Knowing who won is just the beginning. Election Reports show where they won, how different voter groups supported each candidate, and whether the race followed partisan patterns or defied them. This is the platform's tool for forensic analysis of completed races—essential for campaign post-mortems, targeting future elections, and understanding the political dynamics of any jurisdiction.
What Election Reports Reveal
Election Reports answer questions that simple vote totals can't:
- Geographic patterns: Which precincts delivered the margin of victory? Which neighborhoods swung against expectations?
- Coalition composition: Did the winner build support across the partisan spectrum, or run up the score with their base?
- Partisan dynamics: Was this a party-line race, or did candidates build cross-partisan coalitions?
- Competitive terrain: Which precincts were decisive swing areas versus safely partisan?
This analysis is possible because Election Reports work at the precinct level—the smallest geographic unit for which election results are reported.
Finding Election Reports
From the Election Reports index: Browse all available reports. Filter by year, election type (General/Primary), and race type. Search for specific contests by name or jurisdiction.
From an Election page: Past elections include an "Election Report" link in the header that goes directly to the precinct-level analysis.
From a jurisdiction's election results: When viewing local election results, races with precinct data available include links to their Election Reports.
Understanding the Precinct Map
The interactive map shows results at the precinct level. By default, precincts are colored by winner and margin:
- Darker colors = larger margin (more decisive for one candidate)
- Lighter colors = closer margin (more competitive)
Switch to individual candidate views to see how a specific candidate performed relative to their overall average—which precincts overperformed or underperformed for them.
Display options:
- Toggle "Show vote volume" to see relative turnout (darker = more votes cast)
- Filter to competitive precincts only (Close <5 pts, Lean <10 pts, Solid <20 pts)
Reading Race Statistics
The statistics panel alongside the map provides key metrics:
Registration Advantage: The partisan lean of registered voters (e.g., "D+25%"). This is the baseline expectation based on who's registered, not how they voted.
Turnout Advantage: Which party's registered voters showed up at higher rates. A D+5% turnout advantage means Democrats exceeded their registration share in the actual electorate.
Partisanship Score: A 0-100 measure of how closely the race followed party lines. High scores (70+) mean precincts with more Democrats voted one way and precincts with more Republicans voted the other. Low scores (<40) mean party registration wasn't predictive—candidate qualities or issue positions mattered more than party.
Party Alignment: Which candidate was most aligned with each party's voters based on actual voting patterns.
Precincts Won: How many geographic units the winner carried. A candidate can win more precincts but lose the race if the precincts they lost were larger.
Ballot Dropoff: What percentage of top-of-ticket voters (President or Governor) also voted in this race. Lower percentages indicate a down-ballot race that many voters skipped.
The Coalition Heatmap
The "How Each Partisan Group Voted" heatmap is one of the most revealing features. It visualizes support levels across the ideological spectrum:
- Columns represent partisan deciles, from most Democratic-leaning precincts (left) to most Republican-leaning precincts (right)
- Rows represent candidates
- Cell values show what percentage of votes in that group went to each candidate
This reveals coalition patterns:
- Flat row = broad support across partisan groups (coalition builder)
- Steep slope = support concentrated in one partisan group (base mobilizer)
- Crossing lines = candidates drawing from different coalitions
The "Electorate center" marker shows where the jurisdiction's actual voters fall on this spectrum. In a heavily Democratic city, even the "Most Republican" precincts may still lean blue in absolute terms.
Geographic Breakdown
The Geographic Breakdown section shows how the race performed across sub-jurisdictions—city council districts, neighborhoods, school districts, legislative districts, etc.
Click any geography to highlight it on the map. This reveals which communities drove the outcome:
- Which neighborhoods delivered the most votes for each candidate?
- Did the winner carry all council districts, or did they lose some?
- How did different school attendance areas vote?
Precinct Results Table
The sortable, filterable table lists all precinct-level results:
- Filter by candidate focus: See only precincts where a specific candidate won
- Filter by margin: Focus on Close (<5 pts), Lean (<10 pts), or Solid (<20 pts) precincts
- Filter by turnout: High, medium, or low turnout precincts
- Sort columns: Click headers to sort by any metric
Click any precinct row to open a detailed modal showing:
- Precinct demographics and registration breakdown
- Results for all other races on the ballot in that precinct
- Context for understanding why this precinct voted as it did
When Election Reports Are Available
Election Reports require precinct-level results data, which isn't available for all races:
- Local candidate races: Generally available 2022-2024
- Legislative races: Generally available 2014-2024
- Local ballot measures: Coverage varies by jurisdiction
The Election Reports index shows what's available. If a race doesn't have an Election Report, precinct data wasn't obtainable.
Practical Applications
Campaign post-mortem: After a race, identify which precincts underperformed expectations. Where did you lose votes you expected to win? Where did you overperform? This informs future targeting.
Building a targeting strategy: Use past Election Reports to identify persuasion targets (swing precincts) versus turnout targets (base precincts). Precincts with <5 point margins are where persuasion matters; precincts with 20+ point margins are where turnout matters.
Understanding ballot measures: See which communities supported or opposed a specific measure. If a housing measure failed, which neighborhoods voted it down? This informs future campaign strategy.
Researching candidates: For candidates who've run before, their Election Report shows their geographic base and coalition composition. A candidate who won by mobilizing base voters runs a different kind of campaign than one who won by building cross-partisan coalitions.
Comparing across elections: Pull up Election Reports for the same jurisdiction across different years to see how geographic voting patterns have shifted.
Important Limitations
Correlation isn't causation: The data shows that Democratic precincts voted a certain way, not that individual Democrats voted that way. Don't assume precinct-level patterns reflect individual voter behavior.
Precinct boundaries change: Precinct boundaries can change between elections, not just with redistricting. Direct precinct-to-precinct comparisons across elections aren't reliable. Focus on neighborhood-level or jurisdiction-level patterns instead.
Precinct sizes vary: Some precincts have 100 voters; others have 5,000. A candidate "winning more precincts" doesn't necessarily mean winning more votes.
Same-party races behave differently: When two Democrats face each other in a general election, the race won't show normal partisan patterns. Low partisanship scores are expected in these cases.
Primary vs. General coalitions differ: Primary electorates are smaller and more partisan. A candidate's primary coalition may look very different from their general election coalition.
Common Mistakes
Over-interpreting the electorate center: The heatmap labels are relative to this jurisdiction. In a D+30 city, even the "Most Republican" column represents precincts that lean Democratic in absolute terms.
Ignoring turnout advantage: A D+5% turnout advantage in a D+20% registration jurisdiction actually means Republicans overperformed in turnout. Context matters.
Assuming past patterns predict the future: The same precincts that swung a 2022 race may not be decisive in 2026. Candidates, issues, and turnout patterns change.
Treating ecological data as individual data: "High-income precincts voted Yes" doesn't mean high-income individuals voted Yes. Other factors may correlate with both income and voting behavior.