Monthly Traffic Safety Analysis

352 CRASHES IN
OHIO, OH
NOVEMBER 2021

In November 2021, Allen County recorded 352 traffic crashes, resulting in 8 fatalities and 102 injuries. A significant portion of these incidents, 53.7%, were single-vehicle crashes not involving another vehicle in transport. Notably, animal strikes, primarily involving deer, accounted for 99 of the total crashes, representing 28.1% of all incidents.

352

Total Crash Events

8

Persons Killed

102

Persons Injured

12.2%

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 · 2021-11-01 to 2021-11-30 · Aggregate counts from crash, person, and vehicle records

43

Hit-and-Run Crashes — November 2021

According to initial officer reports, 43 crashes in November 2021 were classified as hit-and-run incidents, representing 12.2% of all crashes in Allen County during this period. This classification is based on the determination made by the responding officer at the scene.

Vulnerable Road User Casualties

During this period, 8 people were killed and 102 were injured in traffic crashes. Motorists comprised the largest group of casualties, with 6 fatalities and 100 injuries. Two pedestrians were also killed and two were injured. No cyclists were reported killed or injured in this dataset.

2

Pedestrians Killed

6

Motorists Killed

2

Pedestrians Injured

100

Motorists Injured

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash patterns in November showed a concentration on Mondays, which was the peak day with 66 incidents. The single hour with the most crashes was the 6 p.m. hour, recording 31 incidents. Analysis of lighting conditions reveals that more crashes occurred during hours of darkness (171 incidents) than in daylight (162 incidents).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 352 total crashes, 78.4% resulted in no injuries, being classified as property damage only. The remaining 21.7% of crashes involved some level of injury. There were 7 fatal crashes recorded, which resulted in a total of 8 fatalities, indicating at least one crash involved multiple deaths.

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

Outcome by Severity (Crash Events)

Fatal7fatal crashes2%
Serious Injury8serious injury crashes2.3%
Minor Injury28minor injury crashes8%
Possible Injury33possible injury crashes9.4%
No Injury276no injury crashes78.4%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Most severe injury per crash record

Road & Environmental Conditions

The majority of crashes occurred on dry roads (81.3%) and in clear weather (68.2%). However, lighting was a more varied factor, with 162 crashes (46%) happening in daylight, while 171 crashes (48.6%) occurred in dark conditions. Adverse weather was noted in a smaller number of incidents, including 19 crashes in rain and 14 in snow.

Weather

Clear240 (68.2%)
Cloudy76 (21.6%)
Rain19 (5.4%)
Snow14 (4.0%)
Freezing Rain or Freezing Drizzle2 (0.6%)
Blowing Sand; Soil; Dirt; Snow1 (0.3%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Weather condition at time of crash

Lighting

Daylight162 (46.0%)
Dark - Roadway Not Lighted118 (33.5%)
Dark - Lighted Roadway48 (13.6%)
Dawn/Dusk19 (5.4%)
Dark - Unknown Roadway Lighting5 (1.4%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Lighting condition field

Road Surface

Dry286 (81.3%)
Wet45 (12.8%)
Ice16 (4.5%)
Snow5 (1.4%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Road surface condition field

Vehicles & Demographics

Analysis of persons involved in crashes shows the 16-20 age group was the most represented, with 113 individuals, followed by the 26-34 age group with 108 individuals. Among the 556 vehicles involved, the most frequent makes were Ford, with 121 vehicles, Chevrolet with 105, and Dodge with 41.

Top Vehicle Makes (556 vehicles)

1
FORD121 (21.8%)
2
CHEVROLET105 (18.9%)
3
DODGE41 (7.4%)
4
HONDA32 (5.8%)
5
CHRYSLER27 (4.9%)
6
KIA26 (4.7%)
7
JEEP16 (2.9%)
8
GMC16 (2.9%)
9
TOYOTA16 (2.9%)
10
CADILLAC15 (2.7%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Vehicle unit records

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

Sex Distribution (691 persons with recorded sex)

Male370 (53.5%)
Female321 (46.5%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Person-level records linked to crash events

Crash Location (First Harmful Event)

The initial harmful event for the vast majority of crashes, 300 out of 352, occurred on the roadway. A total of 39 crashes, or 11.1% of the total, were classified as run-off-road incidents, with the first harmful event occurring on the roadside (27), shoulder (6), or in the median (6).

