Yearly Traffic Safety Analysis

671 CRASHES IN
OHIO, OH
2021

In 2021, Holmes County recorded 671 traffic crashes, resulting in 8 fatalities and 291 injuries. A notable characteristic of these incidents is the high proportion of single-vehicle collisions, which accounted for nearly half of all crashes (49.6%). Many of these events occurred off the primary roadway, with 30.2% of crashes originating on the roadside, shoulder, or outside the trafficway.

671

Total Crash Events

8

Persons Killed

291

Persons Injured

6.6%

Hit-and-Run Rate

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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 · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

44

Hit-and-Run Crashes — 2021

There were 44 hit-and-run incidents reported in Holmes County, accounting for 6.6% of all crashes in 2021. This classification is based on the initial determination made by the responding law enforcement officer at the scene of the collision.

Vulnerable Road User Casualties

Motorists comprised the vast majority of those killed or injured in crashes, with 7 fatalities and 287 injuries. One pedestrian was killed and four were injured in separate incidents. No bicyclists were killed or injured during this period.

1

Pedestrians Killed

7

Motorists Killed

4

Pedestrians Injured

287

Motorists Injured

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash frequencies in Holmes County peaked on Fridays, which saw a total of 130 incidents over the year. The single most common time for a crash was the 5 p.m. hour, with 63 occurrences. While the majority of crashes (67.8%) happened during daylight hours, a substantial number of incidents (159) occurred in darkness on unlit roadways.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 671 total crashes, 69.2% (464 incidents) resulted in no injuries, involving only property damage. The remaining 30.8% of crashes involved some level of injury or a fatality. There were 8 fatal crashes recorded during this period, which resulted in a total of 8 fatalities.

Outcome by Severity (Crash Events)

Fatal8fatal crashes1.2%
Serious Injury25serious injury crashes3.7%
Minor Injury98minor injury crashes14.6%
Possible Injury76possible injury crashes11.3%
No Injury464no injury crashes69.2%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The majority of crashes occurred in favorable conditions, with 60.2% happening in clear weather and 80.5% on dry road surfaces. Similarly, 67.8% of all incidents took place during daylight hours. Crashes in adverse conditions included 44 in rain and 43 in snow, while 82 crashes occurred on wet roads and 159 took place on unlit roads after dark.

Weather

Clear404 (60.2%)
Cloudy165 (24.6%)
Rain44 (6.6%)
Snow43 (6.4%)
Fog; Smog; Smoke6 (0.9%)
Severe Crosswinds4 (0.6%)
Freezing Rain or Freezing Drizzle2 (0.3%)
Other/Unknown1 (0.1%)
Blowing Sand; Soil; Dirt; Snow1 (0.1%)
Sleet; Hail1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight455 (67.8%)
Dark - Roadway Not Lighted159 (23.7%)
Dawn/Dusk37 (5.5%)
Dark - Lighted Roadway18 (2.7%)
Dark - Unknown Roadway Lighting2 (0.3%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry540 (80.5%)
Wet82 (12.2%)
Snow39 (5.8%)
Ice8 (1.2%)
Slush2 (0.3%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

Among the 1,672 people involved in crashes, the most represented age groups were 0-15 years old (255 individuals), 26-34 years old (224 individuals), and 16-20 years old (221 individuals). Of the 1,082 vehicles involved, the most frequent makes were Chevrolet and Ford, each with 197 vehicles. These were followed by Honda with 89 vehicles and Toyota with 65 vehicles.

Top Vehicle Makes (1,082 vehicles)

1
CHEVROLET197 (18.2%)
2
FORD197 (18.2%)
3
HONDA89 (8.2%)
4
TOYOTA65 (6%)
5
DODGE62 (5.7%)
6
GMC54 (5%)
7
JEEP53 (4.9%)
8
NISSAN31 (2.9%)
9
CHRYSLER25 (2.3%)
10
MAZDA22 (2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

57 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (1,636 persons with recorded sex)

Male957 (58.5%)
Female679 (41.5%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Crash Location (First Harmful Event)

Analysis of the initial crash location shows that 69.1% of incidents (464 crashes) occurred on the roadway itself. A significant portion, 30.2% or 203 crashes, were run-off-road events where the first harmful event happened on the shoulder (67), roadside (83), or outside the trafficway (53).

