ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GREEN, OH · 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/ohio/green/2023-annual-report
Yearly Traffic Safety Analysis
3,027 CRASHES IN
GREEN, OH
2023
Total crashes decreased by 2.04% from 3090 in the prior year to 3027 in the current year. Fatalities saw a significant decrease of 44.44%, falling from 18 to 10. Meanwhile, total injuries experienced a slight increase of 1.19%, rising from 926 to 937. The most notable year-over-year shift was the substantial reduction in fatalities.
3,027
▼ -2.0%was 3,090
Total Crash Events
10
▼ -44.4%was 18
Persons Killed
937
▲ 1.2%was 926
Persons Injured
363
▼ -3.5%was 376
Hit-and-Run Crashes
Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (10) 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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the total number of crashes decreased by 2.04%, from 3090 crashes in the prior year to 3027 crashes in the current year. This decline indicates a downward trend in overall crash incidents. Fatalities also saw a significant decrease of 44.44%, dropping from 18 to 10, while total injuries increased by 1.19%, from 926 to 937.
363
Hit-and-Run Crashes — 2023
▼ -3.5% vs prior (376)
Hit-and-run crashes decreased by 3.46%, from 376 in the prior year to 363 in the current year. The hit-and-run crash rate also saw a slight decrease, moving from 12.2% in the prior year to 12% in the current year. This indicates a minor downward trend in hit-and-run incidents.
Vulnerable Road User Casualties
1
Pedestrians Killed
9
Motorists Killed
9
Pedestrians Injured
928
Motorists Injured
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · 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 520 crashes in the current year compared to 500 in the prior year. The peak hour for crashes shifted from 5 p.m. in the prior year (257 crashes) to 3 p.m. in the current year (261 crashes). Monthly fatality distribution varied, with the current year recording 3 fatalities in February and 2 in April and October, while the prior year saw 4 fatalities in June and 3 in May.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate decreased from 0.55% of total crashes in the prior year to 0.33% in the current year, corresponding to a drop from 17 to 10 fatal crashes. Serious injuries (Severity A) increased from 51 (1.7%) in the prior year to 75 (2.5%) in the current year. Minor injuries (Severity B) slightly decreased from 357 (11.6%) to 341 (11.3%), while possible injuries (Severity C) increased from 224 (7.2%) to 260 (8.6%).
Outcome by Severity (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Road & Environmental Conditions
Crashes occurring in rainy conditions increased by 31.1% from 299 in the prior year to 392 in the current year. Conversely, crashes in snowy conditions decreased by 52.8%, from 163 to 77. Crashes on wet road surfaces increased from 587 to 658, while those on icy surfaces decreased from 42 to 10. Daylight crashes decreased slightly from 2040 to 2009.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 5364 in the prior year to 5264 in the current year. The number of motorcycles (2-wheeled) involved in crashes increased from 33 to 44. Ford became the most frequently involved vehicle make in the current year with 830 vehicles, surpassing Chevrolet which had 813 vehicles in the prior year.
Top Vehicle Makes (5,264 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
302 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (6,557 persons with recorded sex)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: July 5, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: Green, OH
- Total crash records analyzed: 3,027
- Total persons involved: 6,798
- Total vehicles involved: 5,264
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). "Green, OH Crash Intelligence Report: 2023." Published July 5, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/green/2023-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: 2023-01-01 – 2023-12-31
Generated: July 5, 2026 · All rights reserved