Yearly Traffic Safety Analysis

2,492 CRASHES IN
OHIO, OH
2021

In 2021, Muskingum County recorded 2,492 total traffic crashes, resulting in 12 fatalities and 751 injuries. A notable finding from the data is that single-vehicle crashes, categorized as 'Not Collision Between Two Vehicles in Transport,' were the most common crash type, accounting for 1,091 incidents or 43.8% of all crashes.

2,492

Total Crash Events

12

Persons Killed

751

Persons Injured

12.9%

Hit-and-Run Rate

Note: "Persons Killed" (12) counts individual fatalities across all crash events. "Fatal" in the severity table below (12) 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

322

Hit-and-Run Crashes — 2021

There were 322 hit-and-run incidents reported, which constitutes 12.9% of all crashes in the county. This classification is based on the determination made by the responding law enforcement officer at the scene of the collision.

Vulnerable Road User Casualties

Motorists comprised the entirety of the 12 fatalities and the vast majority of injuries, with 733 motorists injured. While no pedestrian or cyclist fatalities were recorded, 18 pedestrians were injured in crashes. There were no cyclist injuries reported in the data for this period.

0

Pedestrians Killed

12

Motorists Killed

18

Pedestrians Injured

733

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 frequency peaked on Fridays, with 425 incidents recorded. The single busiest hour for crashes was between 5:00 PM and 6:00 PM, which saw 201 crashes. The majority of collisions, 1,626 in total, occurred during daylight hours, compared to 733 crashes that happened in dark conditions, whether the roadway was lighted or not.

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

The vast majority of crashes, 78.6% (1,958 incidents), resulted in no injuries. Injury-related crashes, including serious, minor, and possible injuries, accounted for 21.0% of the total. There were 12 fatal crashes, which resulted in 12 total fatalities during this period.

Outcome by Severity (Crash Events)

Fatal12fatal crashes0.5%
Serious Injury40serious injury crashes1.6%
Minor Injury278minor injury crashes11.2%
Possible Injury204possible injury crashes8.2%
No Injury1,958no injury crashes78.6%

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 majority of crashes occurred in favorable conditions, with 65.2% (1,626 crashes) happening in daylight, 75.4% (1,879 crashes) on dry road surfaces, and 58.3% (1,454 crashes) in clear weather. Adverse conditions included 303 crashes during rain, 506 on wet roads, and 733 in dark conditions.

Weather

Clear1,454 (58.3%)
Cloudy629 (25.2%)
Rain303 (12.2%)
Snow57 (2.3%)
Freezing Rain or Freezing Drizzle16 (0.6%)
Sleet; Hail13 (0.5%)
Other/Unknown11 (0.4%)
Fog; Smog; Smoke8 (0.3%)
Blowing Sand; Soil; Dirt; Snow1 (0.0%)

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

Lighting

Daylight1,626 (65.2%)
Dark - Roadway Not Lighted451 (18.1%)
Dark - Lighted Roadway282 (11.3%)
Dawn/Dusk111 (4.5%)
Other/Unknown13 (0.5%)
Dark - Unknown Roadway Lighting9 (0.4%)

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

Road Surface

Dry1,879 (75.4%)
Wet506 (20.3%)
Snow49 (2.0%)
Ice43 (1.7%)
Other/Unknown6 (0.2%)
Slush5 (0.2%)
Sand; Mud; Dirt; Oil; Gravel4 (0.2%)

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

Vehicles & Demographics

Among the 5,650 individuals involved in crashes, the 26-34 age group was the most represented with 906 people, followed by the 35-44 age group with 778 people. Of the 4,237 vehicles involved, the most frequent makes were Chevrolet (730), Ford (629), and Honda (396).

