The Verdict on the 'First Prediction-Market Election': Markets Called the Democratic Sweep but Underestimated It
Democrats won control of both chambers of Congress in the November 3 midterms, an outcome that Kalshi and Polymarket had priced as the favorite. Both platforms claimed roughly 98% directional accuracy across resolved races. But the headline figures carry important caveats: much of that accuracy came from non-competitive races, independent reviewers judged the markets as roughly comparable to conventional forecasts, and analysts noted the markets underestimated the size of the Democratic wave. The New York Times found prediction markets fared about the same as election forecasts; one economist gave them a 'B.' Kalshi's midterm volume reached $2.5 billion, nearly double the 2024 cycle.
Democrats won control of both the Senate and the House of Representatives in the November 3, 2026 midterm elections, delivering the outcome that prediction markets had favored throughout the fall. On the eve of the vote, Kalshi gave Democrats a 74% chance of winning the Senate and 94% for the House; Polymarket priced the Senate at 73%. The markets had been directionally correct for months, moving from a Republican-favored position when the 2026 cycle opened in late 2024 to a solidly Democratic position by the autumn, driven by rising energy prices and declining presidential approval. The result validated the markets' top-line forecast: they called the Democratic sweep, and they called it earlier and more confidently than much of the traditional commentary.
Both platforms made strong accuracy claims. Kalshi said the candidates its traders favored won or led in roughly 98% of resolved races; Polymarket put its figure at 98.4% of settled contests pointing to the correct winner, measured against the day before the election. Earlier in the count, Kalshi's figures were lower — around 95% for House races and 94% for Senate races — and rose as more races were called. These are impressive numbers on their face, and the platforms have used them to argue that prediction markets are a superior forecasting tool that aggregates information more effectively than polls or pundits. For a sector defending its legitimacy against state enforcement and arguing that its products serve a genuine informational purpose, a successful midterm forecast is a valuable piece of evidence.
The headline accuracy figures require context that complicates the platforms' framing. Much of the 98% directional accuracy came from non-competitive races — contests that were never in doubt and that any forecasting method, including a simple partisan-lean model, would have called correctly. The meaningful test of a forecasting tool is how well it prices the close races, and on that measure the markets' performance was more ordinary. The New York Times analysis found that prediction markets fared about the same as conventional election forecasts through most of the campaign, and an economist who studies the markets gave them a grade of 'B.' More pointedly, analysts noted that the markets underestimated the size of the Democratic wave: they correctly identified Democrats as favorites but priced a narrower result than actually materialized, missing the magnitude even as they got the direction right. A forecast that calls the winner but misprices the margin is useful but not oracular.
The accuracy debate matters because it bears directly on the sector's central legitimacy argument. The platforms contend that prediction markets are valuable because they produce accurate, real-time probability estimates that serve the public interest — an argument that distinguishes them from gambling and supports their claim to federal financial regulation rather than state gambling regulation. If the markets are genuinely more accurate than alternatives, that argument is strong; if they are roughly comparable to existing forecasts, the informational-value claim is weaker, and the markets look more like a betting product with a forecasting veneer. The 2026 midterms, the first major US election conducted with prediction markets operating at full scale, produced a genuinely mixed verdict: the markets worked, but not dramatically better than what already existed. Kalshi's midterm volume reached $2.5 billion, nearly double the $1.3 billion of the 2024 cycle, and Polymarket recorded nearly $700 million across its US and international platforms — confirming the commercial success of election markets even as the forecasting-superiority claim received only partial support. The 'first prediction-market election' demonstrated that the markets are accurate enough to be taken seriously and popular enough to be commercially significant, but not so superior to conventional forecasting that the informational-value argument settles the regulatory debate on its own.
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