Yearly Traffic Safety Analysis

151 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Lyon County, total traffic crashes increased by 4.1%, from 145 incidents in 2022 to 151 in 2023. While the number of fatal crashes remained stable at one, the total number of injuries reported saw a notable decrease of 17.0%, falling from 53 to 44. The most significant shift was a sharp rise in broadside collisions, which nearly doubled from 16 to 31 year-over-year.

151

▲ 4.1%was 145

Total Crash Events

1

Persons Killed

44

▼ -17.0%was 53

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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend shows a minor increase in total crashes, rising to 151 in 2023 from 145 in the prior year. This increase in crash volume was accompanied by a positive trend in outcomes, as total injuries fell by 17.0% from 53 to 44. The number of fatalities was unchanged, with one person killed in a crash in both 2022 and 2023.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 1→0.0%

44

Motorists Injured

Prior: 50↓-12.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted year-over-year. The peak day for crashes moved from a tie between Monday and Friday (26 crashes each) in 2022 to Wednesday (31 crashes) in 2023. Similarly, the peak hour for collisions shifted two hours earlier, from 5 p.m. (19 crashes) in 2022 to 3 p.m. (19 crashes) in 2023. The number of crashes during the 3 p.m. hour saw a significant increase, rising from 10 incidents in the prior year.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity profiles showed a decrease in injury outcomes despite a rise in total incidents. The fatal crash rate saw a marginal decline from 0.69 to 0.66 per 100 crashes, with one fatal incident recorded in each period. The proportion of crashes resulting in any type of injury (serious, minor, or possible) decreased from 30.3% of all crashes in 2022 to 25.2% in 2023. Correspondingly, the share of no-injury crashes grew from 69.0% to 74.2% of the total.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.7%
→0.0%prior 1
Serious Injury7serious injury crashes4.6%
→0.0%prior 7
Minor Injury13minor injury crashes8.6%
↓-23.5%prior 17
Possible Injury18possible injury crashes11.9%
↓-10.0%prior 20
No Injury112no injury crashes74.2%
↑12.0%prior 100

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the top contributing factor in both periods, though the count of such incidents decreased from 45 in 2022 to 37 in 2023. 'Lost Control' became a more prominent factor, increasing from 12 to 16 incidents and moving from the third to the second-ranked cause. 'Driving too fast for conditions' held steady with 11 incidents in both years. 'Failure to yield from a stop sign' incidents decreased slightly from 10 to 9.

Officer-Reported Primary Contributing Cause

Animal37 (24.5%)↓-17.8%prior 45
Lost Control16 (10.6%)↑33.3%prior 12
Driving too fast for conditions11 (7.3%)→0.0%prior 11
Ran off road - straight10 (6.6%)↓-23.1%prior 13
Ran Stop Sign9 (6%)
FTYROW: From stop sign9 (6%)↓-10.0%prior 10
Followed too close8 (5.3%)
FTYROW: At uncontrolled intersection6 (4%)
Ran off road - left3 (2%)
Exceeded authorized speed3 (2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift in the conditions under which crashes occurred. The proportion of crashes on dry road surfaces decreased from 63.4% in 2022 to 50.3% in 2023. Concurrently, incidents on adverse surfaces increased, with crashes on ice or frost rising from 10 to 15 and crashes on snow-covered roads doubling from 5 to 10. Lighting conditions remained relatively stable, with daylight crashes accounting for 52.4% of incidents in 2022 and 53.6% in 2023.

Weather

Clear85 (71.4%)
↓-9.6%prior 94
Rain9 (7.6%)
Cloudy7 (5.9%)
↑16.7%prior 6
Fog, smoke, smog6 (5.0%)
Blowing Snow5 (4.2%)
↓-16.7%prior 6
Snow4 (3.4%)
Freezing rain/drizzle2 (1.7%)
Severe Winds1 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight81 (64.8%)
↑6.6%prior 76
Dark - roadway not lighted34 (27.2%)
↑3.0%prior 33
Dusk4 (3.2%)
Dawn2 (1.6%)
Dark - unknown roadway lighting2 (1.6%)
Dark - roadway lighted2 (1.6%)
↓-66.7%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry76 (62.8%)
↓-17.4%prior 92
Ice/frost15 (12.4%)
↑50.0%prior 10
Gravel10 (8.3%)
Snow10 (8.3%)
↑100.0%prior 5
Wet8 (6.6%)
↑60.0%prior 5
Slush2 (1.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Ford (40 vehicles) and Chevrolet (combined 42 vehicles) being the most common in 2023, reflecting similar counts from the previous year. Analysis of persons involved shows a shift in age demographics. The 16-20 age group's share of involvement increased from 15.2% of all persons in 2022 to 17.7% in 2023. The 35-44 age group also saw its representation increase, rising from 11.0% to 14.0% of all individuals involved in crashes.

Top Vehicle Makes (215 vehicles)

1
FORD40 (18.6%)
↑2.6%prior 39
2
CHEV25 (11.6%)
↓-7.4%prior 27
3
CHEVROLET17 (7.9%)
↑30.8%prior 13
4
BUIC10 (4.7%)
↑66.7%prior 6
5
GMC9 (4.2%)
→0.0%prior 9
6
JEEP8 (3.7%)
7
PONT7 (3.3%)
8
DODG7 (3.3%)
↓-12.5%prior 8
9
KIA6 (2.8%)
10
RAM5 (2.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (205 persons with recorded sex)

Male138 (67.3%)
↑38.0%prior 100
Female67 (32.7%)
↓-9.5%prior 74

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 151
  • Total persons involved: 299
  • Total vehicles involved: 215

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-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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