Yearly Traffic Safety Analysis

99 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Montgomery County, total crashes decreased from 117 in 2024 to 99 in 2025, a 15.4% reduction. While overall collisions and injuries declined, the number of crashes attributed to failing to yield the right-of-way from a stop sign increased from 9 to 15 incidents year-over-year.

99

▼ -15.4%was 117

Total Crash Events

1

Persons Killed

26

▼ -27.8%was 36

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

Traffic crashes in Montgomery County showed a downward trend year-over-year. The total number of crashes fell by 15.4%, from 117 in the prior period to 99 in the current period. Similarly, the number of people injured in these incidents decreased by 27.8%, from 36 to 26, while fatalities remained constant at one person killed in each period.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 1→0.0%

26

Motorists Injured

Prior: 36↓-27.8%

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 remained broadly similar year-over-year, with Friday being the peak day for crashes in both periods, recording 20 crashes in 2025 and 24 in 2024. The peak hour for collisions shifted slightly from 5 PM in the prior period (10 crashes) to 4 PM in the current period (12 crashes). A notable change was observed on Wednesdays, where crash counts decreased from 21 to 10.

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 the number of fatal crashes remained unchanged at one for both periods, the fatal crash rate increased from 0.85% to 1.01% due to the lower overall crash total in the current year. The distribution of injury severity shifted, with two serious injury crashes recorded in 2025 compared to none in 2024. Conversely, crashes resulting in 'Possible Injury' saw a significant decrease, dropping from 19 incidents to 8.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1%
→0.0%prior 1
Serious Injury2serious injury crashes2%
Minor Injury10minor injury crashes10.1%
→0.0%prior 10
Possible Injury8possible injury crashes8.1%
↓-57.9%prior 19
No Injury78no injury crashes78.8%
↓-10.3%prior 87

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 between the two periods. 'Failure to yield right-of-way from a stop sign' became the top factor in 2025, with incidents increasing in count from 9 to 15. The previous leading cause, 'Animal' involvement, decreased from 20 to 14 incidents. Another significant change was the reduction in crashes due to 'Followed too close,' which dropped from 15 incidents to 6. Conversely, crashes from 'Ran Stop Sign' increased from 2 to 6.

Officer-Reported Primary Contributing Cause

FTYROW: From stop sign15 (15.2%)↑66.7%prior 9
Animal14 (14.1%)↓-30.0%prior 20
Followed too close6 (6.1%)↓-60.0%prior 15
Ran Stop Sign6 (6.1%)
Improper Backing5 (5.1%)
FTYROW: Making left turn4 (4%)
Driver Distraction: Exterior distraction4 (4%)
FTYROW: From yield sign4 (4%)
Other (explain in narrative): Other3 (3%)↓-40.0%prior 5
Lost Control3 (3%)

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 majority of crashes in both periods occurred in clear weather and on dry roads, with the proportion of crashes under these conditions remaining relatively stable. A significant shift was observed in lighting conditions, as the number of crashes occurring in the dark decreased from 21 in the prior period to 8 in the current period. Correspondingly, crashes in daylight accounted for 73.7% of all incidents in 2025, up from 61.5% in 2024.

Weather

Clear67 (78.8%)
↓-11.8%prior 76
Cloudy11 (12.9%)
↓-26.7%prior 15
Snow3 (3.5%)
Fog, smoke, smog2 (2.4%)
Rain2 (2.4%)
↓-60.0%prior 5

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

Lighting

Daylight73 (85.9%)
↑1.4%prior 72
Dark - roadway not lighted6 (7.1%)
↓-53.8%prior 13
Dusk3 (3.5%)
↓-40.0%prior 5
Dawn1 (1.2%)
Dark - unknown roadway lighting1 (1.2%)
Dark - roadway lighted1 (1.2%)
↓-80.0%prior 5

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

Road Surface

Dry70 (82.4%)
↓-10.3%prior 78
Snow6 (7.1%)
Wet4 (4.7%)
↓-55.6%prior 9
Ice/frost2 (2.4%)
Gravel2 (2.4%)
↓-60.0%prior 5
Slush1 (1.2%)

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 for both periods, though both saw a decrease in raw numbers, with Ford-involved vehicles dropping from 49 to 35 and Chevrolet from 26 to 23. An analysis of persons involved in crashes shows a shift in age demographics. The number of individuals in the 55-64 age group increased from 21 to 28, and the 65+ group grew from 33 to 35, indicating a higher count of older individuals in the current period's crashes.

Top Vehicle Makes (170 vehicles)

1
FORD35 (20.6%)
↓-28.6%prior 49
2
CHEV23 (13.5%)
↓-11.5%prior 26
3
JEEP11 (6.5%)
↑10.0%prior 10
4
GMC11 (6.5%)
↑83.3%prior 6
5
NISS8 (4.7%)
6
BUIC7 (4.1%)
↑40.0%prior 5
7
CHRY7 (4.1%)
↓-12.5%prior 8
8
DODG6 (3.5%)
↓-40.0%prior 10
9
KIA6 (3.5%)
10
HYUN6 (3.5%)
→0.0%prior 6

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

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

Sex Distribution (118 persons with recorded sex)

Male72 (61.0%)
→0.0%prior 72
Female46 (39.0%)
↓-8.0%prior 50

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: 99
  • Total persons involved: 175
  • Total vehicles involved: 170

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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