Yearly Traffic Safety Analysis

312 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Tama County recorded 312 total crashes, a slight decrease from 314 crashes in 2022. The most notable year-over-year shift was a significant improvement in crash outcomes, with total fatalities dropping from two to zero and total injuries decreasing by 38.7% from 106 to 65.

312

▼ -0.6%was 314

Total Crash Events

0

▼ -100.0%was 2

Persons Killed

65

▼ -38.7%was 106

Persons Injured

0

▼ -100.0%was 2

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 crash volume in Tama County remained stable, with a minor decrease of two incidents from 314 in 2022 to 312 in 2023. While the total number of crashes was nearly unchanged, the severity of these incidents decreased substantially. There were no fatal crashes in 2023, compared to two in the prior year, and the number of people injured fell from 106 to 65.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 2↓-100.0%

65

Motorists Injured

Prior: 104↓-37.5%

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

Temporal crash patterns shifted between the two periods. The peak day for crashes moved from Thursday (62 crashes) in 2022 to Friday (52 crashes) in 2023. The peak hour also shifted earlier, from 9 p.m. in the prior year (26 crashes) to 6 p.m. in the current year (29 crashes). The month with the highest crash frequency changed from June in 2022 to November in 2023.

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 decreased significantly in 2023 compared to 2022. Fatal crashes were eliminated, dropping from two incidents in 2022 to zero in 2023. The proportion of crashes resulting in serious injuries fell from 4.1% to 2.6%, and minor injury crashes decreased from 11.8% to 5.1% of the total. Consequently, the share of crashes involving no injuries increased from 73.9% in 2022 to 83.3% in 2023.

Outcome by Severity (Crash Events)

Serious Injury8serious injury crashes2.6%
↓-38.5%prior 13
Minor Injury16minor injury crashes5.1%
↓-56.8%prior 37
Possible Injury28possible injury crashes9%
↓-6.7%prior 30
No Injury260no injury crashes83.3%
↑12.1%prior 232

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 leading contributing factor in both periods, with the count increasing by 13.3% from 135 incidents in 2022 to 153 in 2023. This factor's share of all crashes grew from 43% to 49%. In contrast, crashes attributed to 'Driver Distraction: Other interior distraction' decreased from 14 to 8. 'Lost Control' remained a top factor with a nearly stable count, dropping from 18 to 17 crashes year-over-year.

Officer-Reported Primary Contributing Cause

Animal153 (49%)↑13.3%prior 135
Other (explain in narrative): Other17 (5.4%)↑54.5%prior 11
Lost Control17 (5.4%)↓-5.6%prior 18
Driving too fast for conditions12 (3.8%)→0.0%prior 12
Ran Stop Sign11 (3.5%)↑37.5%prior 8
FTYROW: From stop sign11 (3.5%)→0.0%prior 11
Ran off road - straight10 (3.2%)↓-9.1%prior 11
Followed too close8 (2.6%)→0.0%prior 8
Driver Distraction: Other interior distraction8 (2.6%)↓-42.9%prior 14
Operating vehicle in an reckless, erratic, careless, negligent manner7 (2.2%)↓-22.2%prior 9

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

Road & Environmental Conditions

Year-over-year, there was a shift in the conditions under which crashes occurred. The number of crashes in clear weather decreased from 141 in 2022 to 102 in 2023, while incidents in cloudy conditions rose from 30 to 48. Crashes on dry road surfaces also saw a reduction, falling from 147 to 120. Incidents during daylight hours dropped from 127 to 106, while crashes in dark, unlighted conditions remained relatively stable at 38, compared to 39 in the previous year.

Weather

Clear102 (60.7%)
↓-27.7%prior 141
Cloudy48 (28.6%)
↑60.0%prior 30
Fog, smoke, smog6 (3.6%)
Snow6 (3.6%)
→0.0%prior 6
Rain4 (2.4%)
↓-33.3%prior 6
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

Daylight106 (63.1%)
↓-16.5%prior 127
Dark - roadway not lighted38 (22.6%)
↓-2.6%prior 39
Dark - roadway lighted12 (7.1%)
↓-7.7%prior 13
Dusk6 (3.6%)
↓-40.0%prior 10
Dawn5 (3.0%)
↓-37.5%prior 8
Dark - unknown roadway lighting1 (0.6%)

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

Road Surface

Dry120 (70.6%)
↓-18.4%prior 147
Wet16 (9.4%)
↑23.1%prior 13
Gravel11 (6.5%)
↓-26.7%prior 15
Ice/frost11 (6.5%)
↓-26.7%prior 15
Snow7 (4.1%)
↓-36.4%prior 11
Slush3 (1.8%)
Other (explain in narrative)1 (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

The primary vehicle makes involved in crashes, Chevrolet and Ford, remained consistent in rank and volume between 2022 and 2023. The total number of vehicles involved in crashes saw a slight decrease from 421 to 406. The age demographics of persons involved were also stable, with the 26-34 age group being the most represented in both years, showing a slight increase from 106 to 116 individuals.

Top Vehicle Makes (406 vehicles)

1
CHEV78 (19.2%)
↓-2.5%prior 80
2
FORD75 (18.5%)
↓-1.3%prior 76
3
DODG21 (5.2%)
↑40.0%prior 15
4
TOYT20 (4.9%)
↓-9.1%prior 22
5
CHEVROLET20 (4.9%)
↑17.6%prior 17
6
NISS16 (3.9%)
↑77.8%prior 9
7
GMC16 (3.9%)
↑33.3%prior 12
8
JEEP14 (3.4%)
↓-12.5%prior 16
9
RAM13 (3.2%)
10
KIA12 (3%)
→0.0%prior 12

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

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

Sex Distribution (378 persons with recorded sex)

Male240 (63.5%)
↓-2.0%prior 245
Female138 (36.5%)
↓-4.2%prior 144

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: 312
  • Total persons involved: 634
  • Total vehicles involved: 406

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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