Help Center

Whether you’re exploring our site’s election pages or just doing research on voting patterns, this overview explains how we compile and present statewide election results (i.e., races for statewide offices and statewide propositions). We link voting data to local areas—counties, cities, districts—so you can see how each place weighed in.

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Where the Data Comes From

We obtain California’s official precinct-level statements of vote from the Statewide Database . Each precinct file shows how voters in that precinct chose among candidates and on each proposition. Sometimes, counties may withhold precinct-level results if the number of voters is too small, to protect individual privacy. In those cases, our totals can be off by a small margin from the official countywide tally.

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Handling Smaller Subdistricts

For large, standard jurisdictions—like entire counties, full cities, or statewide legislative or school districts—precincts often line up neatly with those boundaries. However, many smaller or more customized districts (e.g., city council wards or local board seats) cut across precinct lines in complicated ways.

To address this, we estimate how many votes belong to each subdistrict by referencing census block population inside each precinct. Specifically:

• We determine which census blocks lie within each precinct and measure how much of the block overlaps the subdistrict boundary.
• Using the block’s population as a guide, we allocate a proportional share of the votes from that precinct into the subdistrict. For example, if around half of the block’s residents live inside the subdistrict, we’d assign roughly half of that precinct’s votes to the subdistrict.

This approach won’t always be 100% exact—especially in districts where turnout or demographics vary between blocks—but it generally produces a sound approximation of how smaller areas voted.

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Accurate Results for Evolving Districts

One challenge with analyzing historical election results is that district boundaries often change over time due to redistricting. Many traditional datasets report results for districts as numbered during a specific election year, without accounting for changes in geography. For example, a report might claim "Obama won the 75th Assembly District by 20%," but that result reflects the 75th District's boundaries from that time, not the current boundaries.

Our application addresses this by mapping historical election results to the current geography of districts, regardless of their previous numbering or configuration. Using precinct-level voting data and up-to-date district boundaries, we show how the current district would have voted in past elections. This ensures a more accurate and meaningful analysis of historical trends within today’s district lines.

By focusing on the underlying geography rather than just the district number, our platform provides insights that are far more relevant for understanding voting behavior in the context of today’s political map.

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Candidates & Propositions

• Statewide Offices: We show how each candidate performed (votes and percentages), highlighting the winner in that specific area.
• U.S. Senate & Presidential: When these races appear on California’s statewide ballot, they’re included as well.
• Propositions: We display "Yes" and "No" counts, plus which side carried the local vote.

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Why It’s Helpful

Reviewing statewide election outcomes in local contexts can be beneficial in many ways:

• Voter Preferences & Trends: Identify which areas favor certain candidates or policy stances over time.
• Ballot Measure Support: See which parts of the region embraced or opposed propositions, revealing patterns of civic engagement and interest.
• Local Focus: Even if you’re looking at a small board seat or council district, our proportional method offers a reasonable glimpse into how voters there made their choices.

Our goal is to give you as much clarity as possible about voting behavior, from large-scale countywide results all the way down to subdistrict-level estimates—always grounded in the best-available public data.