ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHILLICOTHE, OH · 2025
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/chillicothe/2025-annual-report
Yearly Traffic Safety Analysis
658 CRASHES IN
CHILLICOTHE, OH
2025
Chillicothe experienced a 5.96% increase in total crashes year-over-year, rising from 621 crashes in the prior period to 658 crashes in the current period. The most significant shift was the increase in total fatalities, which rose from 0 in the prior period to 2 in the current period. Total injuries also increased by 19.12%, from 136 to 162.
658
▲ 6.0%was 621
Total Crash Events
2
Persons Killed
162
▲ 19.1%was 136
Persons Injured
98
▲ 12.6%was 87
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in Chillicothe increased by 5.96% year-over-year, with 658 crashes recorded in the current period compared to 621 in the prior period. This upward trend was also reflected in total fatalities, which increased from 0 to 2, and total injuries, which rose by 19.12% from 136 to 162.
98
Hit-and-Run Crashes — 2025
▲ 12.6% vs prior (87)
Hit-and-run crashes increased by 12.64% year-over-year, rising from 87 in the prior period to 98 in the current period. The hit-and-run rate also saw a slight increase, moving from 14% in the prior period to 14.9% in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
1
Motorists Killed
14
Pedestrians Injured
148
Motorists Injured
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · 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 Friday in the prior period (120 crashes) to Tuesday in the current period (125 crashes). However, the peak hour for crashes remained consistent at 3 PM in both periods, with 66 crashes recorded at that time in both the current and prior periods.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate increased from 0% in the prior period to 0.3% in the current period, corresponding to 2 fatal crashes. Serious injuries saw an increase in proportion from 0.8% to 1.4% of total crashes, and minor injuries also rose from 7.4% to 9.4%. Conversely, possible injury crashes decreased from 8.7% to 6.8% of the total.
Outcome by Severity (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 386 to 418, while those in rainy conditions decreased from 75 to 63. A notable increase was observed in crashes on snowy road surfaces, rising from 4 in the prior period to 25 in the current period. Crashes during daylight hours increased from 464 to 498.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 7.78%, from 1221 in the prior period to 1316 in the current period. Chevrolet became the most frequently involved vehicle make in the current period with 192 vehicles, surpassing Ford which was highest in the prior period. The 65+ age group became the largest demographic involved in crashes, with 255 persons in the current period, up from 228 in the prior period.
Top Vehicle Makes (1,316 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
87 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,528 persons with recorded sex)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: July 5, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: Chillicothe, OH
- Total crash records analyzed: 658
- Total persons involved: 1,598
- Total vehicles involved: 1,316
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). "Chillicothe, OH Crash Intelligence Report: 2025." Published July 5, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/chillicothe/2025-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: 2025-01-01 – 2025-12-31
Generated: July 5, 2026 · All rights reserved