7 days, accounting for 67.7%.
Among these ultra-short-term prediction events, 21,848 are currently ongoing markets, of which 13,800 have 24-hour trading volumes of 0, accounting for approximately 63.16%. In other words, on Polymarket, a large number of short-term markets are in a state of illiquidity.
Does this state seem familiar?
During the peak MEME coin craze, thousands of MEME coins were also issued on the Solana chain, and the vast majority of those tokens similarly went unnoticed or died out in the short term.
Currently, this state is replaying in prediction markets, except that unlike 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 under $100.
In terms of categories, these short-term markets are almost entirely divided between sports and crypto price predictions. The main reason is that the judgment mechanisms for these events are relatively simple and mature, typically involving questions like “will a certain token rise or fall in 15 minutes” or “will a certain team win.” However, possibly due to liquidity being far worse compared to crypto derivatives, the crypto category is not the most popular “short-term king.”
Sports events, on the other hand, occupy absolute dominance. After analysis, the average trading volume of sports events with prediction cycles of less than 1 day on Polymarket reaches $1.32 million, while crypto only reaches $440,000. This also means that if you hope to profit by predicting short-term crypto movements in prediction markets, there may not be sufficient liquidity to support it.
2. Long-term Markets: Sedimentation Pools for Large Capital
Compared to the numerous events in short-term markets, markets with longer time cycles are far fewer in number.
On Polymarket, markets with 1-7 day cycles reach 141,000, while markets greater than 30 days total only 28,700. However, these long-term markets have accumulated the most capital. Markets greater than 30 days have average liquidity reaching $450,000, while markets within 1 day only have liquidity around $10,000. This also shows that large capital prefers to allocate in long-term predictions rather than participate in short-term gambling.
In long-term markets (greater than 30 days), aside from sports, other categories show higher average trading volumes and average liquidity. The market category that attracts the most capital is U.S. politics, with average trading volume reaching $28.17 million and average liquidity reaching $811,000. Second is the “other” category, which also performs well in attracting capital sedimentation, with average liquidity reaching $420,000 (this “other” category includes pop culture, social topics, etc.).
In crypto market predictions, capital is also more inclined toward long-term thinking, such as predicting “whether BTC will break $150,000 by year-end” or whether a certain token price will fall below a certain level within months. In prediction markets, crypto predictions are more like simple option hedging tools rather than short-term speculation tools.
3. Polarization of Sports Markets
Sports prediction is currently one of the main sources of daily active users on Polymarket, with current active numbers reaching 8,698, approximately 40%. However, from the distribution of trading volume, markets across different cycles show enormous differences. On one hand, ultra-short predictions of less than 1 day have average trading volume reaching $1.32 million, while mid-term markets (7-30 days) have average trading volume of only $400,000, and ultra-long-term markets (greater than 30 days) have average trading volume reaching $16.59 million.
From these data, it appears that users participating in sports predictions on Polymarket either pursue “instant results” or engage in “season gambling,” while mid-term event contracts are relatively less popular.
4. Real Estate Prediction Launch Facing “Cultural Mismatch”
After extensive data analysis, a superficial data result shows that prediction events with longer timeframes seem to have better liquidity. However, when this logic is applied to certain specific or more granular categories, it sometimes fails. For example, the real estate prediction we mentioned earlier, which should theoretically have relatively high certainty and prediction cycles over 30 days, and such predictions as the 2028 U.S. election results, 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 participation requires higher levels of professionalism and understanding. Currently, the market still appears to be in a “strategy break-in period” where retail participation enthusiasm can only remain observational. Of course, the natural low volatility of real estate markets also exacerbates this cold-start issue. Without frequent event-driven volatility, it reduces speculative capital enthusiasm. Under comprehensive factors, these relatively niche markets face the awkward situation where professional players have no counterparties and amateur players dare not enter.
5. “Short-term” or “Sedimentation”?
Through the above analysis, we can reclassify prediction markets into different categories: ultra-short-term markets like cryptocurrencies and sports can be called short-term markets, while categories like politics, geopolitics, and technology are more inclined toward long-term sedimentation markets.
Behind these two types of markets are different investor demographics. Short-term markets are clearly more suitable for those with smaller capital amounts or those requiring higher capital turnover rates. While “sedimentation” markets are more suitable for those with larger capital amounts and relatively higher certainty.
