Yearly Traffic Safety Analysis

3,177 CRASHES IN
GREEN, OH
2024

All metrics benchmarked against2023

In 2024, the jurisdiction of Green experienced 3177 crashes, an increase from 3027 crashes in 2023, representing a 4.95% rise. Fatalities remained constant at 10 in both years, while total injuries increased by 3.2% from 937 to 967. A significant shift was observed in pedestrian crashes, which doubled from 8 in 2023 to 16 in 2024.

3,177

▲ 5.0%was 3,027

Total Crash Events

Persons Killed

967

▲ 3.2%was 937

Persons Injured

375

▲ 3.3%was 363

Hit-and-Run Crashes

Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (10) 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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Green showed an upward trend year-over-year, with total crashes increasing by 4.95% from 3027 in 2023 to 3177 in 2024. This increase was accompanied by a 3.2% rise in total injuries, from 937 to 967. Fatalities, however, remained stable at 10 in both periods.

375

Hit-and-Run Crashes — 2024

▲ 3.3% vs prior (363)

The number of hit-and-run crashes increased from 363 in 2023 to 375 in 2024. Despite this increase in raw numbers, the hit-and-run crash rate slightly decreased from 12% in 2023 to 11.8% in 2024. This indicates that while more hit-and-run incidents occurred, they represent a marginally smaller proportion of the overall increase in total crashes.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 1→0.0%

Motorists Killed

Prior: 9→0.0%

Pedestrians Injured

Prior: 9↑88.9%

950

Motorists Injured

Prior: 928↑2.4%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, increasing from 520 crashes in 2023 to 556 crashes in 2024. There was a shift in the peak hour, moving from 3 p.m. with 261 crashes in 2023 to 4 p.m. with 264 crashes in 2024. Crashes on Tuesday saw a notable increase from 453 to 502, while Saturday crashes slightly decreased from 389 to 383.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate slightly decreased from 0.33% in 2023 to 0.31% in 2024, although the number of fatal crashes remained constant at 10. Serious injury crashes decreased by 10, from 75 in 2023 to 65 in 2024, while minor injury crashes saw a slight increase from 341 to 343. The proportion of crashes resulting in no injury rose from 77.3% in 2023 to 78.4% in 2024.

Outcome by Severity (Crash Events)

Fatal10fatal crashes0.3%

→0.0%prior 10

Serious Injury65serious injury crashes2%

↓-13.3%prior 75

Minor Injury343minor injury crashes10.8%

↑0.6%prior 341

Possible Injury269possible injury crashes8.5%

↑3.5%prior 260

No Injury2,490no injury crashes78.4%

↑6.4%prior 2,341

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crashes occurring in clear weather increased from 1819 in 2023 to 1947 in 2024, while those in snowy conditions rose from 77 to 105. Under lighting conditions, crashes in daylight increased from 2009 to 2152, and those in dark-lighted roadways increased from 297 to 347. Crashes on dry road surfaces increased from 2298 to 2407, and crashes on icy surfaces more than doubled from 10 to 24.

Weather

Clear1,947 (61.3%)

↑7.0%prior 1,819

Cloudy694 (21.8%)

↑0.9%prior 688

Rain399 (12.6%)

↑1.8%prior 392

Snow105 (3.3%)

↑36.4%prior 77

Other/Unknown13 (0.4%)

↓-13.3%prior 15

Fog; Smog; Smoke11 (0.3%)

↓-54.2%prior 24

Sleet; Hail4 (0.1%)

↓-33.3%prior 6

Freezing Rain or Freezing Drizzle2 (0.1%)

Severe Crosswinds2 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight2,152 (67.7%)

↑7.1%prior 2,009

Dark - Roadway Not Lighted466 (14.7%)

↓-5.7%prior 494

Dark - Lighted Roadway347 (10.9%)

↑16.8%prior 297

Dawn/Dusk188 (5.9%)

→0.0%prior 188

Dark - Unknown Roadway Lighting18 (0.6%)

↓-28.0%prior 25

Other/Unknown6 (0.2%)

↓-57.1%prior 14

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry2,407 (75.8%)

↑4.7%prior 2,298

Wet659 (20.7%)

↑0.2%prior 658

Snow77 (2.4%)

↑42.6%prior 54

Ice24 (0.8%)

↑140.0%prior 10

Slush5 (0.2%)

Other/Unknown2 (0.1%)

Sand; Mud; Dirt; Oil; Gravel2 (0.1%)

Water (Standing; Moving)1 (0.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 5264 in 2023 to 5595 in 2024. Among age groups, persons aged 21-25 saw an increase of 65 individuals involved in crashes, and those aged 65+ increased by 85 individuals. While Ford remained the top make involved, its count decreased from 830 to 804, whereas Chevrolet increased from 713 to 762, and Honda from 524 to 612.

Top Vehicle Makes (5,595 vehicles)

FORD804 (14.4%)

↓-3.1%prior 830

CHEVROLET762 (13.6%)

↑6.9%prior 713

HONDA612 (10.9%)

↑16.8%prior 524

TOYOTA588 (10.5%)

↑15.5%prior 509

NISSAN273 (4.9%)

↓-5.2%prior 288

KIA266 (4.8%)

↑17.2%prior 227

DODGE257 (4.6%)

↓-5.5%prior 272

HYUNDAI228 (4.1%)

↓-13.3%prior 263

JEEP224 (4%)

↑13.7%prior 197

MAZDA118 (2.1%)

↑45.7%prior 81

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (6,904 persons with recorded sex)

Male3,712 (53.8%)

↑5.7%prior 3,513

Female3,192 (46.2%)

↑4.9%prior 3,044

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
Report generated: July 5, 2026

Data Coverage

Reporting period: 2024-01-01 through 2024-12-31 (366 days)
Geographic scope: Green, OH
Total crash records analyzed: 3,177
Total persons involved: 7,150
Total vehicles involved: 5,595

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). "Green, OH Crash Intelligence Report: 2024." Published July 5, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/green/2024-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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3,177 CRASHES INGREEN, OH2024