Yearly Traffic Safety Analysis

78 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In 2018, Butler County recorded 78 total crashes, a 14.3% decrease from the 91 crashes reported in 2017. The most significant year-over-year change was the reduction in traffic fatalities, which fell from two in the prior period to zero in the current period. Total injuries also saw a decrease from 39 to 33.

78

▼ -14.3%was 91

Total Crash Events

0

▼ -100.0%was 2

Persons Killed

33

▼ -15.4%was 39

Persons Injured

0

▼ -100.0%was 2

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash trends in Butler County showed a notable improvement from 2017 to 2018. Total crashes decreased by 14.3%, falling from 91 to 78. This downward trend extended to crash outcomes, with total injuries declining by 15.4% from 39 to 33 and fatalities dropping from two to zero.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 2↓-100.0%

33

Motorists Injured

Prior: 39↓-15.4%

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Butler County shifted between 2017 and 2018. The peak day for crashes moved from Friday (17 crashes) in the prior year to Tuesday (17 crashes) in the current year. The peak hour for collisions also shifted earlier in the day, from the 5 p.m. hour in 2017 to the 3 p.m. hour in 2018, with both peak hours recording 10 crashes respectively.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity improved significantly in 2018, with fatal crashes decreasing from two in 2017 to zero. The share of serious injury crashes remained stable, accounting for 5.5% of crashes in 2017 and 5.1% in 2018. However, the proportion of minor injury crashes increased from 9.9% of all crashes in 2017 to 17.9% in 2018, while the share of no-injury crashes fell from 68.1% to 62.8%.

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes5.1%
↓-20.0%prior 5
Minor Injury14minor injury crashes17.9%
↑55.6%prior 9
Possible Injury11possible injury crashes14.1%
↓-15.4%prior 13
No Injury49no injury crashes62.8%
↓-21.0%prior 62

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor in both periods was 'Animal,' though its count dropped by 53.3% from 30 incidents in 2017 to 14 in 2018. 'Lost Control' remained the second-most common factor, with its count holding steady from 10 to 11 crashes year-over-year. Crashes attributed to 'Driving too fast for conditions' decreased from 7 to 5, while 'Operating vehicle in a reckless, erratic, careless, negligent manner' was a more prominent factor in 2018 with 5 recorded incidents.

Officer-Reported Primary Contributing Cause

Animal14 (17.9%)↓-53.3%prior 30
Lost Control11 (14.1%)↑10.0%prior 10
Driving too fast for conditions5 (6.4%)↓-28.6%prior 7
Operating vehicle in an reckless, erratic, careless, negligent manner5 (6.4%)
Ran off road - left4 (5.1%)
Driver Distraction: Inattentive/lost in thought4 (5.1%)
FTYROW: From parked position4 (5.1%)
Ran off road - straight3 (3.8%)
FTYROW: From stop sign3 (3.8%)
Followed too close3 (3.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both 2017 and 2018 occurred in clear weather and on dry roads. However, the proportion of crashes happening during daylight hours increased from 50.5% of all crashes in 2017 to 61.5% in 2018. The share of crashes on icy or frosty road surfaces also saw an increase, rising from 5.5% of total incidents in the prior year to 10.3% in the current year.

Weather

Clear49 (75.4%)
↑22.5%prior 40
Cloudy5 (7.7%)
↓-50.0%prior 10
Snow4 (6.2%)
Fog, smoke, smog3 (4.6%)
Blowing Snow3 (4.6%)
Freezing rain/drizzle1 (1.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Weather condition at time of crash

Lighting

Daylight48 (73.8%)
↑4.3%prior 46
Dark - roadway not lighted9 (13.8%)
↓-10.0%prior 10
Dark - roadway lighted4 (6.2%)
Dawn3 (4.6%)
Dusk1 (1.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Lighting condition field

Road Surface

Dry38 (58.5%)
↓-15.6%prior 45
Ice/frost8 (12.3%)
↑60.0%prior 5
Gravel7 (10.8%)
Snow5 (7.7%)
Wet5 (7.7%)
↓-37.5%prior 8
Slush2 (3.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Road surface condition field

Vehicles & Demographics

Comparing vehicles involved in crashes, Chevrolet (28 vehicles) overtook Ford (23 vehicles) as the most common make in 2018, reversing the order from 2017 when Ford led with 30 vehicles to Chevrolet's 27. The number of persons involved in crashes from the 55-64 age group increased from 15 to 22 year-over-year. Conversely, involvement of the 16-20 age group decreased from 27 individuals in 2017 to 23 in 2018.

Top Vehicle Makes (117 vehicles)

1
FORD23 (19.7%)
↓-23.3%prior 30
2
CHEVROLET14 (12%)
→0.0%prior 14
3
CHEV14 (12%)
↑7.7%prior 13
4
CHRY6 (5.1%)
5
CHRYSLER5 (4.3%)
6
TOYT5 (4.3%)
7
JEEP4 (3.4%)
8
DODG3 (2.6%)
↓-70.0%prior 10
9
DODGE3 (2.6%)
↓-66.7%prior 9
10
GMC3 (2.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records

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

Sex Distribution (90 persons with recorded sex)

Male52 (57.8%)
↓-11.9%prior 59
Female38 (42.2%)
↑11.8%prior 34

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · 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: 2018-01-01 through 2018-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2018-01-01 through 2018-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 78
  • Total persons involved: 142
  • Total vehicles involved: 117

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: 2018." Published September 9, 2026. Reporting period: 2018-01-01 to 2018-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2018-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

ThatCarHitMe.com · An Injuria.ai Company