[{"data":1,"prerenderedAt":258},["ShallowReactive",2],{"search-sections":3,"blog-what-trades-dont-tell-you-orderbook":70,"all-authors":217,"related-cat-/blog/what-trades-dont-tell-you-orderbook":249,"surround-/blog/what-trades-dont-tell-you-orderbook":251,"related-recent-/blog/what-trades-dont-tell-you-orderbook":254},[4,12,18,23,28,33,38,45,50,55,60,65],{"category":5,"date":6,"id":7,"title":8,"titles":9,"content":10,"level":11},"research","2026-04-06","/blog/market-diversity-lockin","When Do Polymarket Markets Decide? Half Wait Until the Last 15 Minutes",[],"Across Polymarket markets, the number of market makers barely affects when a market reaches certainty. What matters is whether it's a sports bet or a crypto price target. TL;DR: 50% of Polymarket markets lock in within 15 minutes of resolution. The number of different liquidity providers explains ~1% of when markets decide. The type of market (sports, crypto, politics) explains 10x more. Half of all Polymarket binary markets reach certainty within 15 minutes of resolution. Out of 397,000 resolved markets since January 2025, the median time between the last uncertain trade and the final result is 14.6 minutes. We set out to test whether having more different liquidity providers — the people placing resting orders on each side — affects how quickly a market reaches its verdict. The hypothesis: too few providers means thin price discovery, too many means sustained disagreement, and somewhere in the middle should be optimal. The data has a different story. The number of liquidity providers barely matters. What does matter — 10x more — is what the market is about.",1,{"category":5,"date":6,"id":13,"title":14,"titles":15,"content":16,"level":17},"/blog/market-diversity-lockin#the-data","The Data",[8],"397,498 resolved Polymarket binary markets, each with at least 10 trades and at least one trade on the winning outcome below 90 cents. For each market, we measure lock-in timing: how long before resolution did the winning outcome's price last dip below 90 cents? A market that locked in 5 days before resolution \"decided\" early. One that locked in 2 minutes before resolution was uncertain until the end. Half of all markets lock in within the final 15 minutes. Another 20% take 1–6 hours — a second cluster of markets that \"know\" a few hours early. The remaining 30% spread across days to weeks, with 10% locking in more than 5 days before resolution.",2,{"category":5,"date":6,"id":19,"title":20,"titles":21,"content":22,"level":17},"/blog/market-diversity-lockin#more-providers-slightly-later-lock-in","More Providers, Slightly Later Lock-in",[8],"At first glance, markets with more liquidity providers lock in faster. But that's misleading — those markets also have more trades overall (correlation: 0.96), and more trades is the real driver. To separate the two, I held trading volume constant and asked: among markets with the same amount of trading, does having more different providers change anything? Yes, but barely. Markets with 8 unique providers lock in about 4 minutes before resolution. Markets with 500 unique providers lock in about 1.7 hours before resolution. The curve rises, but across the full range of provider diversity, the difference is small in absolute terms — and it explains only about 1% of the total variation.",{"category":5,"date":6,"id":24,"title":25,"titles":26,"content":27,"level":17},"/blog/market-diversity-lockin#what-actually-matters-the-type-of-market","What Actually Matters: The Type of Market",[8],"The type of market explains 10x more than the number of liquidity providers. Sports markets lock in at the final whistle. Crypto price targets lock in when the price hits. Political markets wait for official results. Adding market-type categories to the model explains 6.8% of additional variation beyond trade count alone. Provider diversity adds just 0.6%. The chart shows signed ΔR² — the additional variance explained by provider diversity, with the sign indicating direction. Positive means more providers predicts later lock-in; negative means faster. (Raw ΔR² is always positive; we sign it to show whether diversity delays or accelerates convergence.) In sports and crypto (87% of markets), more providers weakly predicts later lock-in — consistent with more disagreement. In politics, weather, tech, and entertainment, more providers weakly predicts faster lock-in. The pooled result is positive only because sports and crypto dominate the sample.",{"category":5,"date":6,"id":29,"title":30,"titles":31,"content":32,"level":17},"/blog/market-diversity-lockin#a-single-character-bug-that-changed-the-finding","A Single-Character Bug That Changed the Finding",[8],"The most useful discovery was not about liquidity at all. To classify markets by topic, I built a keyword matcher over market titles. The first version used  (space after \"vs\") to catch sports markets. Polymarket titles mostly use \"vs.