How I Predicted Every Election Since 1916

Why “election pundit predictions” betray a misunderstanding of probability

Harys Dalvi
Towards Data Science

In just 91 lines of C++ code, I perfectly predicted every United States presidential election since 1916. That’s 28 straight elections, counting the most recent one in 2024.

The crazy part is I didn’t rely on any complicated polling data trends, voter sentiment, or policy analysis to make these predictions. I just used basic principles of probability.

The US presidential election results in 1916. Public domain. By AndyHogan14, Wikimedia.

Alright, I’ll admit I cheated a little. But arguably not much more than the political pundits that claim to have predicted every election since, say, 1980.

Every election cycle, you see stories on the news of someone who has correctly predicted every election in however many years. Most recently, I saw stories about Allan Lichtman, who correctly predicted most of the 11 elections from 1984 through 2020. His system for predicting elections is called the “13 Keys”, and consists of 13 true/false questions to predict the winner of the election.[1]

But then Allan Lichtman got the 2024 election wrong. Does this cast doubt upon election pundits who claim to have sophisticated election prediction systems?

In this article, I’m going to show you how you, too, can predict every single

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