Explore The Ways Trump Or Biden Could Win The Election
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How this works: We start with the 40,000 simulations that our election forecast runs every time it updates. When you choose the winner of a state or district, we throw out any simulations where the outcome you picked didn’t happen and recalculate the candidates’ chances using just the simulations that are left. If you choose enough unlikely outcomes, we’ll eventually wind up with so few simulations remaining that we can’t produce accurate results. When that happens, we go back to our full set of simulations and run a series of regressions to see how your scenario might look if it turned up more often.
In simplified terms, the regressions start off by looking at the vote share for each candidate in every simulation and seeing how the rest of the map changed in response to big or small wins. So let’s say you picked Trump to win Texas. In some of our simulations, Trump may have won Texas very narrowly and also have narrowly lost some toss-up states. But in simulations where he won Texas by a big margin, he may also have won big in toss-up states and pulled some Democratic-leaning states into his column, while the reverse may be true in simulations where he lost the state. We figure out how every other state tended to look in that full range of scenarios, tracking not just whether the candidate usually won other states but also how much he generally won or lost each one by.
After all that, we take some representative examples of scenarios that include the picks you made and use what we learned from our regression analysis to adjust all 40,000 simulations, and then recalculate state and national win probabilities. Finally, we blend those adjusted simulations with any of the original simulations that still apply and produce a final forecast.
In simplified terms, the regressions start off by looking at the vote share for each candidate in every simulation and seeing how the rest of the map changed in response to big or small wins. So let’s say you picked Trump to win Texas. In some of our simulations, Trump may have won Texas very narrowly and also have narrowly lost some toss-up states. But in simulations where he won Texas by a big margin, he may also have won big in toss-up states and pulled some Democratic-leaning states into his column, while the reverse may be true in simulations where he lost the state. We figure out how every other state tended to look in that full range of scenarios, tracking not just whether the candidate usually won other states but also how much he generally won or lost each one by.
After all that, we take some representative examples of scenarios that include the picks you made and use what we learned from our regression analysis to adjust all 40,000 simulations, and then recalculate state and national win probabilities. Finally, we blend those adjusted simulations with any of the original simulations that still apply and produce a final forecast.
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