Yearly Traffic Safety Analysis

62 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Pocahontas County, total crashes increased from 54 in 2024 to 62 in 2025, a 14.8% rise. While total injuries decreased slightly from 25 to 22, the most significant year-over-year change was the appearance of one fatal crash in 2025, whereas there were none in the prior year.

62

▲ 14.8%was 54

Total Crash Events

1

Persons Killed

22

▼ -12.0%was 25

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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

Crash trends in Pocahontas County showed an increase year-over-year, with total incidents rising to 62 in 2025 from 54 in 2024. This represents an increase of 8 crashes. Despite this rise, the total number of people injured fell from 25 to 22, though the county recorded one fatality in 2025 after having zero in the previous year.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0→%

22

Motorists Injured

Prior: 25↓-12.0%

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 between the two periods. In 2025, crashes peaked on Thursdays and Fridays, with 12 incidents each, and during the 1 p.m. hour, which saw 9 crashes. This contrasts with 2024, when Saturday was the peak day with 11 crashes and the 7 p.m. hour was the peak time with 7 crashes.

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

Crash severity worsened in 2025 compared to 2024. A fatal crash was recorded, accounting for 1.6% of all incidents, up from zero fatal crashes in the prior year. The number of serious injury crashes more than doubled, increasing from 2 to 5, and their share of total crashes grew from 3.7% to 8.1%. Conversely, minor injury crashes decreased in both count (from 13 to 10) and proportion (from 24.1% to 16.1%).

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.6%
Serious Injury5serious injury crashes8.1%
↑150.0%prior 2
Minor Injury10minor injury crashes16.1%
↓-23.1%prior 13
Possible Injury4possible injury crashes6.5%
↑33.3%prior 3
No Injury42no injury crashes67.7%
↑16.7%prior 36

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 involving an animal remained the top contributing factor in both years, though the count decreased from 13 in 2024 to 11 in 2025. The most notable shift was in crashes attributed to 'Driving too fast for conditions,' which nearly doubled in count from 5 in 2024 to 9 in 2025. Conversely, crashes involving 'Lost Control' and 'Ran off road - left' both saw a decrease in count from 6 incidents each in 2024 to 4 and 5 respectively in 2025.

Officer-Reported Primary Contributing Cause

Animal11 (17.7%)↓-15.4%prior 13
Driving too fast for conditions9 (14.5%)↑80.0%prior 5
Ran off road - left5 (8.1%)↓-16.7%prior 6
Driver Distraction: Other interior distraction5 (8.1%)
Lost Control4 (6.5%)↓-33.3%prior 6
FTYROW: From stop sign4 (6.5%)
Driver Distraction: Reaching for object(s)/fallen object(s)2 (3.2%)
Made improper turn2 (3.2%)
Operating vehicle in an reckless, erratic, careless, negligent manner2 (3.2%)
Ran off road - straight2 (3.2%)

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

Road & Environmental Conditions

The proportion of crashes occurring in daylight increased, accounting for 66.1% of incidents in 2025 compared to 48.1% in 2024. While the share of crashes on dry roads remained stable at around 46%, incidents on snow-covered roads were more frequent, with 11 crashes in 2025 versus 3 in 2024. Crashes in cloudy weather also saw a proportional increase, making up 22.6% of the total in 2025, up from 13.0% in 2024.

Weather

Clear29 (56.9%)
↑3.6%prior 28
Cloudy14 (27.5%)
↑100.0%prior 7
Blowing Snow6 (11.8%)
Freezing rain/drizzle1 (2.0%)
Severe Winds1 (2.0%)

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

Lighting

Daylight41 (77.4%)
↑57.7%prior 26
Dark - roadway not lighted7 (13.2%)
↓-30.0%prior 10
Dawn3 (5.7%)
Dark - roadway lighted2 (3.8%)

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

Road Surface

Dry29 (56.9%)
↑16.0%prior 25
Snow11 (21.6%)
Gravel5 (9.8%)
→0.0%prior 5
Wet3 (5.9%)
↓-40.0%prior 5
Ice/frost2 (3.9%)
Slush1 (2.0%)

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

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes in both years, with Ford's involvement increasing from 13 vehicles in 2024 to 21 in 2025. The demographics of persons involved in crashes shifted towards older age groups. The number of individuals aged 55-64 nearly doubled from 9 to 17, and the 65+ age group also doubled from 8 to 16 persons involved.

Top Vehicle Makes (88 vehicles)

1
FORD21 (23.9%)
↑61.5%prior 13
2
CHEV12 (13.6%)
→0.0%prior 12
3
DODG6 (6.8%)
4
GMC5 (5.7%)
5
JEEP5 (5.7%)
6
NR2 (2.3%)
7
PETERBILT2 (2.3%)
8
TOYO2 (2.3%)
9
HOND2 (2.3%)
10
HONDA2 (2.3%)

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

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

Sex Distribution (44 persons with recorded sex)

Male37 (84.1%)
↑42.3%prior 26
Female7 (15.9%)
↓-22.2%prior 9

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: 62
  • Total persons involved: 90
  • Total vehicles involved: 88

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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