Yearly Traffic Safety Analysis

768 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Webster County recorded 768 total crashes, a 5.8% decrease from the 815 crashes reported in 2022. Despite the overall reduction in collisions, the number of fatalities increased significantly, rising from 2 in the prior year to 8 in the current period. This represents a 300% year-over-year increase in traffic-related deaths.

768

▼ -5.8%was 815

Total Crash Events

8

▲ 300.0%was 2

Persons Killed

195

▼ -9.3%was 215

Persons Injured

8

▲ 300.0%was 2

Fatal Crash Events

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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

Overall, the total number of crashes in Webster County decreased by 5.8% from 2022 to 2023, falling from 815 to 768 incidents. The number of people injured in these crashes also saw a decline of 9.3%, from 215 to 195. In contrast, the number of fatalities saw a substantial increase from 2 to 8 year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

8

Motorists Killed

Prior: 2↑300.0%

0

Other Killed

Prior: 0→0.0%

2

Pedestrians Injured

Prior: 2→0.0%

3

Cyclists Injured

Prior: 5↓-40.0%

189

Motorists Injured

Prior: 207↓-8.7%

1

Other Injured

Prior: 1→0.0%

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 showed some shifts between the two periods. The peak day for crashes moved from Monday (129 crashes) in 2022 to Thursday (142 crashes) in 2023. The peak hour for collisions remained consistent at the 3 p.m. hour in both years, with a slight increase in crashes during this hour from 62 to 68. Crash volumes in 2023 were more concentrated on Thursdays and Fridays, whereas 2022 saw a more even distribution across the weekdays.

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 worsened significantly in 2023 compared to the prior year. The number of fatal crashes quadrupled from 2 to 8, causing the fatal crash rate to rise from 0.25% to 1.04%. The proportion of serious injury crashes also increased, moving from 1.7% of all crashes in 2022 to 2.7% in 2023. Correspondingly, the share of crashes resulting in no injuries decreased from 76.7% to 74.7%.

Outcome by Severity (Crash Events)

Fatal8fatal crashes1%
↑300.0%prior 2
Serious Injury21serious injury crashes2.7%
↑50.0%prior 14
Minor Injury66minor injury crashes8.6%
↑4.8%prior 63
Possible Injury99possible injury crashes12.9%
↓-10.8%prior 111
No Injury574no injury crashes74.7%
↓-8.2%prior 625

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 leading contributing factor in both periods, though the count decreased by 10% from 110 in 2022 to 99 in 2023. A notable shift occurred with 'Driving too fast for conditions,' which fell from the third-ranked cause with 61 crashes to the eighth-ranked with 27 crashes, a 55.7% reduction in count. Conversely, crashes attributed to 'Followed too close' increased by 32.6% in count, rising from 43 incidents in 2022 to 57 in 2023.

Officer-Reported Primary Contributing Cause

Animal99 (12.9%)↓-10.0%prior 110
Other (explain in narrative): Other76 (9.9%)↓-22.4%prior 98
Followed too close57 (7.4%)↑32.6%prior 43
FTYROW: From stop sign51 (6.6%)↓-8.9%prior 56
Lost Control37 (4.8%)↓-19.6%prior 46
Driver Distraction: Other interior distraction37 (4.8%)↑23.3%prior 30
Ran off road - left31 (4%)↑3.3%prior 30
Driving too fast for conditions27 (3.5%)↓-55.7%prior 61
FTYROW: Making left turn21 (2.7%)↓-34.4%prior 32
Ran Traffic Signal19 (2.5%)↑46.2%prior 13

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 majority of crashes in both 2023 (64.8%) and 2022 (62.5%) occurred in clear weather. There was a notable decrease in the number of crashes happening under adverse conditions. Collisions on wet, icy, or snowy roads fell from 178 in 2022 to 149 in 2023. Similarly, crashes during rain, snow, or freezing rain dropped from 80 incidents to 53 over the same period.

Weather

Clear498 (72.5%)
↓-2.2%prior 509
Cloudy127 (18.5%)
↓-3.8%prior 132
Rain26 (3.8%)
↑44.4%prior 18
Snow17 (2.5%)
↓-46.9%prior 32
Fog, smoke, smog6 (0.9%)
Freezing rain/drizzle5 (0.7%)
↓-50.0%prior 10
Blowing Snow5 (0.7%)
↓-75.0%prior 20
Other (explain in narrative)2 (0.3%)
Severe Winds1 (0.1%)

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

Lighting

Daylight455 (66.1%)
↓-6.0%prior 484
Dark - roadway lighted98 (14.2%)
↓-10.9%prior 110
Dark - roadway not lighted86 (12.5%)
↓-6.5%prior 92
Dusk23 (3.3%)
↑35.3%prior 17
Dawn17 (2.5%)
↑41.7%prior 12
Dark - unknown roadway lighting9 (1.3%)
↑50.0%prior 6

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

Road Surface

Dry530 (76.9%)
↓-0.4%prior 532
Wet69 (10.0%)
↑43.8%prior 48
Ice/frost45 (6.5%)
↓-23.7%prior 59
Snow32 (4.6%)
↓-50.8%prior 65
Gravel10 (1.5%)
↓-16.7%prior 12
Slush3 (0.4%)
↓-50.0%prior 6

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Chevrolet, Ford, and Dodge vehicles topping the list in both 2022 and 2023. Analysis of persons involved in crashes reveals a notable demographic shift, with the number of individuals in the 16-20 age group increasing from 207 to 259 year-over-year. In contrast, involvement decreased for most other age groups, particularly for those aged 45-54, which saw a drop from 199 to 139 individuals.

Top Vehicle Makes (1,321 vehicles)

1
CHEV230 (17.4%)
↓-9.4%prior 254
2
FORD187 (14.2%)
↓-5.1%prior 197
3
DODG79 (6%)
↓-4.8%prior 83
4
GMC67 (5.1%)
↓-5.6%prior 71
5
JEEP63 (4.8%)
↓-4.5%prior 66
6
NR59 (4.5%)
↓-19.2%prior 73
7
CHRY57 (4.3%)
↑16.3%prior 49
8
BUIC55 (4.2%)
↑14.6%prior 48
9
TOYO55 (4.2%)
↓-6.8%prior 59
10
TOYT46 (3.5%)
↑35.3%prior 34

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

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

Sex Distribution (1,113 persons with recorded sex)

Male612 (55.0%)
↓-1.9%prior 624
Female501 (45.0%)
↓-9.6%prior 554

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: 768
  • Total persons involved: 1,773
  • Total vehicles involved: 1,321

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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