\" (period). One character. This silently misclassified ~100,000 sports markets into the \"other\" bucket, inflating it from 5% to 35% of the sample and creating a fake signal — the misclassified sports markets mixed with genuinely unclassifiable markets produced an apparent provider-diversity effect of 2.7% within \"other\" that did not exist. If you do prediction market research that uses title-based topic classification — and most empirical PM work does — this is a reminder to check your classifier against sample titles. A one-character difference in a LIKE pattern changed the headline finding of a 400K-market analysis.",{"category":5,"date":6,"id":34,"title":35,"titles":36,"content":37,"level":17},"/blog/market-diversity-lockin#what-this-means","What This Means",[8],"For traders: counting liquidity providers won't help you predict when a market converges. Watch the market type and the event schedule instead. For researchers: when a market decides is a different question from whether it's right — and the answer depends almost entirely on the domain, not the market structure. For market designers: a sports market and a political market have fundamentally different convergence dynamics. One-size-fits-all parameters may be leaving efficiency on the table.",{"category":39,"date":40,"id":41,"title":42,"titles":43,"content":44,"level":11},"market-analysis","2026-04-09","/blog/what-trades-dont-tell-you-orderbook","What Trades Don't Tell You But the Orderbook Will",[],"Polymarket fills are on-chain and complete. The orderbook isn't. If you're modeling slippage, market impact, or execution quality, you need the book — and there's no historical record of it unless someone captured it. TL;DR: Polymarket fills are on-chain and complete. The orderbook isn't — it lives on Polymarket's matching engine and there's no historical record of it anywhere unless someone captured it. If you're modeling execution quality, slippage, or market impact, you need the book, not just the fills. If you've done any serious work with Polymarket data, you've probably used the fills. They're on-chain, permanent, and complete — every matched trade is recorded on Polygon via the CTF and NegRisk exchange contracts. You can reconstruct the full trade history of any market going back to inception. What you can't reconstruct is what the book looked like between trades.",{"category":39,"date":40,"id":46,"title":47,"titles":48,"content":49,"level":17},"/blog/what-trades-dont-tell-you-orderbook#what-fills-dont-tell-you","What fills don't tell you",[42],"A fill tells you that at time T, X shares of outcome Y traded at price P. That's useful for a lot of things: price series, volume analysis, market convergence (we wrote about this here). It doesn't tell you what was sitting in the order book at T-1ms. It doesn't tell you what the best bid was before that fill came in, how deep the book was at each price level, or what the spread looked like. If the fill moved the price by 3 cents, you have no idea whether that was a 100-share book or a 10,000-share book. For researchers studying price discovery, this probably doesn't matter much. For anyone modeling execution — slippage, market impact, realistic fill simulation — it matters a lot.",{"category":39,"date":40,"id":51,"title":52,"titles":53,"content":54,"level":17},"/blog/what-trades-dont-tell-you-orderbook#why-theres-no-historical-orderbook","Why there's no historical orderbook",[42],"Polymarket's matching engine runs off-chain. The orderbook state at any moment exists on Polymarket's servers, not on the blockchain. Only the result of a match — the fill — gets settled on-chain. This means there is no canonical historical record of the orderbook. Not on Polymarket's API (no historical endpoint exists). Not on the blockchain. If no one captured it at the time, it's gone. We've been capturing continuously since November 2025. Full-resolution data is available from March 