Prediction markets have transitioned from niche betting platforms to mainstream election forecasting tools, with major news organizations integrating live odds into their coverage. Polymarket and Kalshi, the two largest platforms, saw trading volume reach $21 billion in October, marking a monthly record. Proponents argue that these markets harness collective intelligence more accurately than traditional polling by requiring traders to put money behind their predictions.
However, prediction markets have experienced significant failures in recent elections. In Brazil’s presidential runoff on 25 October, Polymarket priced candidate Flávio Bolsonaro’s chances at roughly 80% on election day, yet incumbent Luiz Inácio Lula da Silva won by a narrow margin. Similar miscalls occurred across multiple contests: Polymarket gave opposition candidate Aleksandar Vučić a 70% probability in Serbia’s snap parliamentary election before he lost with 39.2% of the vote, while opposition candidate Student List won with 52.6%. In Wisconsin’s Democratic governor’s primary, both major platforms gave Francesca Hong approximately a 95% chance despite her losing by less than half a percentage point.
Analysts point to structural differences between market prices and polling data to explain some discrepancies. While polls measure a candidate’s current margin, prediction market prices calculate the odds of winning on election day, often amplifying small polling gaps into large probability swings. For example, Nebraska’s Senate race shows only a 2% polling margin between Pete Ricketts and Dan Osborn, yet markets price a Ricketts victory at approximately 70%. Despite these explanations, critics raise concerns about market manipulation and the influence of well-funded interest groups, particularly given ties between the prediction market industry and cryptocurrency sectors.
As Americans prepare for midterm voting, prediction markets face their most significant credibility test. The stakes have grown considerably as mainstream acceptance increases and institutional money flows into these platforms, raising questions about whether markets can reliably forecast elections or whether recent misses reflect deeper structural problems.
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