South Korea's 2026 local elections will reshape the political landscape of Daegu, the country's third-largest metropolitan city with over 2.4 million residents. This event aggregates prediction markets tracking the mayoral race, where five significant candidates are competing for the position. These markets—covering Kim Boo-kyum, Hong Seok-jun, Joo Ho-young, Kang Min-gu, and Lee Jae-man—offer a real-time probability assessment based on aggregated expectations across a distributed pool of forecasters. Unlike traditional polling, which captures opinion at discrete moments, prediction markets continuously incorporate new information as the election approaches and campaigns evolve. When reading the prices below, interpret each candidate's market price as the collective forecast probability that they will win the election. Higher prices indicate stronger expected performance, while compressed gaps between candidates suggest genuine uncertainty. The concentration of markets on these five names reflects both their viability as contenders and the market's assessment of the competitive field. Observers should note that prediction market signals have historically correlated with electoral outcomes more reliably than single-poll snapshots, though neither is infallible. The Daegu mayoral race carries broader implications for national politics: how voters in Korea's industrial heartland respond to policies on urban development, labor relations, and inflation will echo in subsequent national contests. These markets allow you to compare relative forecast probabilities across candidates and track how assessments shift as new events, campaign announcements, and economic data emerge. Whether you're tracking electoral politics, testing forecasting accuracy, or seeking a structured view of expert expectations, these aggregated markets provide transparent, real-time signals for the 2026 race.