Yearly Traffic Safety Analysis

253 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Floyd County recorded 253 total crashes, a 12.5% decrease from the 289 crashes documented in 2022. While overall crashes and injuries remained stable or declined, the most significant year-over-year change was the emergence of fatal incidents. Fatalities rose from zero in 2022 to five in 2023, resulting from four separate fatal crashes.

253

▼ -12.5%was 289

Total Crash Events

5

Persons Killed

62

▼ -1.6%was 63

Persons Injured

4

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 for crashes in Floyd County was downward, with total incidents falling by 12.5% from 289 in 2022 to 253 in 2023. The number of people injured remained nearly unchanged, decreasing from 63 to 62. In a reversal of the prior year's trend, there were five fatalities recorded in 2023, whereas none were recorded in 2022.

Vulnerable Road User Casualties

5

Motorists Killed

Prior: 0→%

0

Other Killed

Prior: 0→0.0%

56

Motorists Injured

Prior: 60↓-6.7%

6

Other Injured

Prior: 1↑500.0%

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 between the two periods. In 2023, the peak day for crashes was Wednesday with 45 incidents, a change from Monday (48 incidents) in 2022. The busiest time of day also moved later, with the peak hour shifting from 3 p.m. in 2022 (30 crashes) to the 5 p.m. commute hour in 2023 (23 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

Although total crashes decreased, the severity of outcomes worsened in 2023. Fatal crashes, which were absent in the prior year, accounted for 1.6% of all incidents in 2023 (4 crashes). The proportion of crashes resulting in serious injuries also increased from 1.0% in 2022 to 1.6% in 2023. Crashes resulting in no injuries made up a slightly smaller share of the total, decreasing from 81.0% to 79.4%.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.6%
Serious Injury4serious injury crashes1.6%
↑33.3%prior 3
Minor Injury15minor injury crashes5.9%
↓-28.6%prior 21
Possible Injury29possible injury crashes11.5%
↓-6.5%prior 31
No Injury201no injury crashes79.4%
↓-14.1%prior 234

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 animals remained the top contributing factor in both periods, with the count of these incidents increasing by 11.2% from 98 in 2022 to 109 in 2023. In contrast, several other leading factors saw significant reductions. Crashes attributed to 'Driving too fast for conditions' fell by 36.4% (from 22 to 14 incidents), and incidents of 'Followed too close' were halved, decreasing from 20 to 10.

Officer-Reported Primary Contributing Cause

Animal109 (43.1%)↑11.2%prior 98
Driving too fast for conditions14 (5.5%)↓-36.4%prior 22
FTYROW: At uncontrolled intersection10 (4%)↑11.1%prior 9
Followed too close10 (4%)↓-50.0%prior 20
Lost Control10 (4%)↓-23.1%prior 13
FTYROW: From stop sign10 (4%)↓-9.1%prior 11
Ran Stop Sign8 (3.2%)↓-20.0%prior 10
Ran Traffic Signal7 (2.8%)↑16.7%prior 6
Ran off road - straight6 (2.4%)↑20.0%prior 5
Other (explain in narrative): Other6 (2.4%)↓-57.1%prior 14

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

Road & Environmental Conditions

The proportion of crashes occurring in clear weather and on dry roads was consistent year-over-year. There was a significant decrease in crashes related to adverse road conditions, as incidents on icy or frosty surfaces dropped from 26 in 2022 to 10 in 2023. The share of crashes taking place in daylight also saw a notable reduction, from 52.6% of all incidents in 2022 to 41.9% in 2023.

Weather

Clear100 (64.9%)
↓-15.3%prior 118
Cloudy31 (20.1%)
↓-27.9%prior 43
Snow11 (7.1%)
↑10.0%prior 10
Rain6 (3.9%)
↓-25.0%prior 8
Fog, smoke, smog2 (1.3%)
Severe Winds2 (1.3%)
Freezing rain/drizzle1 (0.6%)
↓-90.0%prior 10
Blowing Snow1 (0.6%)
↓-83.3%prior 6

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

Lighting

Daylight106 (67.9%)
↓-30.3%prior 152
Dark - roadway lighted15 (9.6%)
↓-16.7%prior 18
Dark - roadway not lighted15 (9.6%)
↓-11.8%prior 17
Dawn12 (7.7%)
Dusk5 (3.2%)
Dark - unknown roadway lighting3 (1.9%)

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

Road Surface

Dry112 (72.7%)
↓-13.2%prior 129
Snow13 (8.4%)
↓-18.8%prior 16
Wet13 (8.4%)
↓-27.8%prior 18
Ice/frost10 (6.5%)
↓-61.5%prior 26
Gravel4 (2.6%)
↓-33.3%prior 6
Slush1 (0.6%)
Mud, dirt1 (0.6%)

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

Vehicles & Demographics

Ford and Chevrolet were the top two vehicle makes involved in crashes in both 2022 and 2023, with both seeing a reduction in total counts. The demographics of individuals involved in crashes shifted, with an increased representation of the 35-44 age group, which grew from 104 people in 2022 to 124 in 2023. Conversely, the number of people in the 45-54 age group involved in crashes decreased from 89 to 58.

Top Vehicle Makes (365 vehicles)

1
FORD64 (17.5%)
↓-17.9%prior 78
2
CHEV56 (15.3%)
↓-16.4%prior 67
3
CHEVROLET24 (6.6%)
→0.0%prior 24
4
JEEP19 (5.2%)
↑11.8%prior 17
5
DODG17 (4.7%)
↓-41.4%prior 29
6
CHRY15 (4.1%)
↑7.1%prior 14
7
TOYT12 (3.3%)
↑20.0%prior 10
8
HOND11 (3%)
→0.0%prior 11
9
NISS10 (2.7%)
↑11.1%prior 9
10
TOYO10 (2.7%)

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

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

Sex Distribution (347 persons with recorded sex)

Male201 (57.9%)
↓-17.3%prior 243
Female146 (42.1%)
↓-11.0%prior 164

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: 253
  • Total persons involved: 538
  • Total vehicles involved: 365

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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