Sentencing Disparities Across Federal Districts
Why the same offense can result in different sentences depending on where it is prosecuted. What PlainSentencing reveals about geographic variation.
The verdict
Where a federal case is prosecuted measurably changes the sentence. Among districts with at least 500 cases in FY2024, the Northern Alabama District sentenced about 60.4% above the national average for its offense mix, while the Guam District ran roughly 36% below it, a spread that offense type alone does not explain.
- +60.4%
- Northern Alabama, most above average
- -36%
- Guam, most below average
- FY2024
- Districts with ≥500 cases
The Geographic Lottery
One of the most striking findings in federal sentencing data is the degree to which outcomes vary by geography. The same offense, with the same guideline range, can result in significantly different sentences depending on which of the 90 federal judicial districts prosecutes the case. PlainSentencing quantifies this variation through disparity scores that measure each district deviation from national sentencing averages.
What Drives Disparities
Geographic sentencing variation has multiple causes, some legitimate and some concerning:
- Case mix differences - Districts near the border handle more immigration cases. Districts with major financial centers handle more fraud cases. The composition of the caseload naturally affects average sentences.
- Prosecutorial practices - U.S. Attorney offices in different districts may charge differently, offer different plea deals, and file substantial assistance motions at different rates. These practices directly affect sentencing outcomes.
- Judicial culture - Individual judges and district-level judicial culture influence how far and how often courts vary from the guidelines. Some districts have historically been more lenient or more severe than the national average.
- Local conditions - Factors like local crime rates, available alternatives to incarceration, and community supervision resources can influence sentencing decisions.
How PlainSentencing Measures Disparity
PlainSentencing calculates a disparity score for each district by comparing its average sentence for each offense type to the national average for that same offense type. The disparity score represents the average percentage deviation across all offense types prosecuted in the district. This approach controls for case mix, a district that handles mostly drug cases is compared against national drug sentencing averages, not against a district that handles mostly fraud cases.
However, the disparity score cannot control for all legitimate case-specific factors: cooperation levels, role in the offense, drug quantities within a single offense category, or individual defendant circumstances. High disparity scores indicate that something is different about how a district sentences, but they do not automatically indicate unfairness.
Districts that sentence furthest above the national average (FY2024)
Average percent deviation from the national benchmark for the same offense mix
- Northern Alabama
Northern Alabama
60.4 % above national average
- Southern Texas
Southern Texas
55.1 % above national average
- Middle Alabama
Middle Alabama
41.5 % above national average
- Kansas
Kansas
36 % above national average
- Northern Texas
Northern Texas
30.3 % above national average
- Idaho
Idaho
28 % above national average
What this shows The Northern Alabama District tops the list at +60.4% versus the national average for its offense mix, among districts handling at least 500 cases, where the figure is statistically meaningful rather than a small-sample artifact.
Explore District Disparities
Browse rankings to see which districts deviate most from national averages. Click into any district profile to see offense-level breakdowns and year-over-year trends. The data tells a nuanced story that resists simple conclusions, which is exactly why transparent, accessible sentencing data matters.
Policy Implications
Geographic sentencing disparity raises fundamental questions about equal justice. Should a defendant charged with the same offense face a significantly different sentence depending on which district files the case? The guidelines were originally created in part to reduce such disparity, and the data shows they have partially succeeded, variation is smaller than it was in the pre-guidelines era. But meaningful geographic differences persist in the post-Booker advisory system.
The data on PlainSentencing provides the empirical foundation for this ongoing policy discussion. Whether one views geographic variation as a problem to be solved or as appropriate local adaptation depends on values and priorities, but the conversation should be grounded in data rather than anecdote.
Controlling for Legitimate Variation
Perfect sentencing uniformity across districts is neither achievable nor necessarily desirable. Different districts face different challenges, border districts handle immigration cases, financial center districts handle complex fraud, and rural districts may handle more drug cases. The disparity score on PlainSentencing controls for offense type to address some of this variation, but cannot control for all legitimate case-specific factors such as cooperation, role in the offense, or quantity within a category.
Researchers who study sentencing disparity use increasingly sophisticated methods to control for legally relevant factors. PlainSentencing provides the accessible first layer of analysis, district-level patterns that identify where deeper investigation may be warranted. For formal research requiring individual-level controls, the USSC public-use datafiles provide the necessary granularity.
Why This Matters for Research and Journalism
Federal sentencing data is one of the most important public-records corpora produced by the U.S. government. Researchers, journalists, defense attorneys, and policy analysts rely on it to evaluate the fairness, consistency, and proportionality of the federal criminal justice system. PlainSentencing exists to make this dataset navigable for non-specialists without flattening the complexity that makes it meaningful.
Every district profile, ranking, and explainer on this site is derived from the U.S. Sentencing Commission Individual Offender Datafiles, which we recompute from the raw FY2015 through FY2024 records. The numbers presented here are reproducible from the source data, and the methodology that produced each chart and table is documented on our methodology page. Corrections, refinements, and questions are welcome at the contact address listed there.
For practitioners considering using this data in court filings, scholarly research, or journalism, please cite the underlying USSC datasets rather than PlainSentencing, we are a presentation layer, not the primary source. Our editorial role is to translate technical fields, explain methodological caveats, and surface comparisons that highlight meaningful patterns in the federal sentencing system.
Frequently Asked Questions
Where does PlainSentencing get its data?
All data comes from the United States Sentencing Commission (USSC) public-use datafiles. The USSC collects data on every federal offender sentenced in U.S. district courts and publishes annual datafiles. PlainSentencing aggregates FY2015 through FY2024, covering over 660,000 sentencing records.
What does the disparity score measure?
The disparity score measures how much a district average sentence deviates from the national average for the same offense types. Higher scores indicate greater deviation. It controls for offense mix but not for case-specific factors like cooperation or role in offense.
Is PlainSentencing legal advice?
No. PlainSentencing is for educational and research purposes only. Sentencing outcomes depend on case-specific factors that aggregate statistics cannot capture. Consult a qualified federal defense attorney for guidance on any specific case.