Who will be eliminated next?

Typically, prediction market odds reflect a wisdom-of-the-crowd perspective, often differing from individual analyst forecasts. While analysts may focus on specific technical aspects of the performances or judges’ tendencies, this market incorporates a broader range of factors, including public opinion and unexpected events. It’s common to see discrepancies between the two, especially in entertainment events where subjective elements play a significant role. Currently, the market’s implied probabilities for elimination may diverge from those presented by entertainment news sources and commentators, offering a unique perspective on the likely outcome.

On Kalshi, this market is priced through a continuous double auction, meaning traders buy and sell contracts representing the probability of each contestant being eliminated. The price of a contract reflects the market’s collective belief about that outcome. As more traders participate, the prices adjust to reflect new information and sentiment. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The market depth shows how many contracts are available at different price points, indicating the level of conviction behind each prediction. This dynamic pricing mechanism allows for a fluid and responsive assessment of the elimination probabilities.

This market resolves around Nov 3, 2026, with the outcome confirmed once the official elimination result is verifiable from credible public reporting following the conclusion of Episode 9 of Dancing with the Stars. The market will settle to 100 for the eliminated contestant, and 0 for all others. The resolution will be based on the official announcement made during the show, ensuring accuracy and alignment with the actual event. Traders should monitor official sources for the final result to understand when the market is officially settled.

Several factors could significantly influence this market before resolution. Unexpected injuries to contestants, controversial judging decisions, or shifts in public opinion following performances are all potential catalysts. Social media buzz and media coverage can also play a role, amplifying certain narratives and impacting trader sentiment. Furthermore, any news regarding a contestant’s personal life that might affect their popularity could move the odds. Strong performances during the next live show will likely shift probabilities, while a poor showing could lead to a rapid reassessment of elimination chances.