However, when markets are divided by transaction amount, we can see that markets with capital sedimentation capacity (over $10 million) account for 47% of total trading volume, despite having the fewest contracts, only 505. While markets with trading volumes between $100,000 to $1 million comprise the vast majority in quantity, totaling 156,000 contracts, but represent only 7.54% of trading volume. For the vast majority of prediction contracts lacking top-tier narrative capability, “zero upon launch” is the norm. Liquidity is not evenly distributed sunshine, but rather a spotlight gathered around extremely rare superevents.
6. “Geopolitics” Sector Rising
From “current active count / historical count,” one can see the growth momentum of a category. Currently, the sector with the highest growth efficiency is undoubtedly “geopolitics,” with geopolitics having only 2,873 historical event contracts, but currently active with 854, an active ratio of 29.7%, the highest among all sectors.
This data indicates that the number of new geopolitics-related contracts is currently rising rapidly, making it one of the topics most concerned by prediction market users. This can also be glimpsed from the recent frequent exposure of insider addresses related to several geopolitics-related contracts.
Overall, behind the liquidity analysis of prediction markets, whether it’s the sports sector as a “high-frequency casino” or the political sector as “macro hedging,” their core ability to capture liquidity lies in either providing instant dopamine feedback or offering deep macro gaming space. Those “chicken rib” markets lacking narrative density, with feedback cycles that are too long 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 track, value is only discovered where liquidity is abundant; where liquidity is exhausted, there are only traps.
This may be the greatest truth that data tells us about prediction markets.
AI 圈のコアリソースは技術と製品であり、あなたは何かを示す必要があります。黄仁勋はあなたが毎日彼を父さんと呼んでもGPUを分けてくれるわけではありません。仮想通貨界のコアリソースは上場権、流量、誰が先に情報を知るかです。これらはコードの中にはなく、人の手にあります。人の手にあるものは、人の方法で手に入れる必要があります。山东学越が盛んな場所ほど、人脈や情報の差に依存し、革新や技術には頼りません。何一はこのことを全く知らないかもしれません。時価総額数百万の小さなMEMEは、役員会のCEOを動かすほどではありません。しかし、これこそが問題の本質です。彼女は知る必要はありません。魚頭は自分で方向を変えます。これは本当に閨蜜コインよりもはるかに効率的です。
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 greatest obstacle to whether many arbitrage strategies work may not be the mathematical formula of the strategy itself, but rather the depth of liquidity in the prediction market itself.
Recently, after Polymarket announced the launch of U.S. real estate prediction markets, this phenomenon has become even more apparent. After launch, the daily trading volume of this series of markets is only a few hundred dollars, completely lacking the anticipated activity. The actual market heat falls far short of the discussion volume on social media. This seems both laughable and abnormal, so it may be necessary for us to conduct a comprehensive investigation into prediction market liquidity to reveal several truths about liquidity in prediction markets.
PANews retrieved historical data from 295,000 markets on Polymarket to date, yielding the following results.
1. Short-term Markets: PVP Battlefields Comparable to MEME Coins
Among the 295,000 markets, 67,700 have cycles of less than 1 day, accounting for 22.9%, and 198,000 have cycles of less than 7 days, accounting for 67.7%.
Among these ultra-short-term prediction events, 21,848 are currently ongoing markets, of which 13,800 have 24-hour trading volumes of 0, accounting for approximately 63.16%. In other words, on Polymarket, a large number of short-term markets are in a state of illiquidity.
Does this state seem familiar?
During the peak MEME coin craze, thousands of MEME coins were also issued on the Solana chain, and the vast majority of those tokens similarly went unnoticed or died out in the short term.
Currently, this state is replaying in prediction markets, except that unlike 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 under $100.
In terms of categories, these short-term markets are almost entirely divided between sports and crypto price predictions. The main reason is that the judgment mechanisms for these events are relatively simple and mature, typically involving questions like “will a certain token rise or fall in 15 minutes” or “will a certain team win.” However, possibly due to liquidity being far worse compared to crypto derivatives, the crypto category is not the most popular “short-term king.”
Sports events, on the other hand, occupy absolute dominance. After analysis, the average trading volume of sports events with prediction cycles of less than 1 day on Polymarket reaches $1.32 million, while crypto only reaches $440,000. This also means that if you hope to profit by predicting short-term crypto movements in prediction markets, there may not be sufficient liquidity to support it.
2. Long-term Markets: Sedimentation Pools for Large Capital
Compared to the numerous events in short-term markets, markets with longer time cycles are far fewer in number.