Crash Location (First Harmful Event)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Traffic Control Device

The vast majority of vehicles involved in collisions were at locations with no traffic control device present, accounting for 920 of the 1,082 vehicles in the dataset. By comparison, 93 vehicles were involved in crashes at locations with a stop sign and 61 were at intersections with a traffic signal.

Traffic Control Device

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Driver Contributing Factor

Among driver-related actions cited as contributing to crashes, the most common was unsafe speed, noted for 152 vehicles. This was followed by following too closely, which was a factor for 146 vehicles, and failure to yield, cited in 105 instances.

Driver Contributing Factor

1
Unsafe Speed152 (25%)
2
Following too Close / ACDA146 (24.1%)
3
Failure to Yield105 (17.3%)
4
Drove off Road54 (8.9%)
5
Left of Center32 (5.3%)
6
Other Improper Action18 (3%)
7
Improper Passing17 (2.8%)
8
Improper Backing17 (2.8%)
9
Not Discernible16 (2.6%)

Showing top 9 of 21 reported. 12 additional (50 total) not shown: Improper Turn, Swerving to Avoid, Ran Stop Sign, Load shifting/Falling/Spilling, Improper Crossing, Improper Lane Change, Operating Defective Equipment, Ran Red Light, Wrong Way, Improper Start From a Parked Position, Lying in Roadway, Vision Obstruction.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Commercial / Truck Involvement

Crashes involving commercial trucks accounted for 47 incidents, or approximately 7.0% of all crashes. Of these, 28 involved a semi-tractor trailer and 19 involved other types of commercial vehicles.

Vulnerable Road Users & Motorcycles

A total of 34 crashes involved vulnerable road users or motorcyclists. These included 16 crashes with motorcyclists, 13 with bicyclists, and 5 with pedestrians. Combined, crashes involving pedestrians and bicyclists, who are considered the most vulnerable road users, totaled 18 incidents.

Animal-Involved Crashes

Collisions with animals were a factor in 63 crashes, representing 9.4% of the total for the year. The majority of these incidents, 45 crashes, involved deer. An additional 18 crashes involved other types of animals.

Impairment (Alcohol / Drugs)

Impairment was a factor in 24 crashes, or 3.6% of all incidents. Alcohol was involved in 20 of these crashes, a combination of alcohol and drugs was noted in 3, and drugs alone were a factor in 1 crash.

Driver Condition

Excluding drivers noted as 'Apparently Normal,' specific adverse conditions were recorded for 30 of the 1,058 drivers. These included 14 drivers under the influence of medications, drugs, or alcohol, 5 who were ill, 5 with a physical impairment, and 4 who reportedly fell asleep or were fatigued.

Driver Condition

1
Apparently Normal985 (95.4%)
2
Other/Unknown17 (1.6%)
3
Under the Influence of Medications / Drugs / Alcohol14 (1.4%)
4
Illness5 (0.5%)
5
Physical Impairment5 (0.5%)
6
Fell Asleep; Fainted; Fatigued; etc.4 (0.4%)
7
Emotional (E.G.; Depressed; Angry; Disturbed)2 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Driver Distraction

Among 1,058 drivers, 61 were identified as being distracted at the time of the crash. The most common cited distractions were an event or object inside the vehicle (23 drivers) or outside the vehicle (18 drivers). Additionally, 18 drivers were distracted by some form of electronic device, including 5 who were manually operating one.

Driver Distraction

1
Not Distracted953 (92.9%)
2
Other distraction inside the vehicle23 (2.2%)
3
Other distraction outside the vehicle18 (1.8%)
4
Other/Unknown12 (1.2%)
5
Other activity with an electronic device10 (1%)
6
Manually operating an electronic communication device (texting; typing; dialing)5 (0.5%)
7
Passenger2 (0.2%)
8
Talking on hand-held communication device2 (0.2%)
9
Talking on hands-free communication device1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Road Alignment

Road geometry played a role in a significant number of crashes. Over 43% of incidents (291 crashes) occurred on a grade, either straight or curved. Additionally, nearly 21% of crashes (140 incidents) took place on a curve.

Road Alignment

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Top Cities

The geographic distribution of crashes was concentrated in several key areas. The top three locations were Berlin with 98 crashes (14.6% of the total), Millersburg with 83 crashes (12.4%), and Paint township with 70 crashes (10.4%).

