Yearly Traffic Safety Analysis

249 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Tama County, a total of 249 traffic crashes were recorded in 2025, a 5.0% decrease from the 262 crashes in 2024. While overall crashes declined, the number of persons injured increased by 16.4%. The most significant change in contributing factors was a 46.7% reduction in crashes involving driving under the influence (DUI), which fell from 15 incidents in 2024 to 8 in 2025.

249

▼ -5.0%was 262

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

78

▲ 16.4%was 67

Persons Injured

1

▼ -50.0%was 2

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

The overall trend in Tama County shows a decrease in the total number of crashes, which fell from 262 in 2024 to 249 in 2025. However, this decrease in crash volume was accompanied by an increase in the number of people injured, which rose from 67 to 78. The number of fatalities also decreased, with one fatality recorded in 2025 compared to two in the prior year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 2↓-50.0%

2

Pedestrians Injured

Prior: 1↑100.0%

1

Cyclists Injured

Prior: 0→%

75

Motorists Injured

Prior: 65↑15.4%

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

Year-over-year, the temporal patterns of crashes showed some shifts. Saturday remained the peak day for crashes, with the count increasing from 42 in 2024 to 46 in 2025. The peak hour for crashes shifted from a tie at 6 a.m. and 6 p.m. in the prior year (21 crashes each) to 5 p.m. in the current year (20 crashes). Notably, crashes on Mondays increased from 34 to 42, while Sunday crashes saw a significant drop from 39 to 26.

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 shifted slightly between the two periods. The number of fatal crashes decreased from 2 in 2024 to 1 in 2025, and the fatal crash rate fell from 0.8% to 0.4%. While the total number of crashes declined, the number of persons injured increased from 67 to 78. Crashes resulting in serious injuries rose from 8 to 9, and minor injury crashes increased from 30 to 32. Consequently, the proportion of crashes with no injuries decreased from 77.5% to 75.5% of all incidents.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
↓-50.0%prior 2
Serious Injury9serious injury crashes3.6%
↑12.5%prior 8
Minor Injury32minor injury crashes12.9%
↑6.7%prior 30
Possible Injury19possible injury crashes7.6%
→0.0%prior 19
No Injury188no injury crashes75.5%
↓-7.4%prior 203

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 top contributing factor in both years, though the count decreased by 25% from 116 crashes in 2024 to 87 in 2025. Several other factors saw notable increases in count, including 'Driving too fast for conditions' (from 9 to 15 crashes), 'Followed too close' (from 5 to 11 crashes), and 'Ran Stop Sign' (from 3 to 9 crashes). Conversely, crashes attributed to 'Failure to yield right of way from a stop sign' decreased from 13 to 8 incidents.

Officer-Reported Primary Contributing Cause

Animal87 (34.9%)↓-25.0%prior 116
Lost Control21 (8.4%)↑16.7%prior 18
Driving too fast for conditions15 (6%)↑66.7%prior 9
Followed too close11 (4.4%)↑120.0%prior 5
Ran off road - straight10 (4%)↓-28.6%prior 14
Ran off road - left9 (3.6%)↓-18.2%prior 11
Ran Stop Sign9 (3.6%)
Other (explain in narrative): Other8 (3.2%)→0.0%prior 8
FTYROW: From stop sign8 (3.2%)↓-38.5%prior 13
Driver Distraction: Inattentive/lost in thought7 (2.8%)

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

Road & Environmental Conditions

There was a notable shift in crash conditions year-over-year. Crashes occurring on adverse road surfaces increased, with incidents on snowy roads rising from 11 to 16 and those on icy or frosty roads tripling from 4 to 12. Despite the increase in winter-condition crashes, a larger share of total crashes in 2025 occurred during daylight (109 crashes, or 43.8% of total) compared to 2024 (92 crashes, or 35.1% of total).

Weather

Clear122 (73.5%)
↑18.4%prior 103
Cloudy20 (12.0%)
↓-28.6%prior 28
Snow10 (6.0%)
↑42.9%prior 7
Blowing Snow6 (3.6%)
Rain4 (2.4%)
↓-33.3%prior 6
Severe Winds2 (1.2%)
Freezing rain/drizzle1 (0.6%)
Fog, smoke, smog1 (0.6%)

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

Lighting

Daylight109 (63.4%)
↑18.5%prior 92
Dark - roadway not lighted36 (20.9%)
↓-5.3%prior 38
Dark - roadway lighted13 (7.6%)
↑44.4%prior 9
Dawn7 (4.1%)
↑40.0%prior 5
Dark - unknown roadway lighting5 (2.9%)
↓-28.6%prior 7
Dusk2 (1.2%)
↓-75.0%prior 8

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

Road Surface

Dry123 (72.8%)
↑8.8%prior 113
Snow16 (9.5%)
↑45.5%prior 11
Ice/frost12 (7.1%)
Wet8 (4.7%)
↓-38.5%prior 13
Gravel8 (4.7%)
↓-27.3%prior 11
Slush1 (0.6%)
Mud, dirt1 (0.6%)

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 remained consistent, with Chevrolet (59) and Ford (57) being the most common in 2025, swapping the top two positions from 2024 when Ford (58) and Chevrolet (54) led. The age demographics of persons involved in crashes showed a shift; the 26-34 age group saw an increase from 55 to 67 individuals, and the 55-64 age group grew from 30 to 49. In contrast, the number of people in the 35-44 and 45-54 age groups involved in crashes decreased.

Top Vehicle Makes (336 vehicles)

1
CHEV59 (17.6%)
↑9.3%prior 54
2
FORD57 (17%)
↓-1.7%prior 58
3
HOND20 (6%)
↑300.0%prior 5
4
CHEVROLET18 (5.4%)
↑38.5%prior 13
5
KIA13 (3.9%)
↑44.4%prior 9
6
TOYT13 (3.9%)
↓-31.6%prior 19
7
DODG13 (3.9%)
→0.0%prior 13
8
NR10 (3%)
9
RAM10 (3%)
↑100.0%prior 5
10
NISS9 (2.7%)
↑12.5%prior 8

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

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

Sex Distribution (151 persons with recorded sex)

Male106 (70.2%)
↑15.2%prior 92
Female45 (29.8%)
↓-19.6%prior 56

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: 249
  • Total persons involved: 351
  • Total vehicles involved: 336

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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