Despite surging popularity ahead of Brazil’s recent presidential election, prediction markets heavily miscalculated the outcome, underestimating the resilience of Luiz Inácio Lula da Silva. Bettors on major platforms heavily favored the incumbent, Jair Bolsonaro, misled by biased polling interpretations and a skewed demographic of platform users. This massive forecasting failure highlights the structural vulnerabilities of crowdsourced financial models when operating in politically polarized environments. As prediction markets increasingly influence mainstream political coverage, this high-profile misfire serves as a cautionary tale about their reliability. Ultimately, the Brazilian upset proves that algorithmic betting markets are just as susceptible to echo chambers and misinformation as traditional polling methods.