Yearly Traffic Safety Analysis

145 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Lyon County, the total number of crashes remained unchanged at 145 in 2025 compared to the same period in 2024. While fatalities also held steady at 2, total injuries decreased by 18.8% from 64 to 52. The most significant shift in crash causation was a 300% increase in the count of incidents attributed to 'Failure to yield right of way from a stop sign,' which rose from 3 to 12.

145

Total Crash Events

2

Persons Killed

52

▼ -18.8%was 64

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 traffic crash volume in Lyon County was stable year-over-year, with 145 incidents recorded in both 2025 and 2024. Despite the consistent number of total crashes, there was a positive trend in outcomes, as the number of people injured fell by 18.8% from 64 to 52. The number of fatalities was unchanged at 2 for both periods.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 2→0.0%

1

Cyclists Injured

Prior: 0→%

51

Motorists Injured

Prior: 64↓-20.3%

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 shifted year-over-year. The peak day for crashes moved from Friday, with 28 incidents in 2024, to Saturday, with 32 incidents in 2025, as Saturday crashes nearly doubled from the prior year's count of 17. Similarly, the peak hour for collisions shifted slightly earlier, from 4 p.m. (13 crashes) in the prior period to 3 p.m. (15 crashes) in the current period.

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

The number of fatal crashes remained constant at 2 in both 2025 and 2024. However, the distribution of injury severity changed, with serious injury crashes increasing from 5 to 8. This was offset by a notable decrease in less severe incidents, as minor injury crashes fell from 23 to 17 and possible injury crashes dropped from 21 to 14. Consequently, the count of crashes with no reported injuries rose from 94 to 104.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.4%
→0.0%prior 2
Serious Injury8serious injury crashes5.5%
↑60.0%prior 5
Minor Injury17minor injury crashes11.7%
↓-26.1%prior 23
Possible Injury14possible injury crashes9.7%
↓-33.3%prior 21
No Injury104no injury crashes71.7%
↑10.6%prior 94

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

Collisions with animals remained the leading contributing factor in both periods, accounting for 32 crashes each year. A significant change occurred in the ranking of other factors; incidents attributed to 'FTYROW: From stop sign' increased in count by 300%, rising from 3 to 12 crashes. Conversely, crashes attributed to 'Followed too close' decreased from 13 to 9, a 30.8% drop in count from the prior year.

Officer-Reported Primary Contributing Cause

Animal32 (22.1%)→0.0%prior 32
FTYROW: From stop sign12 (8.3%)
Lost Control11 (7.6%)↓-8.3%prior 12
Driving too fast for conditions9 (6.2%)→0.0%prior 9
Followed too close9 (6.2%)↓-30.8%prior 13
Ran off road - straight8 (5.5%)↑60.0%prior 5
Ran off road - left7 (4.8%)→0.0%prior 7
Ran Stop Sign7 (4.8%)→0.0%prior 7
Driver Distraction: Other interior distraction6 (4.1%)↓-25.0%prior 8
Made improper turn6 (4.1%)

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 broadly similar year-over-year, with most incidents in both periods occurring in clear weather (96 in 2025 vs. 94 in 2024) and on dry roads (83 vs. 87). The proportion of crashes happening in daylight increased, accounting for 81 incidents compared to 75 in the prior year. Crashes on wet road surfaces saw an increase from 6 to 10, while those occurring in cloudy weather decreased from 12 to 5.

Weather

Clear96 (78.0%)
↑2.1%prior 94
Severe Winds6 (4.9%)
Snow5 (4.1%)
↓-37.5%prior 8
Cloudy5 (4.1%)
↓-58.3%prior 12
Rain5 (4.1%)
Blowing Snow4 (3.3%)
Fog, smoke, smog2 (1.6%)

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

Lighting

Daylight81 (65.9%)
↑8.0%prior 75
Dark - roadway not lighted30 (24.4%)
↑11.1%prior 27
Dawn5 (4.1%)
Dark - roadway lighted4 (3.3%)
↓-33.3%prior 6
Dusk2 (1.6%)
↓-83.3%prior 12
Dark - unknown roadway lighting1 (0.8%)

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

Road Surface

Dry83 (67.5%)
↓-4.6%prior 87
Snow13 (10.6%)
↑8.3%prior 12
Wet10 (8.1%)
↑66.7%prior 6
Ice/frost8 (6.5%)
↓-11.1%prior 9
Gravel6 (4.9%)
↑20.0%prior 5
Slush2 (1.6%)
Mud, dirt1 (0.8%)

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 some shifts, with Chevrolet vehicles (combining 'CHEV' and 'CHEVROLET' codes) increasing from 48 to 61. The age demographics of persons involved in crashes changed significantly; there was a sharp decrease in individuals aged 16-20 (from 45 to 21) and a notable increase in those aged 65 and older (from 30 to 42).

Top Vehicle Makes (220 vehicles)

1
CHEV38 (17.3%)
↑52.0%prior 25
2
FORD38 (17.3%)
↑18.8%prior 32
3
CHEVROLET23 (10.5%)
→0.0%prior 23
4
GMC13 (5.9%)
↓-13.3%prior 15
5
BUIC7 (3.2%)
↓-12.5%prior 8
6
CHRY7 (3.2%)
↑16.7%prior 6
7
DODG6 (2.7%)
→0.0%prior 6
8
CHRYSLER5 (2.3%)
9
DODGE5 (2.3%)
→0.0%prior 5
10
JEEP4 (1.8%)
↓-50.0%prior 8

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

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

Sex Distribution (125 persons with recorded sex)

Male86 (68.8%)
↑4.9%prior 82
Female39 (31.2%)
→0.0%prior 39

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: 145
  • Total persons involved: 234
  • Total vehicles involved: 220

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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