Yearly Traffic Safety Analysis

444 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Sioux County, total vehicle crashes decreased by 11%, from 499 in 2024 to 444 in 2025. This overall reduction was accompanied by a 23.2% decrease in total injuries, from 237 to 182. However, a notable counter-trend was the 38.5% increase in crashes involving a driver under the influence, which rose from 13 to 18 incidents year-over-year.

444

▼ -11.0%was 499

Total Crash Events

3

Persons Killed

182

▼ -23.2%was 237

Persons Injured

3

▲ 50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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

The overall trend in traffic collisions shows a notable improvement, with total crashes falling by 11% from 499 in the prior year to 444 in the current year. The number of people injured in these incidents also saw a significant decline of 23.2%, dropping from 237 to 182. The number of fatalities, however, remained unchanged at 3 for both periods.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 3→0.0%

3

Pedestrians Injured

Prior: 2↑50.0%

2

Cyclists Injured

Prior: 1↑100.0%

177

Motorists Injured

Prior: 233↓-24.0%

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, the peak day for crashes was Friday with 81 incidents, a change from Monday (95 incidents) in 2024. The most frequent crash hour also moved earlier in the day, from 5 p.m. in the prior period (39 crashes) to 3 p.m. in the current period (43 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

While total crashes decreased, the severity of crashes that did occur worsened. The number of fatal crashes increased from 2 to 3, and serious injury crashes rose from 13 to 16. Consequently, the share of fatal crashes grew from 0.4% to 0.7% of all incidents, and serious injury crashes increased from 2.6% to 3.6%. This occurred as the proportion of crashes resulting in only 'possible' injuries fell sharply from 15.2% to 9.9%.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.7%
↑50.0%prior 2
Serious Injury16serious injury crashes3.6%
↑23.1%prior 13
Minor Injury68minor injury crashes15.3%
↓-6.8%prior 73
Possible Injury44possible injury crashes9.9%
↓-42.1%prior 76
No Injury313no injury crashes70.5%
↓-6.6%prior 335

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 for crashes shifted year-over-year. Collisions involving an animal became the most frequent cause in 2025 with 60 incidents, despite a slight decrease from 63 incidents in the prior year. 'Followed too close' dropped from the top position after its count fell by 34.3%, from 70 to 46 crashes. Meanwhile, crashes attributed to 'driving too fast for conditions' increased by 18.9%, from 37 to 44 incidents.

Officer-Reported Primary Contributing Cause

Animal60 (13.5%)↓-4.8%prior 63
Followed too close46 (10.4%)↓-34.3%prior 70
Driving too fast for conditions44 (9.9%)↑18.9%prior 37
FTYROW: From stop sign40 (9%)↑21.2%prior 33
Ran off road - left27 (6.1%)↓-15.6%prior 32
FTYROW: Making left turn22 (5%)↑46.7%prior 15
Lost Control20 (4.5%)↓-28.6%prior 28
Other (explain in narrative): Other15 (3.4%)→0.0%prior 15
Ran Stop Sign14 (3.2%)↓-30.0%prior 20
Driver Distraction: Other interior distraction13 (2.9%)

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 consistent between the two years, with most incidents in both periods occurring in daylight on dry roads. There was a notable decrease in crashes occurring in dark, unlit conditions, which fell from 72 incidents in 2024 to 51 in 2025. Conversely, crashes on wet road surfaces increased in both count (from 35 to 41) and as a proportion of all crashes (from 7.0% to 9.2%).

Weather

Clear249 (62.4%)
↓-16.4%prior 298
Cloudy86 (21.6%)
↓-3.4%prior 89
Rain21 (5.3%)
↑50.0%prior 14
Snow17 (4.3%)
↓-5.6%prior 18
Blowing Snow8 (2.0%)
Severe Winds8 (2.0%)
Freezing rain/drizzle5 (1.3%)
↓-16.7%prior 6
Fog, smoke, smog3 (0.8%)
↓-72.7%prior 11
Other (explain in narrative)2 (0.5%)

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

Lighting

Daylight292 (72.6%)
↓-7.6%prior 316
Dark - roadway not lighted51 (12.7%)
↓-29.2%prior 72
Dark - roadway lighted33 (8.2%)
↓-5.7%prior 35
Dusk13 (3.2%)
↑8.3%prior 12
Dawn12 (3.0%)
↑9.1%prior 11
Dark - unknown roadway lighting1 (0.2%)

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

Road Surface

Dry269 (67.3%)
↓-13.8%prior 312
Wet41 (10.3%)
↑17.1%prior 35
Snow35 (8.8%)
↓-12.5%prior 40
Ice/frost30 (7.5%)
↓-18.9%prior 37
Gravel18 (4.5%)
↑5.9%prior 17
Slush6 (1.5%)
Mud, dirt1 (0.3%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes, Ford and Chevrolet, maintained their rankings in 2025, though both saw a reduction in total incidents consistent with the overall trend. An analysis of persons involved shows the 16-20 age group's involvement decreased, falling from 162 individuals in 2024 to 124 in 2025. The share of individuals aged 65 and older remained relatively stable, accounting for 13.5% of persons involved in 2025 compared to 13.2% in the prior year.

Top Vehicle Makes (736 vehicles)

1
FORD145 (19.7%)
↓-14.7%prior 170
2
CHEV134 (18.2%)
↓-1.5%prior 136
3
CHEVROLET46 (6.3%)
↓-20.7%prior 58
4
GMC39 (5.3%)
↑5.4%prior 37
5
DODG30 (4.1%)
↑25.0%prior 24
6
JEEP26 (3.5%)
↓-35.0%prior 40
7
RAM25 (3.4%)
↑38.9%prior 18
8
BUIC22 (3%)
↓-29.0%prior 31
9
HOND20 (2.7%)
↓-25.9%prior 27
10
KIA18 (2.4%)
→0.0%prior 18

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

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

Sex Distribution (487 persons with recorded sex)

Male305 (62.6%)
↓-7.3%prior 329
Female182 (37.4%)
↓-18.4%prior 223

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: 444
  • Total persons involved: 775
  • Total vehicles involved: 736

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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