ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · NOVEMBER 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/november-2024-report
Monthly Traffic Safety Analysis
1,389 CRASHES IN
BATON ROUGE, LA
NOVEMBER 2024
In November 2024, Baton Rouge recorded 1,389 total vehicle crashes, an 11.1% increase from the 1,250 crashes documented in November 2023. While the number of fatalities remained stable at three for both periods, the total number of injuries rose from 963 to 1,083. One of the most notable shifts was the peak day for crashes, which moved from Thursday in the prior year to Friday in the current period.
1,389
▲ 11.1%was 1,250
Total Crash Events
3
Fatal Crashes
1,083
▲ 12.5%was 963
Injury Crashes
287
▼ -4.0%was 299
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 · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year crash data for November indicates a rising trend in traffic collisions in Baton Rouge. Total crashes increased by 11.1%, from 1,250 in November 2023 to 1,389 in November 2024. This was accompanied by a 12.5% rise in total injuries, which grew from 963 to 1,083, while fatalities held steady at three in both periods.
287
Hit-and-Run Crashes — November 2024
▼ -4.0% vs prior (299)
Hit-and-run incidents showed a downward trend year-over-year. The total number of hit-and-run crashes decreased from 299 in November 2023 to 287 in November 2024. Correspondingly, the hit-and-run rate, which measures the percentage of all crashes that are hit-and-runs, fell from 23.9% to 20.7%.
When Crashes Happen
The temporal patterns of crashes showed a notable shift between November 2023 and November 2024. The peak day for collisions moved from Thursday, which saw 236 crashes in the prior year, to Friday, with 261 crashes in the current period. Crashes on Fridays increased from 165 to 261 year-over-year, while crashes on Thursdays decreased from 236 to 176.
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday
Crash Severity Breakdown
The number of fatal crashes remained unchanged at three in both November 2023 and November 2024, causing the fatal crash rate to slightly decrease from 0.24% to 0.22% due to the higher total crash volume. The proportion of crashes resulting in an injury increased slightly, accounting for 78.0% of all incidents (1,083 crashes) in the current period compared to 77.0% (963 crashes) in the prior year. Consequently, the share of non-injury crashes decreased from 22.7% to 21.8%.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-11-01 to 2024-11-30 · 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 · 2024-11-01 to 2024-11-30 · Most severe injury per crash record
Top Contributing Factors
Violations remained the leading contributing factor in both periods, with the count of such crashes rising from 940 in November 2023 to 1,005 in November 2024, a 6.9% increase in count. However, its share of all factors decreased from 75.2% to 72.4%. The second-ranked factor, 'Movement prior to crash,' saw its count grow by 25.9% from 263 to 331 incidents, and its share of crashes increased from 21.0% to 23.8%.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in adverse weather conditions, such as rain or clouds, decreased from 21.0% in November 2023 to 17.7% in November 2024. Similarly, crashes on non-dry road surfaces declined as a share of the total, from 17.5% to 15.2%. In contrast, the share of collisions happening in dark or low-light conditions increased, rising from 35.5% of all crashes in the prior year to 37.6% in the current period.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2024-11-01 through 2024-11-30 (30 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,389
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: November 2024." Published June 19, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/november-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: 2024-11-01 – 2024-11-30
Generated: June 19, 2026 · All rights reserved