Yearly Traffic Safety Analysis

221 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Cass County recorded 221 total crashes, a 12.2% increase from the 197 crashes reported in 2024. The most significant year-over-year change was the number of fatalities, which rose from 1 in 2024 to 4 in 2025.

221

▲ 12.2%was 197

Total Crash Events

4

▲ 300.0%was 1

Persons Killed

65

▲ 14.0%was 57

Persons Injured

4

▲ 300.0%was 1

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 Cass County showed an increase year-over-year. Total crashes rose by 12.2%, from 197 in 2024 to 221 in 2025. Similarly, total injuries increased by 14.0% from 57 to 65, and fatalities increased from 1 to 4.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

3

Motorists Killed

Prior: 1↑200.0%

1

Pedestrians Injured

Prior: 1→0.0%

64

Motorists Injured

Prior: 55↑16.4%

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 temporal patterns of crashes showed some shifts between the two periods. While Monday remained the peak day for crashes in both 2025 (36 crashes) and 2024 (35 crashes), the peak hour changed significantly. In 2025, the most crashes occurred at 9 p.m. (15 incidents), a shift from 2024's peak at 3 p.m. (15 incidents).

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 severity of crashes worsened in 2025 compared to the prior year. Fatal crashes increased from 1 to 4, raising the fatal crash rate from 0.5% to 1.8% of all collisions. While the number of serious injury crashes (6) and minor injury crashes (21) remained unchanged, crashes resulting in possible injuries increased from 22 to 28. Consequently, the proportion of no-injury crashes decreased slightly from 74.6% of all crashes in 2024 to 73.3% in 2025.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.8%
↑300.0%prior 1
Serious Injury6serious injury crashes2.7%
→0.0%prior 6
Minor Injury21minor injury crashes9.5%
→0.0%prior 21
Possible Injury28possible injury crashes12.7%
↑27.3%prior 22
No Injury162no injury crashes73.3%
↑10.2%prior 147

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 showed some shifts in prevalence year-over-year. Collisions involving an 'Animal' remained the top factor in both periods, with counts of 36 in 2025 and 35 in 2024. The count of crashes attributed to 'Lost Control' increased from 16 to 27, making it the second most common factor in 2025. Conversely, incidents involving 'Driving too fast for conditions' saw a notable decrease in count, from 13 in 2024 to 5 in 2025.

Officer-Reported Primary Contributing Cause

Animal36 (16.3%)↑2.9%prior 35
Lost Control27 (12.2%)↑68.8%prior 16
Ran off road - straight20 (9%)↑11.1%prior 18
FTYROW: From stop sign19 (8.6%)↑35.7%prior 14
Other (explain in narrative): Other16 (7.2%)↑128.6%prior 7
Driver Distraction: Other interior distraction15 (6.8%)↑36.4%prior 11
Followed too close11 (5%)→0.0%prior 11
Ran off road - left8 (3.6%)↓-57.9%prior 19
Ran Stop Sign7 (3.2%)
Operating vehicle in an reckless, erratic, careless, negligent manner6 (2.7%)

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 2024 and 2025. In both periods, the majority of crashes occurred in clear weather (139 in 2025 vs. 127 in 2024), during daylight hours (116 vs. 113), and on dry road surfaces (146 vs. 140). The number of crashes in adverse conditions like rain and on wet surfaces saw slight increases, but their proportion relative to total crashes did not change significantly.

Weather

Clear139 (73.5%)
↑9.4%prior 127
Cloudy22 (11.6%)
→0.0%prior 22
Rain11 (5.8%)
↑83.3%prior 6
Snow7 (3.7%)
↑40.0%prior 5
Blowing Snow6 (3.2%)
→0.0%prior 6
Severe Winds2 (1.1%)
Freezing rain/drizzle1 (0.5%)
Blowing sand, soil, dirt1 (0.5%)

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

Lighting

Daylight116 (61.1%)
↑2.7%prior 113
Dark - roadway not lighted45 (23.7%)
↑18.4%prior 38
Dark - roadway lighted14 (7.4%)
↑27.3%prior 11
Dusk8 (4.2%)
↑33.3%prior 6
Dawn6 (3.2%)
→0.0%prior 6
Dark - unknown roadway lighting1 (0.5%)

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

Road Surface

Dry146 (76.8%)
↑4.3%prior 140
Wet18 (9.5%)
↑38.5%prior 13
Snow11 (5.8%)
↑10.0%prior 10
Ice/frost7 (3.7%)
↑40.0%prior 5
Gravel6 (3.2%)
Mud, dirt2 (1.1%)

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

Vehicles & Demographics

Ford and Chevrolet were the top two vehicle makes involved in crashes in both years, with Chevrolet-branded vehicles seeing a notable increase from 31 to 49 incidents in 2025. Demographically, the age distribution of persons involved in crashes shifted; the 65+ age group became the largest cohort in 2025 with 68 individuals, up from 49 the prior year. The 16-20 age group also saw a significant increase in involvement, from 25 to 40 individuals.

Top Vehicle Makes (331 vehicles)

1
FORD49 (14.8%)
↓-3.9%prior 51
2
CHEV49 (14.8%)
↑58.1%prior 31
3
FREIGHTLINER23 (6.9%)
↑27.8%prior 18
4
CHEVROLET17 (5.1%)
↓-34.6%prior 26
5
DODG14 (4.2%)
↑27.3%prior 11
6
JEEP12 (3.6%)
↓-20.0%prior 15
7
VOLVO9 (2.7%)
8
PETERBILT9 (2.7%)
9
TOYOTA9 (2.7%)
→0.0%prior 9
10
KENWORTH8 (2.4%)
↑60.0%prior 5

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

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

Sex Distribution (222 persons with recorded sex)

Male155 (69.8%)
↑17.4%prior 132
Female67 (30.2%)
↓-1.5%prior 68

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: 221
  • Total persons involved: 350
  • Total vehicles involved: 331

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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