ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · APRIL 2025
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-2025-report
Monthly Traffic Safety Analysis
1,307 CRASHES IN
BATON ROUGE, LA
APRIL 2025
In April 2025, Baton Rouge recorded 1,307 vehicle crashes, a 2.5% increase from the 1,275 crashes reported in April 2024. While total crashes saw a slight rise, the number of fatal crashes tripled from one to three year-over-year. This increase in fatal outcomes represents the most significant change in the data between the two periods.
1,307
▲ 2.5%was 1,275
Total Crash Events
3
▲ 200.0%was 1
Fatal Crashes
1,013
▼ -0.9%was 1,022
Injury Crashes
274
▼ -5.8%was 291
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 · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash trends in Baton Rouge show a slight increase in total incidents for April 2025 compared to the previous year. Total crashes rose by 2.5%, from 1,275 to 1,307. While the number of injuries saw a marginal decrease of 0.9%, from 1,022 to 1,013, fatalities increased from one to three.
274
Hit-and-Run Crashes — April 2025
▼ -5.8% vs prior (291)
Hit-and-run incidents decreased in April 2025 compared to the same month in the prior year. The total count of hit-and-run crashes fell from 291 to 274, a 5.8% reduction. This corresponds to a decline in the hit-and-run rate, which dropped from 22.8% of all crashes in April 2024 to 21.0% in April 2025.
When Crashes Happen
The temporal patterns of crashes shifted between April 2024 and April 2025. The peak day for crashes moved from Friday, with 221 crashes in the prior year, to Wednesday, with 254 crashes in the current period. Crashes on Wednesdays increased by 46% year-over-year, while incidents on Mondays and Fridays saw notable decreases.
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday
Crash Severity Breakdown
Year-over-year, the severity of crashes in Baton Rouge saw a notable change. The number of fatal crashes increased from one in April 2024 to three in April 2025. Consequently, the proportion of crashes resulting in an injury decreased from 80.2% to 77.5% of all incidents, while the share of no-injury crashes rose from 19.8% to 22.3%.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-04-01 to 2025-04-30 · 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 · 2025-04-01 to 2025-04-30 · Most severe injury per crash record
Top Contributing Factors
The primary contributing factors to crashes remained consistent in rank year-over-year, though their counts shifted. 'Violations' continued to be the leading factor, with the count of related crashes increasing by 5.8% from 996 in April 2024 to 1,054 in April 2025. In contrast, crashes attributed to 'Movement prior to crash' decreased by 15.9% in count, from 239 to 201 incidents.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-04-01 to 2025-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in clear weather and on dry roads remained the vast majority in both periods. However, there was a notable increase in crashes occurring in adverse conditions, with incidents during rain increasing by 68.8% from 32 to 54. Similarly, crashes on wet road surfaces rose by 62.7%, from 51 in April 2024 to 83 in April 2025. The distribution of crashes by lighting condition remained relatively stable.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2025-04-01 through 2025-04-30 (30 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,307
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 2025." Published June 19, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/april-2025-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: 2025-04-01 – 2025-04-30
Generated: June 19, 2026 · All rights reserved