U.S. Senate Forecast
Model-driven seat projections for all 35 Senate races. Updated continuously using polling, ratings, incumbency, and State Voting History
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| State | Rating | Margin | Win Prob | Incumbent |
|---|
Four-Stage Pipeline
Gather expert ratings, polling averages, the state voting history, and incumbency status for all 35 races.
Normalize signal weights to a true weighted average, then add an incumbency bonus that scales with how competitive the race is.
Convert the margin to a win probability using a normal distribution with an 8.5-point uncertainty margin.
Run 1,000,000 correlated Monte Carlo simulations to determine how often each party hits 51 seats.
Signal Weighting
Note: The three base signals (ratings, polling, history) are normalized to a true weighted average. The incumbency bonus is then added on top — scaled back only when live polling shows a wide margin, and applied in full when no polling is available. For open seats, the incumbency bonus is removed entirely and its weight is spread across the remaining signals.
1,000,000 Pre-Computed Simulations: Senate control probabilities are computed offline using 1 million correlated Monte Carlo simulations with a fixed seed for consistency — the same input data always produces the same result. Each simulation applies a shared national environment shift (σ = 8.5 pts) and independent race noise (σ = 8.5 pts). Results are model projections, not guarantees.