Yearly Traffic Safety Analysis

663 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Marshall County recorded 663 total traffic crashes, a 7.1% decrease from the 714 crashes reported in 2022. While overall collisions declined, the number of fatalities increased from 4 to 7. The most significant year-over-year shift was the number of fatal crashes, which rose from 1 in 2022 to 6 in 2023.

663

▼ -7.1%was 714

Total Crash Events

7

▲ 75.0%was 4

Persons Killed

218

▲ 3.8%was 210

Persons Injured

6

▲ 500.0%was 1

Fatal Crash Events

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) 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

Traffic crashes in Marshall County showed a downward trend, decreasing by 7.1% from 714 in 2022 to 663 in 2023. Despite this overall reduction in collisions, the severity of outcomes worsened. Total injuries saw a slight increase from 210 to 218, and total fatalities rose from 4 to 7 year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 4↑25.0%

2

Other Killed

Prior: 0→%

6

Pedestrians Injured

Prior: 5↑20.0%

5

Cyclists Injured

Prior: 7↓-28.6%

206

Motorists Injured

Prior: 198↑4.0%

1

Other Injured

Prior: 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 temporal patterns of crashes shifted slightly between the two periods. In 2023, Friday was the peak day for crashes with 124 incidents, changing from Thursday (118 incidents) in the prior year. The peak hour also shifted earlier, moving from the 4 p.m. hour in 2022 (55 crashes) to the 3 p.m. hour in 2023 (67 crashes).

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 significantly increased in 2023 compared to 2022, despite fewer total incidents. The number of fatal crashes rose from 1 to 6, and the corresponding fatality count increased from 4 to 7. Consequently, the proportion of crashes resulting in a fatality grew from 0.1% to 0.9%. The count of serious injury crashes remained stable at 22 for both years, while minor injury crashes increased from 64 to 70.

Severity is per crash event (most severe injury). 6 fatal crash events resulted in 7 persons killed.

Outcome by Severity (Crash Events)

Fatal6fatal crashes0.9%
↑500.0%prior 1
Serious Injury22serious injury crashes3.3%
→0.0%prior 22
Minor Injury70minor injury crashes10.6%
↑9.4%prior 64
Possible Injury77possible injury crashes11.6%
→0.0%prior 77
No Injury488no injury crashes73.6%
↓-11.3%prior 550

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 with animals remained the leading contributing factor in both years, though the count decreased from 155 in 2022 to 139 in 2023. The most notable change was in crashes attributed to 'Lost Control,' which saw a 32.3% decrease in count from 62 to 42 incidents, dropping its rank from second to fourth. Conversely, crashes from 'Failure to Yield from a Stop Sign' increased from 52 to 57, becoming the second-most common factor in 2023.

Officer-Reported Primary Contributing Cause

Animal139 (21%)↓-10.3%prior 155
FTYROW: From stop sign57 (8.6%)↑9.6%prior 52
Followed too close42 (6.3%)↑7.7%prior 39
Lost Control42 (6.3%)↓-32.3%prior 62
FTYROW: Making left turn36 (5.4%)↑9.1%prior 33
Driving too fast for conditions35 (5.3%)↓-2.8%prior 36
Other (explain in narrative): Other33 (5%)↓-2.9%prior 34
Ran off road - straight30 (4.5%)↑20.0%prior 25
Ran off road - left22 (3.3%)↓-15.4%prior 26
Ran Stop Sign22 (3.3%)↓-24.1%prior 29

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

Road & Environmental Conditions

In both 2023 and 2022, the majority of crashes occurred during daylight on dry roads under clear skies. There was a notable decrease in crashes under adverse conditions in 2023. Collisions on roads with snow or ice dropped from a combined 87 incidents in 2022 to 61 in 2023. Similarly, crashes in dark, unlit conditions decreased from 112 to 83 year-over-year.

Weather

Clear382 (70.6%)
↓-7.1%prior 411
Cloudy83 (15.3%)
↑2.5%prior 81
Snow29 (5.4%)
↓-6.5%prior 31
Rain22 (4.1%)
↓-15.4%prior 26
Fog, smoke, smog12 (2.2%)
Freezing rain/drizzle11 (2.0%)
↑10.0%prior 10
Severe Winds1 (0.2%)
↓-80.0%prior 5
Sleet, hail1 (0.2%)

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

Lighting

Daylight364 (67.0%)
↓-1.4%prior 369
Dark - roadway not lighted83 (15.3%)
↓-25.9%prior 112
Dark - roadway lighted77 (14.2%)
↓-13.5%prior 89
Dawn9 (1.7%)
↑12.5%prior 8
Dusk8 (1.5%)
↓-11.1%prior 9
Dark - unknown roadway lighting2 (0.4%)

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

Road Surface

Dry415 (76.6%)
↓-2.1%prior 424
Wet49 (9.0%)
↓-2.0%prior 50
Snow31 (5.7%)
↓-35.4%prior 48
Ice/frost30 (5.5%)
↓-23.1%prior 39
Gravel16 (3.0%)
↓-15.8%prior 19
Mud, dirt1 (0.2%)

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

Vehicles & Demographics

The ranking of the most common vehicle makes involved in crashes shifted between periods. In 2023, Ford (179 vehicles) surpassed Chevrolet (174 vehicles) as the top make, a reversal from 2022 when Chevrolet led with 212 vehicles involved. The age distribution of persons involved in crashes remained largely consistent, with the 26-34 age group representing the largest cohort in both years (232 people in 2023 vs. 245 in 2022).

Top Vehicle Makes (1,036 vehicles)

1
FORD179 (17.3%)
↑4.7%prior 171
2
CHEV174 (16.8%)
↓-17.9%prior 212
3
HOND67 (6.5%)
↑3.1%prior 65
4
DODG56 (5.4%)
↑7.7%prior 52
5
JEEP53 (5.1%)
↑6.0%prior 50
6
TOYT43 (4.2%)
↓-24.6%prior 57
7
NISS38 (3.7%)
↑22.6%prior 31
8
GMC36 (3.5%)
↓-7.7%prior 39
9
CHEVROLET34 (3.3%)
↓-33.3%prior 51
10
KIA28 (2.7%)
↑27.3%prior 22

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

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

Sex Distribution (939 persons with recorded sex)

Male560 (59.6%)
↓-5.7%prior 594
Female379 (40.4%)
↓-11.0%prior 426

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: 663
  • Total persons involved: 1,464
  • Total vehicles involved: 1,036

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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