2026.",{"category":39,"date":40,"id":56,"title":57,"titles":58,"content":59,"level":17},"/blog/what-trades-dont-tell-you-orderbook#what-continuous-capture-gives-you","What continuous capture gives you",[42],"We snapshot the full orderbook across active Polymarket markets continuously and store every state. For any market, at any moment in its lifetime, you can reconstruct the full bid/ask book — every price level, every size. We interpolate to 1ms resolution using last-observation-carried-forward. On high-volume markets, the raw feed can hit 1,000 orderbook updates per second — storing and querying that at scale is non-trivial. The data ships as Parquet: , , , , each level as .",{"category":39,"date":40,"id":61,"title":62,"titles":63,"content":64,"level":17},"/blog/what-trades-dont-tell-you-orderbook#what-this-is-actually-useful-for","What this is actually useful for",[42],"Slippage modeling: Given a position size, what would your actual fill price have been? The mid-price from fills gives you a number. The orderbook gives you the right number. Market impact estimation: How much does a trade of size S move the book at different probability levels? This is only answerable if you know the book depth at the moment of entry — not after. Execution strategy research: Does it matter whether you're a maker or taker in the final hour of a contested market? With orderbook history, you can test it. Without it, you're guessing. These questions are answerable with orderbook history. They're not answerable from fills alone.",{"category":39,"date":40,"id":66,"title":67,"titles":68,"content":69,"level":17},"/blog/what-trades-dont-tell-you-orderbook#get-the-data","Get the data",[42],"Orderbook history is available on the Orderbook plan. If you're working on execution research or building a model that needs realistic fill simulation, reach out at arsenii@probalytics.io.",{"id":71,"title":42,"author":72,"body":73,"category":39,"date":40,"description":203,"draft":204,"extension":205,"featured":204,"image":206,"meta":207,"navigation":208,"path":41,"seo":209,"series":206,"seriesOrder":206,"stem":210,"tags":211,"__hash__":216},"blog/blog/what-trades-dont-tell-you-orderbook.md","Arsenii",{"type":74,"value":75,"toc":194},"minimark",[76,84,87,90,93,97,105,108,111,114,117,120,123,126,129,155,158,164,170,176,179,182],[77,78,79,83],"p",{},[80,81,82],"strong",{},"TL;DR:"," Polymarket fills are on-chain and complete. The orderbook isn't — it lives on Polymarket's matching engine and there's no historical record of it anywhere unless someone captured it. If you're modeling execution quality, slippage, or market impact, you need the book, not just the fills.",[85,86],"hr",{},[77,88,89],{},"If you've done any serious work with Polymarket data, you've probably used the fills. They're on-chain, permanent, and complete — every matched trade is recorded on Polygon via the CTF and NegRisk exchange contracts. You can reconstruct the full trade history of any market going back to inception.",[77,91,92],{},"What you can't reconstruct is what the book looked like between trades.",[94,95,47],"h2",{"id":96},"what-fills-dont-tell-you",[77,98,99,100,104],{},"A fill tells you that at time T, X shares of outcome Y traded at price P. That's useful for a lot of things: price series, volume analysis, market convergence (we wrote about this ",[101,102,103],"a",{"href":7},"here",").",[77,106,107],{},"It doesn't tell you what was sitting in the order book at T-1ms. It doesn't tell you what the best bid was before that fill came in, how deep the book was at each price level, or what the spread looked like. If the fill moved the price by 3 cents, you have no idea whether that was a 100-share book or a 10,000-share book.",[77,109,110],{},"For researchers studying price discovery, this probably doesn't matter much. For anyone modeling execution — slippage, market impact, realistic fill simulation — it matters a lot.",[94,112,52],{"id":113},"why-theres-no-historical-orderbook",[77,115,116],{},"Polymarket's matching engine runs off-chain. The orderbook state at any moment exists on Polymarket's servers, not on the blockchain. Only the result of a match — the fill — gets settled on-chain.",[77,118,119],{},"This means there is no canonical historical record of the orderbook. Not on Polymarket's API (no historical endpoint exists). Not on the blockchain. If no one captured it at the time, it's gone.",[77,121,122],{},"We've been capturing continuously since November 2025. Full-resolution data is available from March 