ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · APRIL 2024
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-2024-report
Monthly Traffic Safety Analysis
1,275 CRASHES IN
BATON ROUGE, LA
APRIL 2024
In April 2024, Baton Rouge recorded 1,275 total crashes, an increase of 5.5% from the 1,209 crashes reported in April 2023. Despite the rise in total collisions, the number of fatalities saw a significant decrease, dropping from 5 in the prior year period to 1 in the current period.
1,275
▲ 5.5%was 1,209
Total Crash Events
1
▼ -80.0%was 5
Fatal Crashes
1,022
▲ 8.8%was 939
Injury Crashes
291
▲ 10.6%was 263
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 · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year data for April indicates an upward trend in traffic collisions in Baton Rouge. Total crashes rose by 5.5%, from 1,209 in April 2023 to 1,275 in April 2024. The number of reported injuries also increased by 8.8% during the same period, from 939 to 1,022.
291
Hit-and-Run Crashes — April 2024
▲ 10.6% vs prior (263)
The number of hit-and-run incidents in Baton Rouge increased from April 2023 to April 2024. The total count of hit-and-run crashes rose from 263 to 291, an increase of 10.6%. The hit-and-run rate, which measures the percentage of all crashes that were hit-and-runs, also trended upward, climbing from 21.8% to 22.8% over the same period.
When Crashes Happen
The daily pattern of crashes shifted between April 2023 and April 2024. The peak day for collisions moved from Thursday (205 crashes) in the prior year to a tie between Tuesday and Friday (221 crashes each) in the current year. Crashes on Mondays and Tuesdays increased, rising from 160 to 219 and 158 to 221, respectively. Conversely, weekend crashes saw a decline, with Saturday incidents falling from 187 to 151 and Sunday incidents from 141 to 101.
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday
Crash Severity Breakdown
While total crashes increased, the number of fatal crashes decreased from 5 in April 2023 to 1 in April 2024. Consequently, the share of fatal crashes dropped from 0.4% to 0.1% of all incidents. The proportion of crashes resulting in an injury increased, rising from 77.7% (939 crashes) in the prior period to 80.2% (1,022 crashes) in the current period. Crashes with no reported injuries saw a corresponding decrease in their share, from 21.9% to 19.8%.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-04-01 to 2024-04-30 · 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 · 2024-04-01 to 2024-04-30 · Most severe injury per crash record
Top Contributing Factors
The ranking of the top three contributing factors remained consistent year-over-year, with 'Violations' being the most cited factor in both periods. Crashes attributed to 'Violations' increased by 10.2% in count, from 904 in April 2023 to 996 in April 2024. The second-ranked factor, 'Movement prior to crash,' saw a decrease in count from 254 to 239 incidents. Crashes related to 'Driver condition,' the third most common factor, increased from 23 to 26.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In both April 2023 and April 2024, the vast majority of crashes occurred in clear weather, during daylight hours, and on dry roads. However, there was a notable year-over-year decrease in crashes under adverse conditions. Collisions during rain fell from 79 to 32, and crashes on wet road surfaces decreased from 116 to 51. As a proportion of all crashes, incidents on wet roads dropped from 9.6% in the prior period to 4.0% in the current period.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2024-04-01 through 2024-04-30 (30 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,275
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 2024." Published June 19, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/april-2024-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: 2024-04-01 – 2024-04-30
Generated: June 19, 2026 · All rights reserved