ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · MARCH 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/march-2026-report
Monthly Traffic Safety Analysis
1,500 CRASHES IN
BATON ROUGE, LA
MARCH 2026
In March 2026, Baton Rouge recorded 1,500 total crashes, a 9.9% increase from the 1,365 crashes documented in March 2025. Despite the overall rise in collisions, the number of fatalities decreased from 5 to 2 during the same period. This contrast between rising crash volume and falling fatalities represents the most significant year-over-year trend.
1,500
▲ 9.9%was 1,365
Total Crash Events
2
▼ -60.0%was 5
Fatal Crashes
1,135
▲ 7.1%was 1,060
Injury Crashes
332
▲ 16.5%was 285
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 · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year data indicates a rising trend in total collisions for March. Total crashes increased by 9.9%, from 1,365 in March 2025 to 1,500 in March 2026. Similarly, total injuries rose by 7.1% from 1,060 to 1,135, though total fatalities declined from 5 to 2.
332
Hit-and-Run Crashes — March 2026
▲ 16.5% vs prior (285)
22.1% hit-and-run rate this period vs 20.9% prior. Prior period: 285.
When Crashes Happen
The temporal pattern of crashes shifted between the two periods. In March 2026, Wednesday was the peak day for crashes with 255 incidents, a change from March 2025 when Saturday was the peak day with 211 crashes. Weekday crash counts generally increased year-over-year, while crashes on Sunday decreased from 158 to 148.
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday
Crash Severity Breakdown
While total crashes increased, the severity profile of collisions improved year-over-year. The number of fatal crashes decreased from 5 in March 2025 to 2 in March 2026, with the fatal crash rate dropping from 0.37 to 0.13 per 100 crashes. The share of crashes resulting in an injury also saw a slight decrease, from 77.7% of all crashes in the prior period to 75.7% in the current period.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-03-01 to 2026-03-31 · 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 · 2026-03-01 to 2026-03-31 · Most severe injury per crash record
Top Contributing Factors
In both periods, 'Violations' was the leading contributing factor, increasing in count from 1,066 crashes in March 2025 to 1,209 in March 2026, a 13.4% rise. The share of crashes attributed to violations also grew, from 78.1% to 80.6%. Conversely, crashes attributed to 'Movement prior to crash,' the second-ranked factor, decreased from 248 to 237 incidents.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in both periods predominantly occurred in clear weather, during daylight, and on dry roads. The proportion of crashes happening in adverse conditions remained relatively stable, with crashes in non-daylight conditions accounting for 25.5% of incidents in March 2026 compared to 24.5% in March 2025. The share of crashes on wet road surfaces was nearly unchanged, at 9.2% in the current period versus 9.0% in the prior period.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2026-03-01 to 2026-03-31 · 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: 2026-03-01 through 2026-03-31
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2026-03-01 through 2026-03-31 (31 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,500
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: March 2026." Published June 19, 2026. Reporting period: 2026-03-01 to 2026-03-31. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/march-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: 2026-03-01 – 2026-03-31
Generated: June 19, 2026 · All rights reserved