Prediction Markets Adopting Sportsbook Infrastructure
Kurush Dubash, CEO of Dome, on unified API for prediction markets
The important point is that prediction markets are starting to inherit sportsbook infrastructure logic, not just sportsbook demand. In sportsbooks, operators compare the same game price across many books to set safer odds on parlays and other bundled bets. Dome is positioning prediction markets for the same workflow, where builders and trading desks look across Kalshi, Polymarket, and newer venues to price contracts, route orders, and avoid stale lines.
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This matters because the biggest immediate use case is not a retail bettor hunting one obvious arbitrage. It is a house, market maker, or analytics tool ingesting many prices on the same event so its own probability estimate is less noisy and its quoted price is less likely to be wrong.
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The comparison to sportsbooks is especially strong in sports. Dome says sports already make up a large share of activity on Kalshi and Polymarket, and Kalshi has even pushed into same game parlays, which are among the highest margin products in traditional sportsbooks because bad pricing compounds across legs.
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The deeper product implication is that aggregation becomes a picks and shovels layer. Kalshi runs a regulated, closed database model, while Polymarket is crypto native and onchain. A unified API that normalizes both lets builders treat the event itself as the product, instead of hand coding every venue separately.
From here, prediction markets are likely to look more like electronic trading infrastructure and less like standalone consumer apps. As more sportsbooks, brokerages, and vertical operators launch contracts, the winners in infrastructure will be the firms that can merge fragmented liquidity, standardize prices, and become the default routing layer behind many front ends.