Yearly Traffic Safety Analysis

1,267 CRASHES IN
OHIO, OH
2021

In 2021, Belmont County recorded 1,267 traffic crashes, resulting in 8 fatalities and 409 injuries. These incidents involved 1,982 vehicles and 2,548 individuals. A notable finding is that single-vehicle crashes, categorized as 'Not Collision Between Two Vehicles in Transport', constituted the majority of incidents, accounting for 52.3% of the total.

1,267

Total Crash Events

8

Persons Killed

409

Persons Injured

10.8%

Hit-and-Run Rate

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (7) 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

137

Hit-and-Run Crashes — 2021

During this period, 137 crashes were classified as hit-and-run incidents, representing 10.8% of all crashes in the county. This classification is based on the initial determination made by the responding law enforcement officer at the scene of the crash.

Vulnerable Road User Casualties

All 8 fatalities recorded in 2021 were motorists. In total, 406 motorists were injured. Additionally, 3 pedestrians were injured in crashes during this period, though no pedestrian fatalities were reported. There were no recorded fatalities or injuries involving bicyclists.

0

Pedestrians Killed

8

Motorists Killed

3

Pedestrians Injured

406

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 analysis by time reveals specific patterns, with Wednesdays seeing the highest frequency of incidents (211 crashes). The afternoon rush hour is the most hazardous time, with the peak hour for crashes occurring at 2 p.m. (91 crashes) and a sustained high volume of incidents from 1 p.m. through 7 p.m.

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 1,267 total crashes, 7 were classified as fatal. The majority of crashes (75.2%, or 953 incidents) resulted in no injuries. Injury-related crashes accounted for 24.2% of the total, comprising 30 serious injury, 136 minor injury, and 141 possible injury crashes. The 7 fatal crashes resulted in a total of 8 fatalities, as a single crash can involve more than one death.

Severity is per crash event (most severe injury). 7 fatal crash events resulted in 8 persons killed.

Outcome by Severity (Crash Events)

Fatal7fatal crashes0.6%
Serious Injury30serious injury crashes2.4%
Minor Injury136minor injury crashes10.7%
Possible Injury141possible injury crashes11.1%
No Injury953no injury crashes75.2%

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

A significant portion of crashes occurred in seemingly ideal conditions, with 58.0% on clear days, 75.0% on dry road surfaces, and 61.7% during daylight hours. Adverse conditions were also a factor in many incidents; 136 crashes occurred during rain, 45 in snow, and 413 took place in dark or dawn/dusk lighting conditions.

Weather

Clear735 (58.0%)
Cloudy334 (26.4%)
Rain136 (10.7%)
Snow45 (3.6%)
Fog; Smog; Smoke6 (0.5%)
Sleet; Hail5 (0.4%)
Other/Unknown3 (0.2%)
Freezing Rain or Freezing Drizzle3 (0.2%)

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

Lighting

Daylight782 (61.7%)
Dark - Roadway Not Lighted284 (22.4%)
Dark - Lighted Roadway129 (10.2%)
Dawn/Dusk62 (4.9%)
Dark - Unknown Roadway Lighting5 (0.4%)
Other/Unknown5 (0.4%)

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

Road Surface

Dry950 (75.0%)
Wet237 (18.7%)
Snow45 (3.6%)
Ice25 (2.0%)
Slush6 (0.5%)
Sand; Mud; Dirt; Oil; Gravel3 (0.2%)
Other/Unknown1 (0.1%)

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

Vehicles & Demographics

Analysis of persons involved in crashes shows the 26-34 age group was the most represented, with 386 individuals. Among the 1,982 vehicles involved, the most frequent makes were Chevrolet (370 vehicles), Ford (265 vehicles), and Honda (130 vehicles).

