Yearly Traffic Safety Analysis

255 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Fayette County, total traffic crashes decreased by 6.9% from 274 in 2024 to 255 in 2025. Despite the overall reduction in collisions, the number of fatalities increased from 3 to 5, and the number of fatal crashes rose from 3 to 5 during the same period. This increase in crash severity represents the most significant year-over-year shift in the data.

255

▼ -6.9%was 274

Total Crash Events

5

▲ 66.7%was 3

Persons Killed

71

▲ 4.4%was 68

Persons Injured

5

▲ 66.7%was 3

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes in Fayette County showed a downward trend, decreasing by 19 incidents from 274 to 255 year-over-year. However, this trend did not extend to crash outcomes, as total injuries saw a slight increase from 68 to 71, and total fatalities rose from 3 to 5.

Vulnerable Road User Casualties

1

Cyclists Killed

Prior: 0→%

4

Motorists Killed

Prior: 3↑33.3%

0

Cyclists Injured

Prior: 1↓-100.0%

71

Motorists Injured

Prior: 66↑7.6%

Source: Iowa Crash Data · ArcGIS 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 timing of crashes showed some shifts between the two periods. While Friday remained the peak day for crashes in both years, the peak hour moved one hour earlier to 5 p.m. in 2025, with 25 crashes, from 6 p.m. in 2024, which had 21 crashes. Notably, the number of crashes occurring on Sunday increased from 24 in the prior year to 40 in the current year.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes declined, the severity of crashes increased year-over-year. The number of fatal crashes rose from 3 to 5, and the fatal crash rate increased from 1.09% to 1.96%. Similarly, serious injury crashes increased from 8 to 12. This resulted in a higher proportion of severe outcomes, even as the number of minor injury crashes fell from 28 to 21.

Outcome by Severity (Crash Events)

Fatal5fatal crashes2%
↑66.7%prior 3
Serious Injury12serious injury crashes4.7%
↑50.0%prior 8
Minor Injury21minor injury crashes8.2%
↓-25.0%prior 28
Possible Injury25possible injury crashes9.8%
↑25.0%prior 20
No Injury192no injury crashes75.3%
↓-10.7%prior 215

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors remained consistent, though their counts shifted. Collisions involving an 'Animal' continued to be the top factor but decreased in count from 104 to 82. 'Ran off road - left' also saw a decrease from 21 to 15 incidents. 'FTYROW: From stop sign' held steady with 13 crashes in both periods, while 'Operating vehicle in a reckless, erratic, careless, negligent manner' saw an increase in count from 7 to 11 incidents.

Officer-Reported Primary Contributing Cause

Animal82 (32.2%)↓-21.2%prior 104
Ran off road - left15 (5.9%)↓-28.6%prior 21
FTYROW: From stop sign13 (5.1%)→0.0%prior 13
Lost Control12 (4.7%)↓-25.0%prior 16
Ran off road - straight11 (4.3%)↑10.0%prior 10
Operating vehicle in an reckless, erratic, careless, negligent manner11 (4.3%)↑57.1%prior 7
Driver Distraction: Other interior distraction10 (3.9%)↓-23.1%prior 13
Followed too close9 (3.5%)
Ran Stop Sign8 (3.1%)→0.0%prior 8
Driving too fast for conditions7 (2.7%)↓-12.5%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained remarkably stable year-over-year, with no significant shifts in patterns. In both periods, the majority of crashes occurred in 'Clear' weather (129 in 2025 vs. 133 in 2024) and on 'Dry' road surfaces (130 vs. 135). The proportion of crashes happening in 'Daylight' was also consistent, accounting for 122 of 255 crashes in the current period and 119 of 274 in the prior period.

Weather

Clear129 (72.5%)
↓-3.0%prior 133
Cloudy28 (15.7%)
↑3.7%prior 27
Snow6 (3.4%)
↑20.0%prior 5
Rain5 (2.8%)
Fog, smoke, smog4 (2.2%)
↓-50.0%prior 8
Severe Winds3 (1.7%)
Sleet, hail1 (0.6%)
Freezing rain/drizzle1 (0.6%)
Blowing Snow1 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight122 (67.0%)
↑2.5%prior 119
Dark - roadway not lighted33 (18.1%)
↓-15.4%prior 39
Dark - roadway lighted10 (5.5%)
↓-28.6%prior 14
Dusk9 (4.9%)
↑80.0%prior 5
Dawn4 (2.2%)
↓-20.0%prior 5
Dark - unknown roadway lighting4 (2.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry130 (72.6%)
↓-3.7%prior 135
Wet16 (8.9%)
↓-11.1%prior 18
Gravel14 (7.8%)
↑55.6%prior 9
Snow12 (6.7%)
→0.0%prior 12
Ice/frost3 (1.7%)
↓-70.0%prior 10
Other (explain in narrative)2 (1.1%)
Slush2 (1.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes saw a shift in ranking at the top. Chevrolet became the most frequent make with 72 crashes, overtaking Ford, which decreased from 87 crashes in the prior year to 62 in the current year. Regarding persons involved, the share of individuals in the 16-20 age group increased from 12.7% to 14.0% of the total, and the 65+ age group's share grew from 15.8% to 17.2%.

Top Vehicle Makes (363 vehicles)

1
CHEV72 (19.8%)
↑9.1%prior 66
2
FORD62 (17.1%)
↓-28.7%prior 87
3
DODG23 (6.3%)
↑43.8%prior 16
4
BUIC22 (6.1%)
↑120.0%prior 10
5
GMC18 (5%)
↑12.5%prior 16
6
JEEP17 (4.7%)
↓-22.7%prior 22
7
CHEVROLET12 (3.3%)
↓-40.0%prior 20
8
TOYT11 (3%)
↑37.5%prior 8
9
CHRY10 (2.8%)
↑25.0%prior 8
10
NISS10 (2.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (185 persons with recorded sex)

Male107 (57.8%)
↓-11.6%prior 121
Female78 (42.2%)
↑13.0%prior 69

Source: Iowa Crash Data · ArcGIS 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 Iowa Crash Data, accessed programmatically via the ArcGIS 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: ArcGIS 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: September 9, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 255
  • Total persons involved: 372
  • Total vehicles involved: 363

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). "iowa, IA Crash Intelligence Report: 2025." Published September 9, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/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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