Top Cities

1
Berlin98 (14.6%)
2
Millersburg83 (12.4%)
3
Paint70 (10.4%)
4
Hardy53 (7.9%)
5
Walnut Creek49 (7.3%)
6
Salt Creek47 (7%)
7
Washington42 (6.3%)
8
Monroe40 (6%)
9
Mechanic37 (5.5%)

Showing top 9 of 18 reported. 9 additional (152 total) not shown: Clark, Prairie, Killbuck, Knox, Ripley, Richland, Nashville, Holmesville, Glenmont.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Pre-Crash Driver Action

The most common pre-crash action for the 1,082 vehicles involved was driving straight ahead, which accounted for 628 vehicles (58.0%). The second most frequent action was slowing or stopping in traffic, reported for 177 vehicles (16.4%).

Pre-Crash Driver Action

1
Straight Ahead628 (58%)
2
Slowing or Stopped In Traffic177 (16.4%)
3
Making Left Turn86 (7.9%)
4
Negotiating a Curve67 (6.2%)
5
Overtaking/Passing29 (2.7%)
6
Backing26 (2.4%)
7
Making Right Turn19 (1.8%)
8
Entering Traffic Lane17 (1.6%)
9
Parked16 (1.5%)

Showing top 9 of 17 reported. 8 additional (17 total) not shown: Other/Unknown, Changing Lanes, Driverless, Walking; Running; Jogging; Playing, Making U-Turn, Entering or Crossing Specified Location, Approaching or Leaving Vehicle, Other Non-Motorist.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Manner of Collision

Nearly half of all crashes (49.6%) were single-vehicle incidents, categorized as 'Not Collision Between Two Vehicles in Transport' (333 crashes). The most common type of multi-vehicle collision was a rear-end crash, which accounted for 140 incidents or 20.9% of the total.

Manner of Collision

"Other" combines 2 smaller categories (5 records): Rear-to-rear (4), Other/Unknown (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, with 329 units, followed by 281 sport utility vehicles and 232 pickup trucks. Combined, these three vehicle types accounted for 77.8% of all vehicles in collisions.

Vehicle Type

"Other" combines 14 smaller categories (97 records): Motorcycle 2 Wheeled (15), Cargo Van (15), Bicycle (14), Animal with Rider or Animal Drawn Vehicle (12), Unknown or Hit/Skip (10), Farm Equipment (10), Bus (16+ Passengers) (5), Pedestrian/Skater (5), All Terrain Vehicle (ATV/UTV) (4), Other Vehicle (3), Motorhome (1), Motorcycle 3 Wheeled (1), Moped or Motorized Bicycle (1), Heavy Equipment (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Person Type

Of the 1,672 individuals involved in crashes, the majority were either drivers (1,058 people, or 63.3%) or vehicle occupants (609 people, or 36.4%). A small fraction were pedestrians, who accounted for 5 of the individuals involved.

Person Type

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Person Injury Severity

Among the 1,672 people involved in crashes, 8 sustained fatal injuries and 291 suffered non-fatal injuries. The breakdown of non-fatal injuries includes 30 serious injuries, 130 minor injuries, and 131 possible injuries. The vast majority of individuals, 1,345 people, were not injured.

Person Injury Severity

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Occupant Safety Equipment

A total of 215 individuals, or 12.9% of all people involved in crashes, were recorded as not using any safety equipment. The most commonly used form of protection was a shoulder and lap belt, which was utilized by 1,242 people.

Occupant Safety Equipment

"Other" combines 3 smaller categories (26 records): Helmet Used (17), Lap Belt Only Used (8), Lighting - Pedestrian / Bicycle Only (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Vehicles Per Crash

The majority of crashes, 354 incidents (52.8%), involved two vehicles. Single-vehicle crashes were also very common, with 289 incidents representing 43.1% of the total. Multi-vehicle pileups were rare, with only 27 crashes involving three vehicles and one crash involving four.

Vehicles Per Crash

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

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: 2021-01-01 through 2021-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 671
  • Total persons involved: 1,672
  • Total vehicles involved: 1,082

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). "ohio, OH Crash Intelligence Report: 2021." Published July 5, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2021-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

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Holmes County, OH Crash Report — 2021 | ThatCarHitMe.com