ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GREENVILLE, OH · 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/ohio/greenville/2024-annual-report
Yearly Traffic Safety Analysis
382 CRASHES IN
GREENVILLE, OH
2024
Total crashes in Greenville decreased by 7.51% year-over-year, from 413 crashes in the prior period to 382 crashes in the current period. The most significant year-over-year shift was a 66.67% decrease in total fatalities, falling from 3 to 1. This period also saw a 10.67% reduction in total injuries.
382
▼ -7.5%was 413
Total Crash Events
1
▼ -66.7%was 3
Persons Killed
134
▼ -10.7%was 150
Persons Injured
33
▲ 17.9%was 28
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in Greenville experienced a downward trend year-over-year. The total number of crashes decreased by 31, representing a 7.51% reduction compared to the prior period.
33
Hit-and-Run Crashes — 2024
▲ 17.9% vs prior (28)
Hit-and-run crashes increased by 17.86% year-over-year, rising from 28 crashes in the prior period to 33 in the current period. Consequently, the hit-and-run crash rate increased from 6.8% to 8.6% of all crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Motorists Killed
4
Pedestrians Injured
130
Motorists Injured
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Friday in both periods, with 76 crashes in the current period compared to 72 in the prior period. The peak hour for crashes also remained 3 p.m., although the count at this hour decreased slightly from 44 to 43. Crashes occurring during early morning hours (6 a.m. and 7 a.m.) decreased, while crashes in mid-afternoon (1 p.m., 2 p.m., 4 p.m., and 5 p.m.) generally increased.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Total fatalities decreased by 66.67%, from 3 in the prior period to 1 in the current period, leading to a fatal crash rate reduction from 0.73% to 0.26%. Total injuries also saw a decrease of 10.67%, falling from 150 to 134. The proportion of minor injury crashes decreased from 12.6% to 10.7%, while the proportion of no-injury crashes increased from 76.3% to 78%.
Outcome by Severity (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Road & Environmental Conditions
Crashes occurring in daylight conditions increased from 232 to 266, while crashes in dark conditions (both unlighted and lighted roadways) collectively decreased by 55. There was a notable increase in crashes on snow-covered roads, rising from 12 to 25. Crashes in clear weather conditions decreased slightly from 283 to 278, and crashes on dry road surfaces decreased from 332 to 294.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 6.35%, from 709 to 664. Passenger cars, sport utility vehicles, and pickup trucks all experienced decreases in their involvement counts. Ford became the most frequently involved vehicle make with 119 vehicles, surpassing Chevrolet which had 110 vehicles involved in the current period.
Top Vehicle Makes (664 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
35 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (778 persons with recorded sex)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Ohio Crash Data (ODOT TIMS), accessed programmatically via the Csv 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: Csv 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: 2024-01-01 through 2024-12-31
- Report generated: July 5, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: Greenville, OH
- Total crash records analyzed: 382
- Total persons involved: 800
- Total vehicles involved: 664
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). "Greenville, OH Crash Intelligence Report: 2024." Published July 5, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/greenville/2024-annual-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: Ohio Crash Data (ODOT TIMS) · Csv
Period: 2024-01-01 – 2024-12-31
Generated: July 5, 2026 · All rights reserved