Prediction markets broadly called the election, but their earlier accuracy is harder to assess

The speakers judged prediction markets broadly successful in calling election outcomes, though the Texas race was a surprise: prices shifted sharply only about two hours before results came in. The host said Kalshi was 95% accurate by the time polls opened. One, two and even three months before the election, its accuracy was 81%, compared with VoteHub’s 77% average. A guest said those figures seemed impressive because many markets had been closer to 60/40 than 80/20, and suggested giving markets somewhat more weight on average when a candidate has a clear lead.

Favorably relaying Joe Weisenthal’s assessment, the host said prediction markets performed well: they offered a confident forecast ahead of the vote and conveyed incoming data promptly on election night. The host also said Nick Carter and Matt Wong considered the markets accurate that night. The host said Polymarket correctly called every result at one awards show—either the Emmys or the Oscars. He compared that with elections: when markets signal a “blue wave” for months, a correct prediction can drain the suspense. A guest countered that a sporting event is still undecided while it is underway, whereas an awards ceremony may simply announce a result already determined. The speakers also noted that people in and around tech who said both polls and prediction markets were wrong had themselves been wrong.