Wisconsin, Michigan primaries expose limits of polls and prediction markets

A big miss for prediction markets

Prediction markets in Wisconsin had a bad night, too. Just like polls, they portrayed a race that looked much more secure for Hong than in reality once the votes started rolling in.

On Kalshi, Hong had a 95% chance of winning as of Monday night, while Crowley just had a less than 5% chance. In a now deleted post on X on Tuesday afternoon, before polls closed, Polymarket said that Hong was a “near-lock” to win the nomination, noting she had 96% odds to do so.

A Polymarket spokesperson told CNBC that the post was flagged internally for its language to describe the race and thus was deleted.

Meanwhile in Michigan last week, prediction markets showed El-Sayed with greater than 90% odds to win the Democratic nomination for Senate before polls closed, despite his very narrow victory.

Lakshya Jain, co-founder of the electoral data website SplitTicket and director of political data at the publication The Argument, said he was frustrated by what was happening on the related contracts on prediction markets once polls closed in Wisconsin on Tuesday night.

“The biggest concern for me was that the movement that I was seeing,” Jain said. He was frustrated that odds for Hong were shooting higher or tumbling lower as results from across the state came in, all while he didn’t think individual vote drops were altering the outlook for her actual chances to win that much. “There was absolutely no reason for the markets to move toward her if they were actually being efficient.”

Still, Jain said there is usefulness to prediction markets when it comes to elections, particularly their ability to price in factors often external to polls.

Kalshi co-founder and CEO Tarek Mansour took to X to defend the platforms’ outcomes.

“Before the ‘prediction markets got it wrong’ headlines roll in: a 5% probability doesn’t mean it won’t happen,” he wrote. “It means it should happen 1 in 20 times. If 5% candidates never won, the markets would be broken.”

Meanwhile, voters in Minnesota delivered a surprise. Prediction markets gave Flanagan about a 70% chance to win the nomination in the state’s U.S. senate race Tuesday night, showcasing a better result for traders on those platforms.

Flip Pidot, chief strategy officer at PredictIt and member of the board of directors at the Coalition for Political Forecasting, said reliance on polls is often a problem for prediction market contracts, like those in Michigan and Wisconsin.

“People just still look at that poll barometer as the North Star,” he said. “Everyone was surprised that the polls were so wrong on both these races, and the markets are what they are. They’re just a reflection of what the general populace thinks.” But the good thing about markets is there’s an incentive for more traders to participate and make them more accurate, due to their potential financial rewards.

A mixed bag for Democrats

How the results differed from polls and prediction markets present a mixed bag for Democrats amid a progressive surge throughout the country.

Hong’s shortfall compared with public polling could temper the belief that progressives have hijacked the Democratic Party.

“More broadly, the Democratic ‘establishment’ isn’t as strong as it once was but party leaders are not without power,” Kondik said.

Article source: https://www.cnbc.com/2026/08/13/midterm-democrats-polling-primary-wisconsin-michigan-minnesota.html