ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BATON ROUGE, LA · DECEMBER 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/december-2024-report
Monthly Traffic Safety Analysis
1,293 CRASHES IN
BATON ROUGE, LA
DECEMBER 2024
In December 2024, Baton Rouge recorded 1,293 total vehicle crashes, a 9.9% increase from the 1,177 crashes in December 2023. This rise in collisions was accompanied by a 10.9% increase in injuries, from 911 to 1,010, though total fatalities decreased from 6 to 5. A notable year-over-year shift was the significant increase in the number and proportion of crashes occurring on wet roads, which rose from 139 to 216 incidents.
1,293
▲ 9.9%was 1,177
Total Crash Events
5
▼ -16.7%was 6
Fatal Crashes
1,010
▲ 10.9%was 911
Injury Crashes
290
▼ -0.7%was 292
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 · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Baton Rouge showed a rising trend year-over-year, with total collisions increasing by 9.9% from 1,177 in December 2023 to 1,293 in December 2024. This was paralleled by a 10.9% increase in total injuries, which climbed from 911 to 1,010. In contrast, the number of fatalities saw a slight decrease from 6 to 5 over the same period.
290
Hit-and-Run Crashes — December 2024
▼ -0.7% vs prior (292)
The number of hit-and-run crashes decreased slightly from 292 in December 2023 to 290 in December 2024. Despite an overall increase in total collisions, the hit-and-run rate trended downward, declining from 24.8% of all crashes in the prior year to 22.4% in the current period.
When Crashes Happen
The temporal pattern of crashes shifted year-over-year, with the peak day for incidents moving from Friday (255 crashes) in December 2023 to Monday (240 crashes) in December 2024. The number of crashes on Mondays increased substantially from 148 in the prior period. Detailed hourly data was not available for a more granular comparison.
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday
Crash Severity Breakdown
While the total number of crashes increased, the fatal crash rate decreased from 0.51% to 0.39% year-over-year, with fatal crashes dropping from 6 to 5. Conversely, the proportion of crashes resulting in an injury increased slightly, rising from 77.4% of all crashes in the prior period to 78.1% in the current period. The total number of injuries grew from 911 to 1,010.
Outcome by Severity (Crash Events)
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-12-01 to 2024-12-31 · 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 · 2024-12-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The primary contributing factors remained consistent, with "Violations" and "Movement prior to crash" ranking first and second in both periods. The count of crashes attributed to violations grew by 9.4% from 876 to 958, though its share of all crashes remained stable at approximately 74%. Crashes linked to "Driver condition" also increased in count from 22 to 27.
Officer-Reported Primary Contributing Cause
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
There was a notable increase in crashes occurring under adverse conditions compared to the prior year. The number of crashes on wet road surfaces rose by 55.4%, from 139 to 216 incidents, and crashes during rain increased by 63.8% from 94 to 154. As a result, the proportion of total crashes happening on wet roads increased from 11.8% to 16.7% year-over-year.
Weather
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Baton Rouge Crash Data · Socrata Open Data · 2024-12-01 to 2024-12-31 · 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: 2024-12-01 through 2024-12-31
- Report generated: June 19, 2026
Data Coverage
- Reporting period: 2024-12-01 through 2024-12-31 (31 days)
- Geographic scope: Baton Rouge, LA
- Total crash records analyzed: 1,293
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: December 2024." Published June 19, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Baton Rouge Crash Data, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/louisiana/baton-rouge/december-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: 2024-12-01 – 2024-12-31
Generated: June 19, 2026 · All rights reserved