Yearly Traffic Safety Analysis

95 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Butler County, there were 95 total crashes in 2024, a 5.9% decrease from the 101 crashes recorded in 2023. Despite the drop in overall collisions, the number of people injured rose by 31.0%, from 29 in the prior year to 38 in the current period. The number of fatalities remained stable at two for both years.

95

▼ -5.9%was 101

Total Crash Events

2

Persons Killed

38

▲ 31.0%was 29

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in Butler County saw a slight decline in 2024 compared to the previous year, with total incidents falling from 101 to 95. This represents a 5.9% year-over-year decrease in crashes. However, this downward trend in collisions did not correspond with a decrease in harm, as total injuries increased from 29 to 38 while fatalities held steady at two.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 2→0.0%

38

Motorists Injured

Prior: 28↑35.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The most frequent day for crashes shifted from Thursday and Friday (18 crashes each) in 2023 to Monday (19 crashes) in 2024. Similarly, the peak time for collisions moved two hours earlier, from 7 p.m. in the prior year to 5 p.m. in the current year, though both peak hours saw 12 crashes. While October was the month with the most crashes in 2023 (19), the highest crash volumes in 2024 were observed in September and November, with 12 crashes each.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes remained unchanged at two in both 2023 and 2024, though the fatal crash rate saw a slight increase from 1.98% to 2.11% due to the lower overall crash total. Crashes resulting in an injury became more common, with the proportion of collisions involving possible, minor, or serious injuries rising from 21.8% in 2023 to 29.5% in 2024. This increase was primarily driven by a rise in 'Possible Injury' crashes, which grew from 6 incidents to 14 incidents.

Outcome by Severity (Crash Events)

Fatal2fatal crashes2.1%
→0.0%prior 2
Serious Injury5serious injury crashes5.3%
→0.0%prior 5
Minor Injury9minor injury crashes9.5%
↓-18.2%prior 11
Possible Injury14possible injury crashes14.7%
↑133.3%prior 6
No Injury65no injury crashes68.4%
↓-15.6%prior 77

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving animals remained the leading contributing factor in both periods, though their count decreased by 26.2%, from 42 crashes in 2023 to 31 in 2024. 'Lost Control' incidents, the second-most common factor in 2023 with 13 crashes, dropped to just 3 incidents in 2024. Conversely, crashes attributed to 'Failure to Yield Right of Way from a stop sign' more than doubled, increasing from 3 to 7, becoming the second-leading factor in 2024.

Officer-Reported Primary Contributing Cause

Animal31 (32.6%)↓-26.2%prior 42
FTYROW: From stop sign7 (7.4%)
FTYROW: Making left turn5 (5.3%)
Exceeded authorized speed4 (4.2%)
Other (explain in narrative): Other4 (4.2%)
Ran off road - left4 (4.2%)
Driver Distraction: Other interior distraction4 (4.2%)↓-33.3%prior 6
Other (explain in narrative): Vision obstructed3 (3.2%)
Driving too fast for conditions3 (3.2%)
Ran Stop Sign3 (3.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The most notable shift in crash conditions occurred in lighting, where the number of collisions in dark conditions more than doubled, rising from 9 in 2023 to 18 in 2024. This was driven by an increase in crashes on lighted roadways after dark, which went from 2 to 8. The proportions of crashes occurring in clear weather and on dry road surfaces remained relatively stable year-over-year.

Weather

Clear50 (74.6%)
↑4.2%prior 48
Cloudy6 (9.0%)
↓-14.3%prior 7
Snow5 (7.5%)
Rain2 (3.0%)
Blowing sand, soil, dirt2 (3.0%)
Fog, smoke, smog1 (1.5%)
Severe Winds1 (1.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight51 (71.8%)
↓-3.8%prior 53
Dark - roadway lighted8 (11.3%)
Dark - roadway not lighted6 (8.5%)
→0.0%prior 6
Dark - unknown roadway lighting4 (5.6%)
Dawn1 (1.4%)
Dusk1 (1.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry47 (70.1%)
↑2.2%prior 46
Gravel7 (10.4%)
↑16.7%prior 6
Snow5 (7.5%)
Wet5 (7.5%)
→0.0%prior 5
Ice/frost3 (4.5%)
↓-40.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes in both years, with Ford vehicles decreasing from 26 to 24 and Chevrolet from 25 to 22. Buick, which ranked third in 2023 with 9 vehicles, was replaced by Dodge in 2024 with 7 vehicles. Analysis of persons involved in crashes shows a relatively stable age distribution, although the share of individuals in the 26-54 age range decreased from 44.0% of persons in 2023 to 39.5% in 2024.

Top Vehicle Makes (139 vehicles)

1
FORD24 (17.3%)
↓-7.7%prior 26
2
CHEV22 (15.8%)
↓-12.0%prior 25
3
DODGE7 (5%)
4
HONDA6 (4.3%)
5
NISS6 (4.3%)
6
GMC6 (4.3%)
7
DODG6 (4.3%)
↓-14.3%prior 7
8
HOND5 (3.6%)
9
JEEP5 (3.6%)
→0.0%prior 5
10
CHEVROLET5 (3.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (69 persons with recorded sex)

Male44 (63.8%)
↓-45.0%prior 80
Female25 (36.2%)
↓-50.0%prior 50

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 95
  • Total persons involved: 147
  • Total vehicles involved: 139

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: 2024." Published September 9, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2024-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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