Top Vehicle Makes (1,982 vehicles)

1
CHEVROLET370 (18.7%)
2
FORD265 (13.4%)
3
HONDA130 (6.6%)
4
DODGE123 (6.2%)
5
TOYOTA119 (6%)
6
JEEP98 (4.9%)
7
NISSAN90 (4.5%)
8
KIA72 (3.6%)
9
FREIGHTLINER66 (3.3%)
10
HYUNDAI65 (3.3%)

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

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

Sex Distribution (2,470 persons with recorded sex)

Male1,448 (58.6%)
Female1,022 (41.4%)

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)

The initial point of impact for most crashes was on the primary roadway, accounting for 834 incidents. However, a substantial number of crashes involved vehicles leaving the travel lanes. Run-off-road events, including crashes on the roadside (295), shoulder (36), and median (15), collectively represent 27.5% of all crashes where the location was specified.

Crash Location (First Harmful Event)

"Other" combines 4 smaller categories (19 records): Other/Unknown (9), Driveway/Alley access (8), Crossover (1), On Gore (1).

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 vehicle units were involved in crashes at locations with no traffic control devices, accounting for 1,594 of 1,982 units. In contrast, 201 units were in crashes at locations with a traffic signal, and 171 units were at locations controlled by a stop sign.

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

Analysis of driver actions reveals that driving off the road was the most cited contributing factor, noted for 210 units. This was followed by unsafe speed (176 units), following too closely (168 units), and failure to yield (137 units).

Driver Contributing Factor

1
Drove off Road210 (19.4%)
2
Unsafe Speed176 (16.3%)
3
Following too Close / ACDA168 (15.5%)
4
Failure to Yield137 (12.7%)
5
Improper Lane Change70 (6.5%)
6
Left of Center68 (6.3%)
7
Other Improper Action51 (4.7%)
8
Improper Backing46 (4.3%)
9
Improper Turn27 (2.5%)

Showing top 9 of 21 reported. 12 additional (129 total) not shown: Not Discernible, Load shifting/Falling/Spilling, Swerving to Avoid, Operating Defective Equipment, Improper Passing, Ran Red Light, Ran Stop Sign, Vision Obstruction, Improper Crossing, Stopped or Parked Illegally, Improper Start From a Parked Position, Wrong Way.

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

Commercial / Truck Involvement

Crashes involved a total of 204 commercial trucks. Of these, 151 were identified as semi-tractor trailers and 53 were classified as other types of commercial vehicles.

Vulnerable Road Users & Motorcycles

A total of 27 crashes involved motorcyclists or vulnerable road users. This group included 23 motorcyclists, 3 pedestrians, and 1 bicyclist.

Animal-Involved Crashes

Crashes involving animals accounted for 133 incidents, representing 10.5% of all crashes in the county. The vast majority of these, 129 crashes, specifically involved deer.

Impairment (Alcohol / Drugs)

Impairment was a factor in 94 crashes, constituting 7.4% of the total. Among these, alcohol was suspected in 47 incidents, drugs in 25, and a combination of alcohol and drugs in 22.

Driver Condition

Among 1,892 drivers with a recorded condition, 92 were noted as being under the influence of medications, drugs, or alcohol. An additional 37 drivers were identified as having fallen asleep, fainted, or been fatigued at the time of their crash.

Driver Condition

1
Apparently Normal1,643 (87.9%)
2
Under the Influence of Medications / Drugs / Alcohol92 (4.9%)
3
Other/Unknown91 (4.9%)
4
Fell Asleep; Fainted; Fatigued; etc.37 (2%)
5
Physical Impairment4 (0.2%)
6
Emotional (E.G.; Depressed; Angry; Disturbed)2 (0.1%)
7
Illness1 (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

Driver Distraction

For drivers where a distraction was noted, the most common were other distractions inside the vehicle (29 drivers) and outside the vehicle (22 drivers). Manually operating an electronic communication device was a factor for 8 drivers, while other activities with an electronic device distracted 6 drivers.

Driver Distraction

1
Not Distracted1,684 (91.1%)
2
Other/Unknown95 (5.1%)
3
Other distraction inside the vehicle29 (1.6%)
4
Other distraction outside the vehicle22 (1.2%)
5
Manually operating an electronic communication device (texting; typing; dialing)8 (0.4%)
6
Other activity with an electronic device6 (0.3%)
7
Passenger4 (0.2%)
8
Talking on hand-held 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

Roadway geometry played a role in many crashes, with 49.3% of incidents occurring on a grade (either straight or curved). Crashes on curves accounted for 22.3% of the total, with 208 of these happening on a curve with a grade.

