Yearly Traffic Safety Analysis

77 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Butler County recorded 77 total traffic crashes, a slight 1.3% decrease from the 78 crashes recorded in 2019. While total crashes and injuries remained relatively stable, with 34 injuries in 2020 versus 35 in the prior year, there was a notable 50% decrease in crashes involving driving under the influence (DUI), which fell from 4 incidents in 2019 to 2 in 2020. Both periods reported zero fatalities.

77

▼ -1.3%was 78

Total Crash Events

0

Persons Killed

34

▼ -2.9%was 35

Persons Injured

0

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 · 2020-01-01 to 2020-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Butler County were stable year-over-year. Total crashes decreased by a single incident, from 78 in 2019 to 77 in 2020. Similarly, the number of people injured in these crashes saw a minor decline from 35 to 34, while fatalities remained at zero for both years, indicating a consistent safety landscape.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 0→%

33

Motorists Injured

Prior: 35↓-5.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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 the peak hour for crashes remained 5 p.m. in both 2020 (7 crashes) and 2019 (9 crashes), the peak day for incidents became more pronounced. Wednesday was the peak day in 2020 with 17 crashes, an increase from 2019 when Wednesday and Tuesday shared the peak with 14 crashes each. The month with the most crashes also shifted from March (10 crashes) in 2019 to October (11 crashes) in 2020.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity levels remained largely consistent year-over-year, with zero fatal crashes reported in either 2019 or 2020. The number of serious injury crashes decreased slightly from 4 in 2019 to 3 in 2020. Conversely, crashes resulting in possible injuries increased from 11 in 2019 to 13 in 2020, while minor injury crashes were unchanged at 12 incidents in both periods. Crashes with no injuries accounted for the majority in both years, with 49 in 2020 and 51 in 2019.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes3.9%
↓-25.0%prior 4
Minor Injury12minor injury crashes15.6%
→0.0%prior 12
Possible Injury13possible injury crashes16.9%
↑18.2%prior 11
No Injury49no injury crashes63.6%
↓-3.9%prior 51

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the top contributing factor in both years, though the count of these incidents decreased by 20%, from 20 crashes in 2019 to 16 in 2020. The most significant change was the rise of 'Lost Control' as a factor, which increased by 200% from 4 crashes in 2019 to 12 in 2020, making it the second-leading cause. Conversely, 'Ran off road - straight' incidents decreased from 7 in 2019 to 3 in 2020. Total driver distraction-related crashes increased from 4 in 2019 to 10 in 2020.

Officer-Reported Primary Contributing Cause

Animal16 (20.8%)↓-20.0%prior 20
Lost Control12 (15.6%)
Driver Distraction: Other interior distraction5 (6.5%)
FTYROW: From stop sign5 (6.5%)↓-16.7%prior 6
Ran off road - left4 (5.2%)↓-20.0%prior 5
Ran off road - right3 (3.9%)
Ran off road - straight3 (3.9%)↓-57.1%prior 7
Failed to keep in proper lane3 (3.9%)
Other (explain in narrative): Other3 (3.9%)↓-40.0%prior 5
Operating vehicle in an reckless, erratic, careless, negligent manner3 (3.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a distinct shift in the conditions under which crashes occurred. In 2020, a higher number of crashes happened in ideal conditions compared to the prior year, with incidents on dry roads increasing from 35 to 44 and those in clear weather rising from 34 to 50. Correspondingly, crashes during adverse conditions saw a marked decrease; incidents on wet, snowy, or icy roads fell from 24 in 2019 to 11 in 2020. Crashes in daylight remained the most common lighting condition, with 42 incidents in 2020 compared to 43 in 2019.

Weather

Clear50 (83.3%)
↑47.1%prior 34
Cloudy4 (6.7%)
↓-50.0%prior 8
Snow3 (5.0%)
↓-40.0%prior 5
Rain2 (3.3%)
↓-60.0%prior 5
Freezing rain/drizzle1 (1.7%)
↓-83.3%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Weather condition at time of crash

Lighting

Daylight42 (68.9%)
↓-2.3%prior 43
Dark - roadway not lighted10 (16.4%)
↓-23.1%prior 13
Dark - roadway lighted6 (9.8%)
Dawn3 (4.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Lighting condition field

Road Surface

Dry44 (72.1%)
↑25.7%prior 35
Gravel6 (9.8%)
Wet6 (9.8%)
↓-14.3%prior 7
Ice/frost3 (4.9%)
↓-70.0%prior 10
Snow2 (3.3%)
↓-71.4%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Chevrolet (35 vehicles) and Ford (19 vehicles) leading in 2020, similar to their 2019 rankings. However, the age distribution of persons involved in crashes changed notably. The number of individuals in the 16-20 age group dropped from 24 in 2019 to 9 in 2020. In contrast, involvement increased for the 35-44 age group (from 23 to 34 persons) and the 65+ age group (from 20 to 29 persons).

Top Vehicle Makes (115 vehicles)

1
CHEV24 (20.9%)
↓-14.3%prior 28
2
FORD19 (16.5%)
↓-5.0%prior 20
3
CHEVROLET11 (9.6%)
4
DODGE7 (6.1%)
5
DODG5 (4.3%)
↓-16.7%prior 6
6
GMC4 (3.5%)
7
BUIC3 (2.6%)
8
NR3 (2.6%)
9
CHRYSLER3 (2.6%)
10
PONT3 (2.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Vehicle unit records

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

Sex Distribution (101 persons with recorded sex)

Male59 (58.4%)
↑1.7%prior 58
Female42 (41.6%)
↓-17.6%prior 51

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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: 2020-01-01 through 2020-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-01-01 through 2020-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 77
  • Total persons involved: 177
  • Total vehicles involved: 115

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: 2020." Published September 9, 2026. Reporting period: 2020-01-01 to 2020-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2020-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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