Market is split — Francesca Hong at 59%. High uncertainty = high risk/reward opportunity.
| # | Outcome | Probability | If Right | Volume |
|---|---|---|---|---|
| 1 | Francesca Hong | 59% | +69% | $26K |
| 2 | Mandela Barnes | 16% | +525% | $18K |
| 3 | Sara Rodriguez BEST VALUE | 16% | +545% | $41K |
Real-money prediction market · Trade with confidence
This market will resolve according to the winner of the Democratic Primary for Governor of Wisconsin, scheduled to take place on August 11, 2026. Resolution will be based on the overall winner of the...
This prediction market tracks whether Wisconsin Governor Democratic Primary Winner will occur, with $135K in total trading volume reflecting significant trader interest. Prediction markets aggregate the collective intelligence of participants who stake real money on outcomes, making them one of the most reliable forecasting tools available for events driven by polling data, political developments, and historical voting patterns.
The market is closely contested, with Francesca Hong leading at just 59%. This near-even split signals high uncertainty among traders, creating potential value opportunities for those with strong conviction based on their own analysis of the underlying factors.
Recent trading volume of $16K in 24 hours shows healthy market activity. Active markets tend to produce more accurate probability estimates, as continuous trading ensures prices quickly incorporate new information.
This market is scheduled to resolve by 2026-08-11. As the resolution date approaches, expect increased trading activity and tighter probability estimates. Historical data shows that prediction market accuracy improves significantly in the final days before resolution.
As of Jul 13, 2026 at 23:05 UTC, the leading outcome is Francesca Hong at 59% probability, with $135K in total trading volume on Polymarket.
The total trading volume for this market is $135K, with $16K traded in the last 24 hours. This represents real money at stake from prediction market traders on Polymarket.
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