In the US, not all votes are equal. Enter addresses above to explore how the power of a vote varies across the country.
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Appendix
PowerVoting uses the closeness of elections and the constituency size (e.g. voters per representative, senator, or elector) at the federal level to find the relative “impact” of a vote for the addresses you look up. The Voting Impact Score is the percentage of Vote Slices that could remain unchanged for the results of an election to still flip. The higher this number, the less movement necessary to flip the election and the greater the impact of a vote.
Election closeness is calculated by subtracting the percentage victory margin between the first and second place candidates in an election from one. This closeness score is calculated for every historical election in the district since 1976, then displayed as a chart on the results page. The overall closeness score for the district is a weighted average of these individual election scores, with increasingly recent elections weighted according to the square of the number of years since 1975.
The Vote Slice is calculated by dividing the average units of power in an election (1 for house and senate elections, the number of electors in the state for presidential elections) over the turnout in the district (or, in the case of senate and presidential elections, the state) for the two most recent elections with nonzero votes. More simply, this metric quantifies the ‘slice’ of the representative or elector that an individual vote corresponds to.
The overall Voting Impact Score is the product of the overall closeness score and the two most recent Vote Slice scores for the district multiplied by ten million (to make the number more accessible and intuitive). A higher impact score for a district means generally closer elections and larger “slice” of an elected official per vote.
District mapping data is from Google and election data is from the MIT Election Lab. Some special elections may not be included.
The source code is open source and available on GitHub.