Crash Location (First Harmful Event)

"Other" combines 1 smaller categories (1 records): Driveway/Alley access (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Crash-level records

Traffic Control Device

Analysis of traffic controls present at crash locations shows that a majority of vehicles (381) were involved in crashes where no traffic control device was present. Crashes at signalized intersections involved 125 vehicles, while those at locations with stop signs involved 42 vehicles.

Traffic Control Device

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Vehicle unit records

Driver Contributing Factor

The most frequently cited contributing factors for drivers involved in crashes were 'Following too Close / ACDA,' attributed to 50 drivers, and 'Failure to Yield,' cited for 48 drivers. 'Drove off Road' was the third most common factor, noted for 32 drivers, followed by 'Unsafe Speed' for 14 drivers.

Driver Contributing Factor

1
Following too Close / ACDA50 (19.8%)
2
Failure to Yield48 (19%)
3
Drove off Road32 (12.7%)
4
Other Improper Action30 (11.9%)
5
Improper Backing15 (6%)
6
Unsafe Speed14 (5.6%)
7
Left of Center13 (5.2%)
8
Improper Lane Change13 (5.2%)
9
Improper Turn8 (3.2%)

Showing top 9 of 20 reported. 11 additional (29 total) not shown: Ran Red Light, Not Discernible, Swerving to Avoid, Ran Stop Sign, Operating Defective Equipment, Stopped or Parked Illegally, Wrong Way, Improper Passing, Load shifting/Falling/Spilling, Vision Obstruction, Improper Crossing.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Vehicle unit records

Commercial / Truck Involvement

Crashes involving commercial trucks were documented in at least 23 incidents. Of these, 18 involved a semi-tractor trailer, while 5 involved other types of commercial vehicles. These incidents represent approximately 6.5% of all crashes during the period.

Animal-Involved Crashes

Animal-related collisions were a significant factor, accounting for 100 crashes, or 28.4% of the total for the month. The vast majority of these incidents, 99 out of 100, involved collisions with deer, highlighting a notable seasonal hazard.

Impairment (Alcohol / Drugs)

Impairment was a noted factor in 18 crashes, representing 5.1% of all incidents. Among these, alcohol was suspected in 11 cases, drugs in 4 cases, and a combination of alcohol and drugs in 3 cases. These figures are based on officer suspicion at the scene and should be considered a minimum.

Driver Condition

Beyond those noted as 'Apparently Normal,' specific adverse driver conditions were recorded for 24 drivers. This included 15 drivers suspected of being under the influence of medications, drugs, or alcohol. Other noted conditions were fatigue or falling asleep (3 drivers), illness (2 drivers), and emotional distress (2 drivers).

Driver Condition

1
Apparently Normal465 (90.6%)
2
Other/Unknown24 (4.7%)
3
Under the Influence of Medications / Drugs / Alcohol15 (2.9%)
4
Fell Asleep; Fainted; Fatigued; etc.3 (0.6%)
5
Illness2 (0.4%)
6
Emotional (E.G.; Depressed; Angry; Disturbed)2 (0.4%)
7
Physical Impairment2 (0.4%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Person-level records linked to crash events

Driver Distraction

Driver distraction was identified as a factor for 25 drivers involved in crashes. The most common specific distraction was 'Other distraction inside the vehicle,' noted for 15 drivers. Electronic device use was explicitly cited for 5 drivers, including 3 who were manually operating a device and 1 talking on a hand-held device.

Driver Distraction

1
Not Distracted457 (88.9%)
2
Other/Unknown32 (6.2%)
3
Other distraction inside the vehicle15 (2.9%)
4
Manually operating an electronic communication device (texting; typing; dialing)3 (0.6%)
5
Other distraction outside the vehicle3 (0.6%)
6
Passenger2 (0.4%)
7
Other activity with an electronic device1 (0.2%)
8
Talking on hand-held communication device1 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Person-level records linked to crash events

Road Alignment

The majority of crashes (306) occurred on straight and level road segments. However, road geometry was a factor in some incidents, with 24 crashes (6.8%) occurring on curves and 30 crashes (8.5%) taking place on grades. Nine of these crashes occurred on segments that were both curved and graded.

Road Alignment

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Crash-level records

Top Cities

The geographic distribution of crashes was concentrated in a few key areas within the county. The city of Lima accounted for the largest share, with 88 crashes, representing 25% of the total. The townships of Bath and American followed, with 56 (15.9%) and 47 (13.4%) crashes, respectively.