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 is concentrated in a few key areas. The top three locations, Richland (325 crashes), Pease (127 crashes), and Pultney (104 crashes), together account for 43.9% of all incidents in the county.

Top Cities

1
Richland325 (25.7%)
2
Pease127 (10%)
3
Pultney104 (8.2%)
4
Bridgeport95 (7.5%)
5
Union83 (6.6%)
6
Kirkwood66 (5.2%)
7
Colerain58 (4.6%)
8
Mead55 (4.3%)
9
Barnesville51 (4%)

Showing top 9 of 28 reported. 19 additional (303 total) not shown: St. Clairsville, Bellaire, Wheeling, Warren, Somerset, Goshen, Flushing, Smith, York, Powhatan Point, Wayne, Washington, Bethesda, Shadyside, Belmont, Holloway, Fairview, Neffs, Martins Ferry.

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 vehicles involved was driving straight ahead, which was the case for 1,061 of the 1,982 vehicles (53.5%). The next most frequent actions were negotiating a curve (221 vehicles) and slowing or stopped in traffic (194 vehicles).

Pre-Crash Driver Action

1
Straight Ahead1,061 (53.5%)
2
Negotiating a Curve221 (11.2%)
3
Slowing or Stopped In Traffic194 (9.8%)
4
Making Left Turn127 (6.4%)
5
Parked79 (4%)
6
Changing Lanes67 (3.4%)
7
Making Right Turn63 (3.2%)
8
Backing61 (3.1%)
9
Entering Traffic Lane46 (2.3%)

Showing top 9 of 16 reported. 7 additional (63 total) not shown: Overtaking/Passing, Other/Unknown, Leaving Traffic Lane, Driverless, Making U-Turn, Standing, Walking; Running; Jogging; Playing.

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

Manner of Collision

Single-vehicle crashes, classified as 'Not Collision Between Two Vehicles in Transport', were the most frequent type, accounting for 663 incidents or 52.3% of all crashes. Among multi-vehicle incidents, rear-end collisions were the most common, with 188 crashes (14.8%).

Manner of Collision

"Other" combines 2 smaller categories (21 records): Head-on (18), Rear-to-rear (3).

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, accounting for 780 of the 1,982 total vehicles. Sport Utility Vehicles (477) and Pick-up trucks (376) were the next most frequent types.

Vehicle Type

"Other" combines 9 smaller categories (65 records): Motorcycle 2 Wheeled (23), Cargo Van (22), Farm Equipment (6), Van (9-15 Seats) (4), Pedestrian/Skater (3), Bus (16+ Passengers) (3), Other Vehicle (2), Bicycle (1), All Terrain Vehicle (ATV/UTV) (1).

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

Person Type

Of the 2,548 people involved in crashes, the majority (1,892, or 74.3%) were drivers. Passengers, classified as occupants, comprised the next largest group with 651 individuals (25.5%). A small fraction, 5 individuals (0.2%), were pedestrians.

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 all 2,548 persons involved in crashes, 8 sustained fatal injuries and 37 suffered serious injuries. A total of 409 individuals experienced some level of injury, while 2,078 reported no injury.

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

Out of 2,540 occupants whose safety equipment use was recorded, 128 individuals (5.0%) were reported as not using any restraints. The majority, 1,986 occupants, were recorded as using both a shoulder and lap belt.

Occupant Safety Equipment

"Other" combines 2 smaller categories (27 records): Lap Belt Only Used (16), Helmet Used (11).

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

Two-vehicle crashes were the most common scenario, accounting for 634 incidents or 50.0% of the total. Single-vehicle crashes were also very common, with 594 incidents (46.9%). Crashes involving three or more vehicles were far less frequent, making up only 3.1% of the total.

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: 1,267
  • Total persons involved: 2,548
  • Total vehicles involved: 1,982

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