ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · APRIL 2026
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/louisiana/baton-rouge/april-2026-report
Monthly Traffic Safety Analysis
1,348 CRASHES IN
BATON ROUGE, LA
APRIL 2026
In April 2026, Baton Rouge recorded 1,348 vehicle crashes, a 3.1% increase from the 1,307 crashes documented in April 2025. While the total number of crashes rose slightly and injuries remained stable, the most significant year-over-year change was the reduction in traffic fatalities, which dropped from three in the prior year's period to zero.
1,348
▲ 3.1%was 1,307
Total Crash Events
0
▼ -100.0%was 3
Fatal Crashes
1,011
▼ -0.2%was 1,013
Injury Crashes
296
▲ 8.0%was 274
Hit-and-Run Crashes
Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons.
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-04-01 to 2026-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes in Baton Rouge saw a slight increase of 3.1% in April 2026 compared to the same month in 2025, rising from 1,307 to 1,348 incidents. Despite the rise in collisions, the number of reported injuries was nearly unchanged, decreasing from 1,013 to 1,011. Notably, there were no fatalities recorded in April 2026, a positive change from the three fatalities reported in April 2025.
296
Hit-and-Run Crashes — April 2026
▲ 8.0% vs prior (274)
Hit-and-run incidents increased in both absolute numbers and as a proportion of total crashes in April 2026 compared to the previous year. The total count of hit-and-run crashes rose from 274 in April 2025 to 296 in April 2026. This change reflects an increase in the hit-and-run rate from 21% to 22% of all vehicle collisions.
When Crashes Happen
The temporal patterns of crashes remained broadly consistent year-over-year, with Wednesday being the peak day for collisions in both April 2026 (272 crashes) and April 2025 (254 crashes). However, there was a noticeable shift in the daily distribution of crashes; collisions on Tuesdays decreased from 235 to 178, while crashes on Thursdays increased from 208 to 262. Weekend days (Saturday and Sunday) continued to have the lowest crash volumes in both periods.
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-04-01 to 2026-04-30 · Crash date field aggregated by weekday
Crash Severity Breakdown
Crash severity outcomes improved in April 2026 compared to the prior year, with fatal crashes decreasing from three to zero. The proportion of crashes resulting in an injury also saw a slight reduction, accounting for 75% of all incidents (1,011 crashes) compared to 77.5% (1,013 crashes) in April 2025. Correspondingly, the share of crashes with no reported injuries increased from 22.3% of the total in the prior year to 25% in the current period.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-04-01 to 2026-04-30 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)
Severity Distribution (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-04-01 to 2026-04-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors to crashes remained consistent, with 'Violations' cited as the primary cause in both periods. Crashes attributed to violations increased in count from 1,054 in April 2025 to 1,099 in April 2026. The second-ranked factor, 'Movement prior to crash,' also saw a slight rise in count from 201 to 206 incidents. The top three contributing factors maintained their same rank order across both years.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-04-01 to 2026-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The vast majority of crashes in both April 2026 and April 2025 occurred in ideal conditions, with over 85% of incidents happening in clear weather and over 91% on dry road surfaces in both periods. However, there was a slight increase in crashes during adverse conditions year-over-year. Crashes in the rain rose from 54 to 71 incidents, and collisions on wet roads increased from 83 to 101. Similarly, crashes in 'Dark - continuous street lights' conditions increased from 168 to 193.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-04-01 to 2026-04-30 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-04-01 to 2026-04-30 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-04-01 to 2026-04-30 · Road surface condition field
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Baton Rouge Crash Data, accessed programmatically via the Socrata Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.
Data Retrieval
- Access method: Socrata Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2026-04-01 through 2026-04-30
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2026-04-01 through 2026-04-30 (30 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,348
Analytical Methodology
- Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
- Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
- Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
- Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
- Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
- Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
- AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.
Limitations & Disclaimers
- Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
- Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
- Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
- AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
- Percentages are calculated from reported data and are subject to rounding.
Non-Affiliation Disclosure
This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.
Data License
The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.
Corrections & Feedback
If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.
Suggested Citation
ThatCarHitMe.com (Injuria.ai). "Baton Rouge, LA Crash Intelligence Report: April 2026." Published June 19, 2026. Reporting period: 2026-04-01 to 2026-04-30. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/april-2026-report
About the Publisher
ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.
Questions about this report's data or methodology: data@injuria.ai
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Baton Rouge Crash Data · Socrata
Period: 2026-04-01 – 2026-04-30
Generated: June 19, 2026 · All rights reserved