Top Vehicle Makes (4,237 vehicles)

1
CHEVROLET730 (17.2%)
2
FORD629 (14.8%)
3
HONDA396 (9.3%)
4
TOYOTA312 (7.4%)
5
DODGE273 (6.4%)
6
JEEP198 (4.7%)
7
NISSAN187 (4.4%)
8
GMC156 (3.7%)
9
HYUNDAI123 (2.9%)
10
KIA117 (2.8%)

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

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

Sex Distribution (5,482 persons with recorded sex)

Male3,007 (54.9%)
Female2,475 (45.1%)

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 majority of crashes, 1,936 incidents, had their first harmful event occur on the roadway. However, a significant number of crashes were run-off-road events, with 410 occurring on the roadside, 64 on the shoulder, and 20 in the median, collectively accounting for 494 crashes off the primary travel lanes.

Crash Location (First Harmful Event)

"Other" combines 3 smaller categories (5 records): On ramp (2), On Gore (2), Off ramp (1).

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

Traffic Control Device

Analysis of the 4,237 vehicles involved in crashes shows that most were at locations with no traffic control device present, accounting for 3,033 vehicles. In contrast, 840 vehicles were involved in crashes at locations with a traffic signal, and 322 were at locations with 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

Among contributing factors assigned to vehicles, 'Following too Close / ACDA' was the most common, cited for 526 vehicles. This was followed by 'Failure to Yield' for 315 vehicles and 'Drove off Road' for 301 vehicles.

Driver Contributing Factor

1
Following too Close / ACDA526 (23.5%)
2
Failure to Yield315 (14%)
3
Drove off Road301 (13.4%)
4
Other Improper Action273 (12.2%)
5
Unsafe Speed203 (9.1%)
6
Improper Lane Change141 (6.3%)
7
Left of Center96 (4.3%)
8
Improper Backing78 (3.5%)
9
Ran Red Light57 (2.5%)

Showing top 9 of 21 reported. 12 additional (252 total) not shown: Not Discernible, Improper Turn, Swerving to Avoid, Ran Stop Sign, Improper Passing, Operating Defective Equipment, Load shifting/Falling/Spilling, Improper Start From a Parked Position, Improper Crossing, Vision Obstruction, Stopped or Parked Illegally, Wrong Way.

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

Commercial / Truck Involvement

A total of 240 commercial trucks were involved in crashes during this period. Of these, 181 were classified as semi-tractor-trailers, and 59 were identified as other types of commercial vehicles.

Vulnerable Road Users & Motorcycles

There were 68 crashes involving motorcyclists or vulnerable road users. These included 46 crashes with motorcyclists, 17 with pedestrians, and 5 with bicyclists. Combined, crashes involving pedestrians and bicyclists totaled 22 incidents.

Animal-Involved Crashes

A total of 221 crashes involved collisions with animals. The vast majority of these, 210 incidents, were strikes involving deer, while 11 involved other types of animals. Animal-related collisions accounted for 8.8% of all crashes.

Impairment (Alcohol / Drugs)

Impairment was a factor in 145 crashes, representing 5.8% of the total. Among these, alcohol was suspected in 87 incidents, drugs in 31, and a combination of alcohol and drugs in 27.

Driver Condition

Out of 4,013 drivers with a reported condition, 177 were noted as having a condition other than 'Apparently Normal.' This included 104 drivers suspected of being under the influence of medications, drugs, or alcohol, 33 with a physical impairment, and 24 who fell asleep, fainted, or were fatigued.

Driver Condition

1
Apparently Normal3,584 (90%)
2
Other/Unknown220 (5.5%)
3
Under the Influence of Medications / Drugs / Alcohol104 (2.6%)
4
Physical Impairment33 (0.8%)
5
Fell Asleep; Fainted; Fatigued; etc.24 (0.6%)
6
Emotional (E.G.; Depressed; Angry; Disturbed)12 (0.3%)
7
Illness4 (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

Among 4,013 drivers, a specific distraction was identified for 149 of them. The most cited distractions were 'Other distraction inside the vehicle' (60 drivers), 'Other distraction outside the vehicle' (36 drivers), and 'Manually operating an electronic communication device' (29 drivers).

