Yearly Traffic Safety Analysis

2,415 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In Muskingum County, total traffic crashes increased slightly from 2,379 in 2024 to 2,415 in 2025, a change of approximately 1.5%. While the overall crash volume remained relatively stable, the number of fatalities rose by 26.7%, from 15 in the prior period to 19 in the current period. This increase in fatalities represents the most significant year-over-year shift in the data.

2,415

1.5%was 2,379

Total Crash Events

19

26.7%was 15

Persons Killed

741

3.6%was 715

Persons Injured

282

-7.2%was 304

Hit-and-Run Crashes

Note: "Persons Killed" (19) counts individual fatalities across all crash events. "Fatal" in the severity table below (19) 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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Muskingum County show a slight increase year-over-year. Total collisions rose by 1.5%, from 2,379 to 2,415. This was accompanied by a 3.6% increase in total injuries, from 715 to 741, and a more significant 26.7% rise in fatalities, which grew from 15 to 19.

282

Hit-and-Run Crashes — 2025

-7.2% vs prior (304)

Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. The number of hit-and-run crashes fell from 304 in 2024 to 282 in 2025. Consequently, the hit-and-run rate declined from 12.8% to 11.7% of all crashes during this period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 2-100.0%

19

Motorists Killed

Prior: 1346.2%

10

Pedestrians Injured

Prior: 16-37.5%

731

Motorists Injured

Prior: 6994.6%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained broadly consistent year-over-year, with Friday being the peak day for collisions in both periods, increasing from 392 to 420 crashes. However, the peak hour for crashes shifted slightly earlier, moving from 5 PM in the prior period (199 crashes) to 4 PM in the current period (215 crashes). The afternoon hours from 3 PM to 5 PM continued to account for the highest concentration of collisions in both years.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes worsened in the current period, with the fatal crash rate increasing from 0.59 to 0.79 per 100 crashes. Fatal crashes accounted for 0.8% of all incidents, up from 0.6% in the prior year. While the proportion of serious injury crashes decreased from 2.6% to 2.2%, the share of minor and possible injury crashes saw a slight increase.

Outcome by Severity (Crash Events)

Fatal19fatal crashes0.8%
35.7%prior 14
Serious Injury52serious injury crashes2.2%
-14.8%prior 61
Minor Injury313minor injury crashes13%
3.3%prior 303
Possible Injury143possible injury crashes5.9%
10.9%prior 129
No Injury1,888no injury crashes78.2%
0.9%prior 1,872

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather and on dry roads. However, there was a notable increase in crashes during adverse winter conditions in 2025. Crashes reported during snowy weather increased from 42 to 147, and collisions on snowy road surfaces rose from 29 to 126. The proportion of crashes occurring in daylight decreased slightly from 67.3% to 64.8%.

Weather

Clear1,410 (58.4%)
-4.1%prior 1,470
Cloudy571 (23.6%)
-9.9%prior 634
Rain244 (10.1%)
22.6%prior 199
Snow147 (6.1%)
250.0%prior 42
Fog; Smog; Smoke18 (0.7%)
63.6%prior 11
Other/Unknown17 (0.7%)
6.3%prior 16
Freezing Rain or Freezing Drizzle6 (0.2%)
Sleet; Hail2 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight1,564 (64.8%)
-2.3%prior 1,600
Dark - Roadway Not Lighted451 (18.7%)
9.5%prior 412
Dark - Lighted Roadway236 (9.8%)
5.8%prior 223
Dawn/Dusk136 (5.6%)
7.1%prior 127
Other/Unknown20 (0.8%)
66.7%prior 12
Dark - Unknown Roadway Lighting8 (0.3%)
60.0%prior 5

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry1,821 (75.4%)
-5.0%prior 1,916
Wet419 (17.3%)
4.5%prior 401
Snow126 (5.2%)
334.5%prior 29
Ice33 (1.4%)
175.0%prior 12
Other/Unknown12 (0.5%)
20.0%prior 10
Sand; Mud; Dirt; Oil; Gravel2 (0.1%)
Slush2 (0.1%)
-66.7%prior 6

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes shifted, with Ford taking the top spot from Chevrolet; Fords were involved in 659 crashes compared to 604 previously, while Chevrolets were involved in 607, down from 659. The age distribution of persons involved in crashes remained largely consistent, with the 16-20 age group being one of the largest in both years. Passenger Cars and Sport Utility Vehicles remained the two most common vehicle types involved in crashes in both periods.

Top Vehicle Makes (4,073 vehicles)

1
FORD659 (16.2%)
9.1%prior 604
2
CHEVROLET607 (14.9%)
-7.9%prior 659
3
HONDA480 (11.8%)
15.4%prior 416
4
TOYOTA284 (7%)
-3.4%prior 294
5
JEEP216 (5.3%)
1.9%prior 212
6
DODGE200 (4.9%)
-1.0%prior 202
7
NISSAN195 (4.8%)
-5.3%prior 206
8
GMC156 (3.8%)
5.4%prior 148
9
KIA121 (3%)
6.1%prior 114
10
HYUNDAI116 (2.8%)
8.4%prior 107

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (5,193 persons with recorded sex)

Male2,747 (52.9%)
-4.9%prior 2,889
Female2,446 (47.1%)
0.1%prior 2,444

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 2,415
  • Total persons involved: 5,385
  • Total vehicles involved: 4,073

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: 2025." Published July 5, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2025-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 — 2025 | ThatCarHitMe.com