Prediction Markets Too Thin for Institutions

Prediction markets still look retail on the surface, but the money already behaves more like an early, thin institutional market. The headcount is mostly casual users placing small trades, but volume is concentrated in a tiny group of whales, small hedge funds, and one to ten person algo shops. That is why the market has enough activity for data tools and arbitrage, but not yet enough depth for firms like Jane Street or Citadel to deploy serious balance sheet.

• The clearest sign of concentration is on Polymarket, where about 1.4 million users have used the platform over roughly two and a half years, but fewer than 8,000 users made more than 1,000 trades, and those power users drove about 80% of volume.
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• The current professional cohort is not big multi strategy market makers. It is smaller funds and lean HFT teams using cross venue arbitrage, backtesting, copy trading, and fast reaction bots. Dome itself says about 25% of its users use the data for backtesting, analytics, or high frequency trading.
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• This concentration is reinforced by what trades best. Sports has become the main liquidity engine because games resolve fast and run every day, so capital can be recycled quickly. By late 2025, Kalshi was doing roughly $1.1B in monthly sports volume and Polymarket about $350M, which is large for a young category but still small relative to markets that attract top tier quant firms.
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The next phase is straightforward. As more sports, financial, and hedging use cases stack up, liquidity should deepen and the participant mix should move upmarket from whales and small bots toward larger market makers and brokers. If that happens, infrastructure that aggregates venues, normalizes data, and routes orders becomes more important because thicker markets reward speed, tighter spreads, and cross platform execution.