Top Cities

1
Lima88 (25%)
2
Bath56 (15.9%)
3
American47 (13.4%)
4
Perry30 (8.5%)
5
Shawnee27 (7.7%)
6
Auglaize16 (4.5%)
7
Amanda13 (3.7%)
8
Marion13 (3.7%)
9
Jackson12 (3.4%)

Showing top 9 of 19 reported. 10 additional (50 total) not shown: Sugar Creek, Richland, Spencer, Monroe, Delphos, Bluffton, Elida, Harrod, Beaverdam, Spencerville.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Crash-level records

Pre-Crash Driver Action

Analysis of vehicle actions prior to collision shows that the majority of vehicles (351, or 63.1%) were proceeding straight ahead. The next most common pre-crash action was slowing or being stopped in traffic, which accounted for 64 vehicles (11.5%). Making a left turn was the third most frequent action, involving 35 vehicles.

Pre-Crash Driver Action

1
Straight Ahead351 (63.1%)
2
Slowing or Stopped In Traffic64 (11.5%)
3
Making Left Turn35 (6.3%)
4
Parked29 (5.2%)
5
Backing17 (3.1%)
6
Changing Lanes13 (2.3%)
7
Negotiating a Curve12 (2.2%)
8
Making Right Turn12 (2.2%)
9
Other/Unknown8 (1.4%)

Showing top 9 of 16 reported. 7 additional (15 total) not shown: Entering Traffic Lane, Walking; Running; Jogging; Playing, Leaving Traffic Lane, Overtaking/Passing, Making U-Turn, Entering or Crossing Specified Location, Driverless.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Vehicle unit records

Manner of Collision

The most common type of crash was a single-vehicle incident, categorized as 'Not Collision Between Two Vehicles in Transport,' which accounted for 189 crashes or 53.7% of the total. Among multi-vehicle crashes, angle collisions were the most frequent type with 64 incidents (18.2%), followed by rear-end collisions with 50 incidents (14.2%).

Manner of Collision

"Other" combines 1 smaller categories (4 records): Backing (4).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 257 of the 556 vehicles (46.2%). Sport Utility Vehicles (130) and Pick-up trucks (91) were the next most frequent types. Commercial vehicles, including semi-tractors and other trucks, were involved in 29 incidents.

Vehicle Type

"Other" combines 6 smaller categories (15 records): Pedestrian/Skater (4), Single Unit Truck (4), Van (9-15 Seats) (3), Heavy Equipment (2), Motorcycle 2 Wheeled (1), Bicycle (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Vehicle unit records

Person Type

A total of 717 people were involved in crashes during this period. Drivers were the largest group, accounting for 523 individuals (73%). Vehicle occupants or passengers comprised the next largest group with 190 individuals (26.5%), while 4 pedestrians (0.6%) were also involved.

Person Type

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Crash-level records

Person Injury Severity

Of the 717 individuals involved in crashes, 8 sustained fatal injuries (1.1%) and 102 sustained non-fatal injuries (14.2%). The majority of people involved, 598 individuals or 83.4%, were not injured. The non-fatal injuries included 10 serious injuries, 40 minor injuries, and 52 possible injuries.

Person Injury Severity

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Crash-level records

Occupant Safety Equipment

Safety equipment usage was reported for most vehicle occupants, with 618 individuals (86.2%) recorded as using both a shoulder and lap belt. However, 28 individuals were reported as using no safety equipment at the time of their crash. An additional 13 occupants were secured using various child restraint systems.

Occupant Safety Equipment

"Other" combines 2 smaller categories (2 records): Booster Seat (1), Helmet Used (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · Person-level records linked to crash events

Vehicles Per Crash

The crashes were almost evenly split between two-vehicle incidents (171 crashes, or 48.6%) and single-vehicle incidents (165 crashes, or 46.9%). A smaller number of crashes were multi-vehicle pile-ups, with 15 crashes involving three vehicles and one crash involving four vehicles.

Vehicles Per Crash

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-11-01 to 2021-11-30 · 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: 2021-11-01 through 2021-11-30
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2021-11-01 through 2021-11-30 (30 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 352
  • Total persons involved: 717
  • Total vehicles involved: 556

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: November 2021." Published July 6, 2026. Reporting period: 2021-11-01 to 2021-11-30. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/november-2021-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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Allen County, OH Crash Report — November 2021 | ThatCarHitMe.com