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Yearly Traffic Safety Analysis

36 CRASHES IN
ADA, OH
2022

All metrics benchmarked against2021

In 2022, Ada recorded 36 total traffic crashes, a 5.9% increase from the 34 crashes reported in 2021. Despite the rise in total incidents, the number of people injured decreased by 63.6%, from 11 in 2021 to 4 in 2022. The most significant year-over-year change was this sharp decline in injuries, even as the overall crash count slightly increased.

▲ 5.9%was 34

Total Crash Events

Persons Killed

▼ -63.6%was 11

Persons Injured

▲ 66.7%was 3

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic crashes in Ada showed a slight upward trend, increasing from 34 incidents in 2021 to 36 in 2022. This represents a 5.9% year-over-year increase in crash volume. However, the severity of these crashes decreased, with total injuries falling from 11 to 4, while fatalities remained at zero for both periods.

Hit-and-Run Crashes — 2022

▲ 66.7% vs prior (3)

The incidence of hit-and-run crashes increased from 2021 to 2022. The total number of hit-and-run incidents rose from 3 to 5. As a proportion of all crashes, the hit-and-run rate increased from 8.8% in 2021 to 13.9% in 2022, indicating an upward trend for this crash type.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 0→0.0%

Motorists Killed

Prior: 0→0.0%

Pedestrians Injured

Prior: 0→%

Motorists Injured

Prior: 11↓-72.7%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two years. In 2022, the peak day for crashes was Friday with 10 incidents, a change from 2021 when Wednesday was the peak day with 12 crashes. The peak hour for collisions remained consistent, occurring at 3 p.m. in both 2022 and 2021, with 5 and 4 crashes respectively.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity decreased from 2021 to 2022, with no fatal crashes reported in either year. The proportion of crashes resulting in an injury dropped significantly; injury-related crashes accounted for 26.5% of all incidents in 2021 compared to just 11.1% in 2022. Correspondingly, the share of non-injury crashes rose from 73.5% in 2021 to 88.9% in 2022.

Outcome by Severity (Crash Events)

Possible Injury4possible injury crashes11.1%

↓-42.9%prior 7

No Injury32no injury crashes88.9%

↑28.0%prior 25

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of crashes across different environmental conditions remained largely stable year-over-year. In both 2022 and 2021, the majority of crashes occurred during daylight hours (66.7% and 64.7%, respectively) and on dry road surfaces (77.8% and 76.5%). Clear weather was the predominant condition in both periods, accounting for 58.3% of crashes in 2022 and 61.8% in 2021, showing no significant shift in the role of adverse conditions.

Weather

Clear21 (58.3%)

→0.0%prior 21

Cloudy9 (25.0%)

↑50.0%prior 6

Snow3 (8.3%)

Rain2 (5.6%)

↓-60.0%prior 5

Other/Unknown1 (2.8%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight24 (66.7%)

↑9.1%prior 22

Dark - Lighted Roadway8 (22.2%)

→0.0%prior 8

Dark - Roadway Not Lighted4 (11.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry28 (77.8%)

↑7.7%prior 26

Wet4 (11.1%)

↓-33.3%prior 6

Ice2 (5.6%)

Snow2 (5.6%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent, with Ford, Chevrolet, and Honda being the most frequent in both 2022 and 2021. Regarding the age of persons involved, the 21-25 age group was prominent in both years, with 18 individuals in 2021 and 14 in 2022. Notably, the number of persons in the 16-20 age group involved in crashes increased from 8 in 2021 to 14 in 2022, making it an equally prominent group.

Top Vehicle Makes (69 vehicles)

FORD9 (13%)

↓-30.8%prior 13

CHEVROLET8 (11.6%)

↓-20.0%prior 10

HONDA7 (10.1%)

→0.0%prior 7

NISSAN5 (7.2%)

BUICK4 (5.8%)

PONTIAC3 (4.3%)

DODGE3 (4.3%)

↓-40.0%prior 5

CADILLAC3 (4.3%)

VOLKSWAGEN2 (2.9%)

HARLEY DAVIDSON2 (2.9%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (58 persons with recorded sex)

Female30 (51.7%)

↑15.4%prior 26

Male28 (48.3%)

↓-34.9%prior 43

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
Report generated: August 22, 2026

Data Coverage

Reporting period: 2022-01-01 through 2022-12-31 (365 days)
Geographic scope: Ada, OH
Total crash records analyzed: 36
Total persons involved: 62
Total vehicles involved: 69

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). "Ada, OH Crash Intelligence Report: 2022." Published August 22, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/ada/2022-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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