ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · NOVEMBER 2023
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-2023-report
Monthly Traffic Safety Analysis
1,250 CRASHES IN
BATON ROUGE, LA
NOVEMBER 2023
In November 2023, Baton Rouge recorded 1,250 vehicle crashes, a slight increase from the 1,239 crashes reported in November 2022. While overall crash volume remained stable, the number of 'Sideswipe - same direction' collisions increased by 33.9% year-over-year, rising from 180 to 241 incidents.
1,250
▲ 0.9%was 1,239
Total Crash Events
3
▲ 50.0%was 2
Fatal Crashes
963
▲ 2.9%was 936
Injury Crashes
299
▲ 6.0%was 282
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 · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year, total crashes in Baton Rouge saw a minor increase of 0.9%, from 1,239 in November 2022 to 1,250 in November 2023. This upward trend was also reflected in crash outcomes, with total injuries rising by 2.9% from 936 to 963, and fatalities increasing from two to three.
299
Hit-and-Run Crashes — November 2023
▲ 6.0% vs prior (282)
Hit-and-run incidents increased in both count and as a proportion of total crashes in November 2023 compared to the same month in 2022. The total number of hit-and-run crashes rose from 282 to 299, an increase of 6.0%. This pushed the hit-and-run rate up from 22.8% to 23.9% of all crashes, indicating an upward trend.
When Crashes Happen
The temporal pattern of crashes shifted between November 2022 and November 2023. The peak day for collisions moved from Wednesday (233 crashes) in the prior year to Thursday (236 crashes) in the current year. This change was driven by a 43.9% increase in Thursday crashes, which rose from 164 to 236 year-over-year, while crashes on Wednesday and Friday saw decreases.
Source: Baton Rouge Crash Data · Socrata Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday
Crash Severity Breakdown
Crash severity worsened slightly in November 2023 compared to the previous year. The number of fatal crashes increased from two to three, and the overall fatal crash rate rose from 0.16% to 0.24%. The proportion of crashes resulting in an injury also increased, from 75.5% of all crashes in November 2022 to 77.0% in November 2023. Correspondingly, the share of crashes with no reported injuries decreased from 24.3% to 22.7%.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2023-11-01 to 2023-11-30 · 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 · 2023-11-01 to 2023-11-30 · Most severe injury per crash record
Top Contributing Factors
The ranking of the top two contributing factors remained unchanged year-over-year, though their counts trended in opposite directions. 'Violations' remained the primary factor in both periods but saw its count decrease by 1.6% from 955 to 940 incidents. Conversely, crashes attributed to 'Movement prior to crash' increased by 19.5%, from 220 in November 2022 to 263 in November 2023. The count for 'Driver condition' as a factor fell by 28.1%, from 32 to 23.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring during adverse weather and on wet road surfaces increased from November 2022 to November 2023. The number of crashes in rainy conditions rose by 26.0% from 123 to 155, and collisions on wet roads increased by 27.8% from 169 to 216. Consequently, the share of total crashes happening on non-dry road surfaces grew from 14.1% to 17.5% year-over-year. In contrast, the proportion of crashes in dark or low-light conditions decreased from 40.8% to 37.4%.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2023-11-01 through 2023-11-30 (30 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,250
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 2023." Published June 19, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/november-2023-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: 2023-11-01 – 2023-11-30
Generated: June 19, 2026 · All rights reserved