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Guide

Understanding Liquidity in Prediction Markets

What is liquidity in prediction markets? Learn why it matters, how to measure it, and which platforms offer the deepest order books in 2026.

James Carlton
Crypto Analyst — On-Chain Flows · · 3 min read
✓ Fact-checked · 📅 Updated 1 May 2026 · 3 min read
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Key takeaway: Liquidity stands as the paramount consideration for anyone trading prediction markets. When liquidity runs deep, traders benefit from compressed bid-ask spreads, rapid order execution, and market prices that accurately reflect probabilities. Polymarket dominates the landscape with over $1.5B in total trading volume; the vast majority of rival platforms operate at substantially lower levels of market depth.

Prediction market liquidity shapes your entire trading experience — influencing both the cost of entry and the ease with which you can unwind positions. Regrettably, many newcomers prioritise market selection over liquidity assessment. This article demonstrates precisely why liquidity supersedes all other considerations.

What is liquidity?

Within financial markets, liquidity refers to the capacity to transact an asset swiftly whilst maintaining stable pricing. For prediction markets, three distinct dimensions define liquidity:

  • Depth: The quantity of contracts available at successive price tiers within the order book
  • Spread: The distance separating the maximum bid price from the minimum ask price
  • Volume: The total number of contracts traded throughout a specified timeframe

A market displaying 10,000 contracts bid at 48 cents and 10,000 offered at 50 cents demonstrates genuine liquidity. Conversely, a market with merely 50 contracts on each side separated by a 10-cent gap exhibits poor liquidity characteristics.

Why liquidity matters for traders

Insufficient liquidity erodes profitability through multiple mechanisms:

  1. Wider spreads: Transaction costs increase both when establishing and closing positions
  2. Slippage: Substantial orders push pricing unfavourably for the trader
  3. Trapped positions: Absence of willing buyers may prevent position closure prior to market settlement
  4. Price inaccuracy: Sparse trading activity prevents prices from converging toward genuine probabilities

How to measure prediction market liquidity

Evaluate these metrics before executing any trade:

  • Order book depth: PolyGram's depth chart displays the cumulative buy and sell interest at each price level
  • 24h volume: Elevated trading activity correlates with improved fill probability — especially for standard position sizes
  • Number of unique traders: Markets attracting 100+ distinct participants typically possess sufficient depth for standard retail trades
  • Spread percentage: Target markets where the bid-ask gap remains below 3 cents (3%) to minimise transaction friction

Which platforms have the most liquidity?

Platform Cumulative volume Avg. spread
Polymarket$1.5B+1-3 cents
Kalshi$500M+2-5 cents
Betfair ExchangeN/A (sports-focused)1-2% on sports
Augur/Azuro$50M+5-15 cents

How market makers create liquidity

Institutional liquidity providers simultaneously post bids and offers, capturing the spread differential whilst furnishing trading counterparties. Polymarket incentivises these providers through fee reductions and MATIC token distributions. PolyGram's proprietary liquidity engine replicates Polymarket's full order book, guaranteeing PolyGram participants access to equivalent market depth as those trading directly on Polymarket.

Tips for trading illiquid markets

  • Employ limit orders exclusively — refrain from market orders when order book depth is minimal
  • Distribute substantial orders across multiple price tiers to minimise market impact
  • Exercise patience: establish your desired price and await execution rather than accepting unfavourable fills
  • Evaluate temporal dynamics — liquidity often expands as markets approach their settlement dates

Trade on the most liquid prediction market platform. Start trading on PolyGram →

James Carlton
Crypto Analyst — On-Chain Flows

James covers DeFi research and writes for PolyGram on USDC flows, the Polymarket Polygon order book, and conditional-token mechanics.