ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · SEPTEMBER 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/september-2025-report
Monthly Traffic Safety Analysis
1,322 CRASHES IN
BATON ROUGE, LA
SEPTEMBER 2025
In September 2025, Baton Rouge recorded 1,322 total vehicle crashes, a 4.7% increase from the 1,263 crashes documented in September 2024. While total collisions and injuries (1,006 vs. 984) rose, fatalities decreased from 5 to 4. A notable shift occurred in the weekly crash pattern, with Tuesday replacing Friday as the day with the highest number of incidents.
1,322
▲ 4.7%was 1,263
Total Crash Events
4
▼ -20.0%was 5
Fatal Crashes
1,006
▲ 2.2%was 984
Injury Crashes
317
▲ 13.2%was 280
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 · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Baton Rouge show an increase year-over-year for the month of September. Total collisions rose by 4.7%, from 1,263 to 1,322, and total injuries increased by 2.2%, from 984 to 1,006. In contrast, the number of fatalities resulting from these crashes declined from 5 in the prior year to 4 in the current period.
317
Hit-and-Run Crashes — September 2025
▲ 13.2% vs prior (280)
Hit-and-run incidents trended upward in September 2025 compared to the same month in 2024. The total count of hit-and-run crashes increased by 13.2%, rising from 280 to 317. This increase is also reflected in the hit-and-run rate, which climbed from 22.2% to 24.0% of all crashes, indicating that a larger proportion of collisions involved a driver leaving the scene.
When Crashes Happen
The temporal pattern of crashes shifted year-over-year. In September 2025, Tuesday was the peak day for collisions with 250 incidents, a change from September 2024 when Friday was the peak day with 226 incidents. While Friday remained a high-crash day in the current period with 229 incidents, the highest concentration of crashes moved to earlier in the week.
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday
Crash Severity Breakdown
The severity of crashes showed a mixed profile compared to the previous year. The number of fatal crashes decreased from 5 to 4, lowering the fatality rate from 0.4% to 0.3% of all crashes. While the absolute number of injuries increased, the proportion of crashes resulting in an injury slightly decreased from 77.9% to 76.1%. Conversely, the share of non-injury crashes rose from 21.7% to 23.6%.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-09-01 to 2025-09-30 · 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 · 2025-09-01 to 2025-09-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, though their counts shifted. 'Violations' was the top factor in both periods, with its count increasing by 12.5% from 969 to 1,090 incidents. 'Movement prior to crash' remained the second-ranked factor, but its count decreased by 22.4% from 246 to 191 incidents. The share of crashes attributed to 'Violations' also grew from a 76.7% share to an 82.5% share.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in September 2025 occurred under significantly better environmental conditions compared to the prior year. The number of crashes during rain dropped from 124 to 32, and incidents on wet roads fell from 168 to 44. Consequently, the proportion of crashes in clear weather and on dry roads increased, with 94.2% of crashes occurring in clear conditions this year versus 81.6% last year. The share of crashes in daylight also increased from 74.3% to 76.5%.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2025-09-01 through 2025-09-30 (30 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,322
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: September 2025." Published June 19, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/september-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: 2025-09-01 – 2025-09-30
Generated: June 19, 2026 · All rights reserved