Yearly Traffic Safety Analysis

183 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Emmet County recorded 183 total crashes, an 18.8% increase from the 154 crashes documented in 2022. While total crashes and injuries increased, the number of fatalities decreased from 3 in the prior year to 1 in the current year. The most significant year-over-year change was the 50% rise in total injuries, from 30 in 2022 to 45 in 2023.

183

▲ 18.8%was 154

Total Crash Events

1

▼ -66.7%was 3

Persons Killed

45

▲ 50.0%was 30

Persons Injured

1

▼ -66.7%was 3

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

Crash trends in Emmet County show an increase in overall volume from 2022 to 2023. Total crashes rose by 29 incidents (from 154 to 183), and the number of people injured increased by 50% (from 30 to 45). In contrast, the number of fatalities recorded decreased from 3 to 1 over the same period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 3↓-66.7%

2

Pedestrians Injured

Prior: 1↑100.0%

43

Motorists Injured

Prior: 28↑53.6%

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 between 2022 and 2023. In 2023, the highest number of crashes occurred on Tuesdays and Fridays (31 each), a change from 2022 when Wednesday was the peak day with 27 crashes. The peak hour for collisions also moved from the 7 a.m. hour in 2022 (16 crashes) to the 3 p.m. hour in 2023 (22 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

In 2023, there was a notable shift in crash severity compared to 2022. The number of fatal crashes decreased from 3 to 1, and the corresponding fatal crash rate fell from 1.95 to 0.55 per 100 crashes. Conversely, the count of crashes resulting in serious injuries increased from 1 in 2022 to 4 in 2023. The total number of crashes involving any level of injury rose from 33 to 40, consistent with the overall increase in crash volume.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.5%
↓-66.7%prior 3
Serious Injury4serious injury crashes2.2%
↑300.0%prior 1
Minor Injury15minor injury crashes8.2%
→0.0%prior 15
Possible Injury20possible injury crashes10.9%
↑42.9%prior 14
No Injury143no injury crashes78.1%
↑18.2%prior 121

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 periods, though the count decreased slightly from 44 crashes in 2022 to 42 in 2023. Several other factors saw significant year-over-year increases in crash counts: 'Lost Control' crashes rose from 9 to 16, 'Driving too fast for conditions' doubled from 7 to 14, and 'Followed too close' incidents increased from 1 to 12. Conversely, crashes involving 'Failure to yield from a stop sign' decreased in count from 10 to 7.

Officer-Reported Primary Contributing Cause

Animal42 (23%)↓-4.5%prior 44
Other (explain in narrative): Other19 (10.4%)↑58.3%prior 12
Lost Control16 (8.7%)↑77.8%prior 9
Driving too fast for conditions14 (7.7%)↑100.0%prior 7
Followed too close12 (6.6%)
FTYROW: From stop sign7 (3.8%)↓-30.0%prior 10
Operating vehicle in an reckless, erratic, careless, negligent manner6 (3.3%)
Made improper turn4 (2.2%)
Improper Backing4 (2.2%)
Driver Distraction: Other interior distraction4 (2.2%)↓-20.0%prior 5

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 and 2022 occurred in clear weather and on dry road surfaces. In 2023, 66.7% of crashes happened in clear weather, compared to 59.1% in 2022, while crashes on dry roads accounted for 63.9% of incidents versus 59.1% in the prior year. The distribution of crashes between daylight (58.5% in 2023) and dark or low-light conditions (25.1% in 2023) also remained largely consistent year-over-year.

Weather

Clear122 (76.3%)
↑34.1%prior 91
Cloudy17 (10.6%)
↑41.7%prior 12
Rain7 (4.4%)
Snow4 (2.5%)
↓-60.0%prior 10
Freezing rain/drizzle4 (2.5%)
Severe Winds2 (1.3%)
Fog, smoke, smog2 (1.3%)
Other (explain in narrative)1 (0.6%)
Blowing Snow1 (0.6%)

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

Lighting

Daylight107 (67.3%)
↑27.4%prior 84
Dark - roadway not lighted26 (16.4%)
↑36.8%prior 19
Dark - roadway lighted17 (10.7%)
↑30.8%prior 13
Dawn6 (3.8%)
Dusk3 (1.9%)

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

Road Surface

Dry117 (73.6%)
↑28.6%prior 91
Ice/frost16 (10.1%)
↑100.0%prior 8
Snow13 (8.2%)
→0.0%prior 13
Wet9 (5.7%)
↑80.0%prior 5
Slush3 (1.9%)
Gravel1 (0.6%)

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

Vehicles & Demographics

Chevrolet and Ford vehicles were the most frequently involved in crashes in both periods, with the number of Fords in crashes increasing from 26 in 2022 to 46 in 2023. Regarding the age of persons involved, the most significant change occurred in the 55-64 age group, which grew from 28 individuals in 2022 to 51 in 2023. The 16-20 age group remained one of the largest involved demographics, with 43 individuals in 2023 compared to 44 in 2022.

Top Vehicle Makes (276 vehicles)

1
CHEV49 (17.8%)
↑14.0%prior 43
2
FORD46 (16.7%)
↑76.9%prior 26
3
CHEVROLET17 (6.2%)
↑30.8%prior 13
4
GMC15 (5.4%)
↓-6.3%prior 16
5
JEEP14 (5.1%)
↑133.3%prior 6
6
NR11 (4%)
↑37.5%prior 8
7
DODG9 (3.3%)
↓-40.0%prior 15
8
CHRY8 (2.9%)
↓-11.1%prior 9
9
HOND8 (2.9%)
↑14.3%prior 7
10
TOYT8 (2.9%)
↑33.3%prior 6

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

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

Sex Distribution (238 persons with recorded sex)

Male142 (59.7%)
↑25.7%prior 113
Female96 (40.3%)
↑21.5%prior 79

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: 183
  • Total persons involved: 371
  • Total vehicles involved: 276

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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