2026.",[94,124,57],{"id":125},"what-continuous-capture-gives-you",[77,127,128],{},"We snapshot the full orderbook across active Polymarket markets continuously and store every state. For any market, at any moment in its lifetime, you can reconstruct the full bid/ask book — every price level, every size.",[77,130,131,132,135,136,140,141,140,144,140,147,150,151,154],{},"We interpolate to 1ms resolution using last-observation-carried-forward. On high-volume markets, the raw feed can hit ",[80,133,134],{},"1,000 orderbook updates per second"," — storing and querying that at scale is non-trivial. The data ships as Parquet: ",[137,138,139],"code",{},"timestamp",", ",[137,142,143],{},"outcome",[137,145,146],{},"bids",[137,148,149],{},"asks",", each level as ",[137,152,153],{},"(price, size)",".",[94,156,62],{"id":157},"what-this-is-actually-useful-for",[77,159,160,163],{},[80,161,162],{},"Slippage modeling:"," Given a position size, what would your actual fill price have been? The mid-price from fills gives you a number. The orderbook gives you the right number.",[77,165,166,169],{},[80,167,168],{},"Market impact estimation:"," How much does a trade of size S move the book at different probability levels? This is only answerable if you know the book depth at the moment of entry — not after.",[77,171,172,175],{},[80,173,174],{},"Execution strategy research:"," Does it matter whether you're a maker or taker in the final hour of a contested market? With orderbook history, you can test it. Without it, you're guessing.",[77,177,178],{},"These questions are answerable with orderbook history. They're not answerable from fills alone.",[94,180,67],{"id":181},"get-the-data",[77,183,184,185,189,190,154],{},"Orderbook history is available on the ",[101,186,188],{"href":187},"/pricing","Orderbook plan",". If you're working on execution research or building a model that needs realistic fill simulation, reach out at ",[101,191,193],{"href":192},"mailto:arsenii@probalytics.io","arsenii@probalytics.io",{"title":195,"searchDepth":196,"depth":196,"links":197},"",3,[198,199,200,201,202],{"id":96,"depth":17,"text":47},{"id":113,"depth":17,"text":52},{"id":125,"depth":17,"text":57},{"id":157,"depth":17,"text":62},{"id":181,"depth":17,"text":67},"Polymarket fills are on-chain and complete. The orderbook isn't. If you're modeling slippage, market impact, or execution quality, you need the book — and there's no historical record of it unless someone captured it.",false,"md",null,{},true,{"title":42,"description":203},"blog/what-trades-dont-tell-you-orderbook",[212,213,214,215],"prediction-markets","microstructure","polymarket","orderbook","waBvu7moYkk5Yvvp4b15ZqCnN3xJyjnOZ6kRaPgj69w",[218,234],{"id":219,"avatar":220,"bio":221,"extension":205,"github":222,"icon":223,"linkedin":206,"meta":224,"name":229,"role":230,"stem":231,"twitter":232,"website":206,"__hash__":233},"authors/authors/arsenii-petrovich.md","/images/authors/arsenii-petrovich.jpg","Building Probalytics from the ground up. Focused on data pipelines, quantitative analysis, and making prediction market data accessible.","Singulariteer","ph:user-circle-duotone",{"body":225},{"type":74,"value":226,"toc":227},[],{"title":195,"searchDepth":196,"depth":196,"links":228},[],"Arsenii Petrovich","Founder & Lead Engineer","authors/arsenii-petrovich","probalytics_io","sorFeFDBF9341JmeyEJgl_P9b0xz5bRWmYS2g5sTYDQ",{"id":235,"avatar":236,"bio":237,"extension":205,"github":238,"icon":239,"linkedin":206,"meta":240,"name":245,"role":246,"stem":247,"twitter":232,"website":206,"__hash__":248},"authors/authors/probalytics-team.md","/images/authors/probalytics-team.svg","Building the data infrastructure for prediction markets. We cover quantitative methods, market analysis, and platform insights.","Probalytics","ph:users-three-duotone",{"body":241},{"type":74,"value":242,"toc":243},[],{"title":195,"searchDepth":196,"depth":196,"links":244},[],"Probalytics Team","Research & Analytics","authors/probalytics-team","-8l8v6Nan6hkqGsqOSmTe71zbEr9sxncNxrJ2GlYtqE",[250],{"title":42,"path":41,"description":203,"date":40,"category":39},[252,206],{"title":8,"path":7,"stem":253,"children":-1},"blog/market-diversity-lockin",[255,256],{"title":42,"path":41,"description":203,"date":40,"category":39},{"title":8,"path":7,"description":257,"date":6,"category":5},"Across Polymarket markets, the number of market makers barely affects when a market reaches certainty. What matters is whether it's a sports bet or a crypto price target.",1775846413508]