Kansas Legislative Forecasts

Kansas Senate Forecast

Simulation Results

Republicans win a supermajority 80 times out of 100

Democrats break the supermajority 20 times out of 100

Here are the seat distributions predicted by the model. Republicans have a 100 percent chance of winning the Senate, and an 79.84 percent chance of maintaining their supermajority (19,961 simulations out of 25,000). The forecast predicts Democrats will earn 11.76 seats (12), two shy of what they need to break the supermajority. Interestingly, the model predicts that Democrats are largely favored in all but one of their current districts (SD5 Pittman), meaning they likely only need to defend that seat and can go on the offensive in the other battleground districts.

Current Ratings

10 Democrats Favored - 4 Tossups - 26 Republicans Favored

Hover over the map to explore each district.

Individual Races

Explore the projected margins and ratings for each race in the chamber. Here you will see information on candidates and some of the data that goes into the forecast.

Kansas Senate Forecast Over Time

I update the forecast and run 25,000 simulations every day. Seeing as there will be very few district and state polls from now until election day, there won't be a large trend in data that you may see on presidential forecasts. Polling data does influence the forecast, but it is not weighted heavily due to factors such as its broadness and ticket splitting. There will be three major shifts in the forecast when we get pre-primary election finance reports, primary results, and pre-general election finance reports.

Battleground Races and the Tipping Point Seat

Here we can see all seven districts that the model suggests is "competitive." These are the districts rated Lean R through Lean D, with a few of the most competitive Likely districts. Their projected margin as well as a 95% range of outcomes are shown to illustrate how close and uncertain these elections truly are. For example, Mike Thompson is projected to lose by 0.61pts, but it is entirely believable that he could win or lose by 5pts. Of course those outcomes are on the extreme ends of the spectrum, but a few of these races are true tossups and this chart illustrates that.

Also listed is the "Tipping Point Chance" value predicted by the model. The tipping point seat is the seat that "tips" the overall outcome of the election, which in this case, is Democrats winning 14 seats and breaking the Republican supermajority. The percent chance is essentially "how likely is this race to be the 14th most Democratic district?" This does not mean that Democrats won the seat, however. For example, Democrats could win 13 seats but lose the 10th district. If SD10 was the next most-Democratic district, it was the tipping point seat that Dems needed to win in order to "win the election." In 2020, the Senate tipping point seat was SD30 won by Renee Erickson by 4.22pts. This data also does not imply any odds that winning said seat means X percent chance of winning the election. I am working on calculating that next.

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