Kalshi Hits $2.5B Midterm Volume, Nearly Double 2024

Kalshi posts more than $2.5 billion in midterm trading

Prediction-market operator Kalshi reported over $2.5 billion in trading volume on its 2026 U.S. midterm election markets, nearly doubling the roughly $1.3 billion recorded across the 2024 election cycle. The surge highlights growing interest in election markets and the role of crypto-native and derivatives-style platforms in aggregating public sentiment ahead of major political events.

What the headline numbers mean

Using rounded company figures, Kalshi's midterm volume represents an increase of about 92% versus the prior cycle. That comparison spans different contests: 2024 included a presidential election, while 2026 focused on congressional, state and local races. Still, the sharp rise underscores expanding participation and liquidity in prediction markets, a sector increasingly connected to broader crypto and financial-market activity.

Market accuracy and resolved races

Kalshi's initial tally showed market favorites winning 479 of 487 resolved races by 6:00 a.m. ET on Nov. 4, covering House, Senate and gubernatorial contests alongside attorney general, lieutenant governor and secretary of state races. The platform reported 356 winning favorites across 360 House races, 32 of 33 Senate contests, and 33 of 34 gubernatorial elections. Eight favorites lost across the full count, producing an overall success rate near 98.4%, rounded to 98% in the company announcement.

Markets that moved on election night

Kalshi's live event feed documented how contract prices shifted as ballots were counted. At 6:55 p.m. ET the probability for Democratic House control stood at 97.2%. The site registered a 99% chance of a Democratic House majority by 8:10 p.m. ET and a 99% probability of Democratic Senate control at 9:00 p.m. ET. Individual market updates included moments when Republican incumbent Greg Abbott lost favored status in the Texas governor's race at 8:06 p.m., and later entries showing a 99% probability for James Talarico in the Texas Senate entry at 9:35 p.m., Annie Andrews in South Carolina at 10:10 p.m., and a 99% projection for Texas gubernatorial challenger Gina Hinojosa at 11:35 p.m.

Kalshi emphasized that these are market projections, not official race calls or contract settlements. As with any prediction market, prices reflect trader expectations and liquidity, and can shift quickly as real-world returns arrive.

Research: improving forecasts and Brier scores

A Kalshi Research working paper, authored by Nicole Kagan and Rubens Baiocchi, tracked forecasts for races called by 6:26 a.m. ET on Nov. 4. The study measured directional accuracy from three months before voting through poll closure and found accuracy increased from 93.8% to 98.2% over that period, a gain of 4.4 percentage points.

Why Brier scores matter

Alongside directional accuracy, the analysis reported improved Brier scores, which quantify the difference between forecast probabilities and actual outcomes. Scores fell from 0.040 to 0.016; lower values indicate better-calibrated probability estimates. The paper notes that simply counting winning favorites masks confidence: a forecast priced at 51% and one priced at 95% both count as correct if the favorite wins, but their calibration differs substantially.

The study matched prices available at specific measurement times and anchored forecasts to voting hours, addressing the fact that election-contract trading can remain open after an outcome becomes obvious. This methodology helps ensure a fair assessment of market performance as a forecasting tool for political outcomes.

Broader context: regulatory scrutiny and market size

U.S. election markets have attracted regulatory attention. Media coverage ahead of the vote noted Commodity Futures Trading Commission (CFTC) surveillance of election markets, with Chairman Michael Selig highlighting monitoring for potential manipulation. Dune analytics data cited by reporters showed roughly $250 million in midterm open interest across Kalshi and Polymarket as of Oct. 18, with Kalshi accounting for approximately $210 million and Polymarket about $40 million.

These figures emphasize the growing intersection of crypto-native platforms, prediction markets and regulated derivatives oversight. As open interest and daily volume climb, exchanges and regulators are adapting to ensure market integrity and protect participants.

Policy responses and candidate participation

Lawmakers have proposed measures targeting candidate trading. Representative Don Davis introduced the No Betting on Your Own Race Act in October, which would bar federal candidates, their spouses, dependent children and authorized campaign committees from trading contracts tied to their elections. Proposed penalties include fines of $10,000 or three times the net financial gain from the transaction, whichever is higher. The bill aims to address conflicts of interest and preserve public confidence in election-related markets.

How markets compared to polls and models

Independent coverage noted that prediction markets anticipated Democratic control of Congress before Election Day but generally underestimated the magnitude of the party's gains. Reuters cited analytics firm BETINT, which identified 14 Democratic winners who had been market underdogs a week earlier and concluded that markets and polls performed roughly equally well overall. This comparison underscores that prediction markets are a complementary forecasting tool alongside polls and election models, particularly in rapidly evolving contests with late-breaking information.

Implications for crypto and prediction markets

Kalshi's midterm performance illustrates how prediction markets can aggregate dispersed information quickly and provide real-time odds that evolve with incoming data. For crypto investors, traders and policy watchers, the episode highlights both opportunity and risk: growing volumes bring more liquidity and forecasting power but also higher regulatory scrutiny and the need for robust surveillance against manipulation.

As election markets continue to mature, monitoring measures such as Brier scores, open interest, and settlement practices will be essential metrics for assessing their reliability and integrity. Platforms like Kalshi and Polymarket remain central to conversations about how decentralized or crypto-adjacent markets can contribute to—and complicate—modern political forecasting.