Driver Distraction

1
Not Distracted3,574 (90%)
2
Other/Unknown246 (6.2%)
3
Other distraction inside the vehicle60 (1.5%)
4
Other distraction outside the vehicle36 (0.9%)
5
Manually operating an electronic communication device (texting; typing; dialing)29 (0.7%)
6
Other activity with an electronic device12 (0.3%)
7
Passenger5 (0.1%)
8
Talking on hand-held communication device5 (0.1%)
9
Talking on hands-free communication device2 (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 notable portion of crashes. Collisions on curves occurred in 418 incidents (16.8% of total), while crashes on a grade (uphill or downhill) occurred in 715 incidents (28.7% of total).

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 heavily concentrated in Zanesville, which accounted for 1,127 incidents, or 45.2% of the county's total. The next most frequent locations were Falls township with 247 crashes and Washington township with 145 crashes.

Top Cities

1
Zanesville1,127 (45.2%)
2
Falls247 (9.9%)
3
Washington145 (5.8%)
4
Perry127 (5.1%)
5
Newton111 (4.5%)
6
Hopewell95 (3.8%)
7
Springfield87 (3.5%)
8
Wayne73 (2.9%)
9
Union72 (2.9%)

Showing top 9 of 32 reported. 23 additional (408 total) not shown: Muskingum, Cass, Licking, Jackson, South Zanesville, Duncan Falls, Highland, Brush Creek, Harrison, Salt Creek, Blue Rock, Salem, Monroe, Roseville, Madison, Adams, Clay, Meigs, Frazeysburg, New Concord, Jefferson, Philo, Rich Hill.

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

Pre-Crash Driver Action

An analysis of the actions of 4,237 vehicles prior to a crash shows that the most common maneuver was 'Straight Ahead,' reported for 2,204 vehicles. The second most common pre-crash action was 'Slowing or Stopped In Traffic,' involving 666 vehicles.

Pre-Crash Driver Action

1
Straight Ahead2,204 (52%)
2
Slowing or Stopped In Traffic666 (15.7%)
3
Making Left Turn354 (8.4%)
4
Negotiating a Curve292 (6.9%)
5
Parked200 (4.7%)
6
Changing Lanes126 (3%)
7
Making Right Turn120 (2.8%)
8
Backing100 (2.4%)
9
Entering Traffic Lane44 (1%)

Showing top 9 of 17 reported. 8 additional (131 total) not shown: Other/Unknown, Overtaking/Passing, Leaving Traffic Lane, Walking; Running; Jogging; Playing, Driverless, Other Non-Motorist, Making U-Turn, Standing.

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

Manner of Collision

The most frequent type of collision was 'Not Collision Between Two Vehicles in Transport,' which includes single-vehicle crashes and represented 43.8% of all incidents (1,091 crashes). The second most common type was a rear-end collision, accounting for 539 crashes or 21.6% of the total.

Manner of Collision

"Other" combines 2 smaller categories (20 records): Other/Unknown (16), Rear-to-rear (4).

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 1,775 units, followed by 1,101 Sport Utility Vehicles. Commercial vehicles were also present, including 206 semi-tractors, 64 single-unit trucks, and 17 buses.

Vehicle Type

"Other" combines 12 smaller categories (181 records): Unknown or Hit/Skip (57), Motorcycle 2 Wheeled (46), Pedestrian/Skater (18), Bus (16+ Passengers) (17), Van (9-15 Seats) (14), Other Vehicle (11), Motorhome (5), Bicycle (5), All Terrain Vehicle (ATV/UTV) (4), Motorcycle 3 Wheeled (2), Heavy Equipment (1), Farm 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 5,650 people involved in crashes, the majority were drivers (4,013 people, or 71.0%). Passengers accounted for 1,618 individuals (28.6%), and pedestrians made up 19 of the total persons 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 all 5,650 individuals involved in crashes, 12 sustained fatal injuries (0.2%) and 751 sustained some level of non-fatal injury (13.3%). The majority of people, 4,847 individuals, 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

Among the 5,650 people involved in crashes, 4,490 were reported as using a shoulder and lap belt. A total of 312 individuals, or 5.5% of all participants, were recorded as using no safety equipment.

Occupant Safety Equipment

"Other" combines 2 smaller categories (35 records): Shoulder Belt Only Used (22), Lap Belt Only Used (13).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · 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: 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: 2,492
  • Total persons involved: 5,650
  • Total vehicles involved: 4,237

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