On Polymarket, markets with 1-7 day cycles reach 141,000, while markets greater than 30 days total only 28,700. However, these long-term markets have accumulated the most capital. Markets greater than 30 days have average liquidity reaching $450,000, while markets within 1 day only have liquidity around $10,000. This also shows that large capital prefers to allocate in long-term predictions rather than participate in short-term gambling.
In long-term markets (greater than 30 days), aside from sports, other categories show higher average trading volumes and average liquidity. The market category that attracts the most capital is U.S. politics, with average trading volume reaching $28.17 million and average liquidity reaching $811,000. Second is the “other” category, which also performs well in attracting capital sedimentation, with average liquidity reaching $420,000 (this “other” category includes pop culture, social topics, etc.).
In crypto market predictions, capital is also more inclined toward long-term thinking, such as predicting “whether BTC will break $150,000 by year-end” or whether a certain token price will fall below a certain level within months. In prediction markets, crypto predictions are more like simple option hedging tools rather than short-term speculation tools.
3. Polarization of Sports Markets
Sports prediction is currently one of the main sources of daily active users on Polymarket, with current active numbers reaching 8,698, approximately 40%. However, from the distribution of trading volume, markets across different cycles show enormous differences. On one hand, ultra-short predictions of less than 1 day have average trading volume reaching $1.32 million, while mid-term markets (7-30 days) have average trading volume of only $400,000, and ultra-long-term markets (greater than 30 days) have average trading volume reaching $16.59 million.
From these data, it appears that users participating in sports predictions on Polymarket either pursue “instant results” or engage in “season gambling,” while mid-term event contracts are relatively less popular.
4. Real Estate Prediction Launch Facing “Cultural Mismatch”
After extensive data analysis, a superficial data result shows that prediction events with longer timeframes seem to have better liquidity. However, when this logic is applied to certain specific or more granular categories, it sometimes fails. For example, the real estate prediction we mentioned earlier, which should theoretically have relatively high certainty and prediction cycles over 30 days, and such predictions as the 2028 U.S. election results, 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 participation requires higher levels of professionalism and understanding. Currently, the market still appears to be in a “strategy break-in period” where retail participation enthusiasm can only remain observational. Of course, the natural low volatility of real estate markets also exacerbates this cold-start issue. Without frequent event-driven volatility, it reduces speculative capital enthusiasm. Under comprehensive factors, these relatively niche markets face the awkward situation where professional players have no counterparties and amateur players dare not enter.
5. “Short-term” or “Sedimentation”?
Through the above analysis, we can reclassify prediction markets into different categories: ultra-short-term markets like cryptocurrencies and sports can be called short-term markets, while categories like politics, geopolitics, and technology are more inclined toward long-term sedimentation markets.
Behind these two types of markets are different investor demographics. Short-term markets are clearly more suitable for those with smaller capital amounts or those requiring higher capital turnover rates. While “sedimentation” markets are more suitable for those with larger capital amounts and relatively higher certainty.
However, when markets are divided by transaction amount, we can see that markets with capital sedimentation capacity (over $10 million) account for 47% of total trading volume, despite having the fewest contracts, only 505. While markets with trading volumes between $100,000 to $1 million comprise the vast majority in quantity, totaling 156,000 contracts, but represent only 7.54% of trading volume. For the vast majority of prediction contracts lacking top-tier narrative capability, “zero upon launch” is the norm. Liquidity is not evenly distributed sunshine, but rather a spotlight gathered around extremely rare superevents.
6. “Geopolitics” Sector Rising
From “current active count / historical count,” one can see the growth momentum of a category. Currently, the sector with the highest growth efficiency is undoubtedly “geopolitics,” with geopolitics having only 2,873 historical event contracts, but currently active with 854, an active ratio of 29.7%, the highest among all sectors.
This data indicates that the number of new geopolitics-related contracts is currently rising rapidly, making it one of the topics most concerned by prediction market users. This can also be glimpsed from the recent frequent exposure of insider addresses related to several geopolitics-related contracts.
Overall, behind the liquidity analysis of prediction markets, whether it’s the sports sector as a “high-frequency casino” or the political sector as “macro hedging,” their core ability to capture liquidity lies in either providing instant dopamine feedback or offering deep macro gaming space. Those “chicken rib” markets lacking narrative density, with feedback cycles that are too long 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 track, value is only discovered where liquidity is abundant; where liquidity is exhausted, there are only traps.
This may be the greatest truth that data tells us about prediction markets.