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District Analysis
Select an analysis mode above, then hover or click a district to explore its metrics.
Polsby-Popper Compactness Score
Select an analysis mode above, then hover or click a district to explore its metrics.
This tool combines three independent datasets to analyze congressional district characteristics across six analytical lenses. All metrics are computed from publicly available government and academic sources. No metric on its own constitutes proof of gerrymandering — each is an indicator that should be interpreted alongside the others and in the context of local political history.
Measures how closely a district's shape resembles a circle. A perfectly circular district scores 1.0; highly irregular, elongated, or fragmented shapes score near 0. Irregular shapes are a classic visual signal of gerrymandering, though they can also result from geographic features like coastlines or mountain ranges.
A secondary score, Reock, is also shown in the district panel. It measures the ratio of district area to the area of the smallest enclosing circle around its convex hull — a different geometric approach to the same question.
Shows the raw Democratic minus Republican vote share from the 2024 general election. Positive values (blue) indicate Democratic advantage; negative values (red) indicate Republican advantage. Gray districts were uncontested — no major-party opponent appeared on the ballot.
A metric developed by Nicholas Stephanopoulos and Eric McGhee (2014) to quantify partisan advantage through "wasted votes." Wasted votes are defined as all losing-party votes plus all winning-party votes above the 50%+1 threshold needed to win. A large gap means one party consistently wastes far more votes than the other — a structural sign of map manipulation.
Values above ±15% are generally flagged in academic literature as potentially significant. Uncontested districts are excluded from this calculation.
Colors each district by whichever racial or ethnic group holds the highest population share, using ACS B03002 (Hispanic or Latino Origin by Race) rather than B02001, which does not distinguish Hispanic identity from racial categories. This allows Non-Hispanic White to be separated from Hispanic populations of any race.
Flags districts where the represented party does not intuitively match the plurality demographic group. This is a coarse heuristic — suburban political realignment and multi-racial coalition building mean many "misaligned" districts reflect genuine voter preference rather than structural manipulation. It is most useful when cross-referenced with the compactness and efficiency gap layers.
Classifies districts by the absolute margin of the 2024 result into four tiers, colored by winning party direction. Systematically uncompetitive districts — particularly when combined with irregular shapes — can indicate deliberate packing or cracking of voters.
A composite index combining three independent signals into a single 0–100 score. Higher scores indicate more characteristics associated with gerrymandered districts. The weighting reflects the relative strength of each signal in academic literature on redistricting.
Where efficiency gap is unavailable (uncontested districts), the score relies on compactness and uncontested status only, with weights renormalized accordingly. No single threshold defines a district as "gerrymandered" — the score is comparative and exploratory.
Stephanopoulos, N. O., & McGhee, E. M. (2015). Partisan Gerrymandering and the Efficiency Gap. University of Chicago Law Review, 82(2), 831–900.
Polsby, D. D., & Popper, R. D. (1991). The Third Criterion: Compactness as a Procedural Safeguard Against Partisan Gerrymandering. Yale Law & Policy Review, 9(2), 301–353.
Reock, E. C. (1961). A Note: Measuring Compactness as a Requirement of Legislative Apportionment. Midwest Journal of Political Science, 5(1), 70–74.