ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GEORGETOWN, OH · 2022
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/georgetown/2022-annual-report
Yearly Traffic Safety Analysis
31 CRASHES IN
GEORGETOWN, OH
2022
Total crashes in Georgetown increased by 10.7% year-over-year, rising from 28 crashes in the prior year to 31 crashes in the current year. The most notable shift was a significant increase in hit-and-run crashes, which more than doubled during this period.
31
▲ 10.7%was 28
Total Crash Events
0
Persons Killed
7
▼ -22.2%was 9
Persons Injured
7
▲ 133.3%was 3
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in Georgetown saw an increase of 10.7%, rising from 28 in the prior year to 31 in the current year. Despite this increase in total crashes, the number of total injuries decreased by 22.2%, from 9 to 7, while fatalities remained at 0 in both years.
7
Hit-and-Run Crashes — 2022
▲ 133.3% vs prior (3)
Hit-and-run crashes experienced a significant increase, rising by 133.3% from 3 crashes in the prior year to 7 crashes in the current year. This resulted in the hit-and-run crash rate more than doubling, from 10.7% to 22.6% of all crashes.
Vulnerable Road User Casualties
0
Motorists Killed
7
Motorists Injured
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Wednesday in the prior year to Tuesday in the current year, with both days recording 8 crashes. The peak hour also changed, moving from 2 p.m. with 5 crashes in the prior year to 8 a.m. with 4 crashes in the current year.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There was a shift in injury severity, with the current year recording 1 serious injury crash (3.2%) compared to 0 in the prior year. Minor injury crashes decreased by 40%, from 5 crashes (17.9%) in the prior year to 3 crashes (9.7%) in the current year. Possible injury crashes remained stable at 1 crash in both periods.
Outcome by Severity (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased by 36.8%, from 19 in the prior year to 26 in the current year. Conversely, crashes during rain decreased by 50%, from 4 to 2. The number of crashes on dry road surfaces increased by 21.1%, from 19 to 23, while crashes on wet surfaces remained at 8 for both periods.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 51 in the prior year to 53 in the current year. Ford remained the most frequently involved make, increasing from 12 to 14 vehicles, while Dodge involvement saw a 150% increase, rising from 2 to 5 vehicles. The 16-20 age group saw a substantial 240% increase in persons involved, rising from 5 to 17.
Top Vehicle Makes (53 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
2 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (63 persons with recorded sex)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: July 5, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: Georgetown, OH
- Total crash records analyzed: 31
- Total persons involved: 67
- Total vehicles involved: 53
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). "Georgetown, OH Crash Intelligence Report: 2022." Published July 5, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/georgetown/2022-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: 2022-01-01 – 2022-12-31
Generated: July 5, 2026 · All rights reserved