Yearly Traffic Safety Analysis

147 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Sac County, total traffic crashes decreased by 7.5%, from 159 in 2020 to 147 in 2021. This downward trend was accompanied by a 12.2% reduction in total injuries, which fell from 49 to 43, while fatalities remained unchanged at one death in each year. The most notable shift in crash characteristics was a decrease in minor injury crashes and a corresponding increase in possible injury crashes.

147

▼ -7.5%was 159

Total Crash Events

1

Persons Killed

43

▼ -12.2%was 49

Persons Injured

1

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 · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Sac County showed improvement from 2020 to 2021. The total number of crashes declined by 7.5% from 159 to 147. Similarly, the number of people injured in these incidents decreased by 12.2% from 49 to 43, while the number of fatalities held steady at one for both years.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 1→0.0%

43

Motorists Injured

Prior: 48↓-10.4%

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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. While Friday remained the most frequent day for crashes in both 2021 (25 crashes) and 2020 (30 crashes), the peak hour for incidents moved two hours earlier, from 9 p.m. in 2020 (12 crashes) to 7 p.m. in 2021 (14 crashes). Crash volumes on Friday and Saturday saw the largest day-of-week decreases, falling by 5 incidents each.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted between 2020 and 2021, though the number of fatal crashes remained constant at one incident in each year. The count of serious injury crashes decreased from 3 to 2, and minor injury crashes dropped from 23 to 13. Conversely, crashes resulting in possible injuries increased from 12 in 2020 to 19 in 2021. Crashes with no injuries accounted for 76.2% of all incidents in 2021, a slight increase in share from 75.5% in the prior year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.7%
→0.0%prior 1
Serious Injury2serious injury crashes1.4%
↓-33.3%prior 3
Minor Injury13minor injury crashes8.8%
↓-43.5%prior 23
Possible Injury19possible injury crashes12.9%
↑58.3%prior 12
No Injury112no injury crashes76.2%
↓-6.7%prior 120

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the leading contributing factor in both years, though the count decreased slightly from 52 in 2020 to 50 in 2021. Significant changes were observed in other factors; crashes attributed to "Ran off road - straight" fell by 54.5% (from 11 to 5), and those involving "Driving too fast for conditions" dropped by 62.5% (from 8 to 3). In contrast, incidents involving "Driver Distraction: Other interior distraction" doubled in count from 4 to 8.

Officer-Reported Primary Contributing Cause

Animal50 (34%)↓-3.8%prior 52
Other (explain in narrative): Other14 (9.5%)↑180.0%prior 5
Lost Control13 (8.8%)↑18.2%prior 11
Driver Distraction: Other interior distraction8 (5.4%)
FTYROW: From stop sign8 (5.4%)↑14.3%prior 7
Ran off road - left8 (5.4%)↑33.3%prior 6
Ran off road - straight5 (3.4%)↓-54.5%prior 11
FTYROW: From yield sign4 (2.7%)
Followed too close3 (2%)↓-62.5%prior 8
Driving too fast for conditions3 (2%)↓-62.5%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions varied year-over-year, with a lower proportion of incidents occurring in clear weather (51.7% in 2021 vs. 67.9% in 2020). Correspondingly, the share of crashes in cloudy weather and rain increased. Crashes on wet road surfaces more than doubled, from 5 in 2020 to 13 in 2021. There was also a notable decrease in crashes occurring in darkness on unlighted roadways, which fell from 44 incidents to 32.

Weather

Clear76 (67.3%)
↓-29.6%prior 108
Cloudy22 (19.5%)
↑69.2%prior 13
Rain7 (6.2%)
Freezing rain/drizzle2 (1.8%)
↓-60.0%prior 5
Fog, smoke, smog2 (1.8%)
Snow2 (1.8%)
↓-60.0%prior 5
Severe Winds1 (0.9%)
Blowing Snow1 (0.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight66 (57.4%)
↓-9.6%prior 73
Dark - roadway not lighted32 (27.8%)
↓-27.3%prior 44
Dark - roadway lighted10 (8.7%)
↓-23.1%prior 13
Dawn4 (3.5%)
↓-20.0%prior 5
Dusk3 (2.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry82 (71.3%)
↓-18.0%prior 100
Wet13 (11.3%)
↑160.0%prior 5
Ice/frost11 (9.6%)
↓-8.3%prior 12
Gravel5 (4.3%)
↓-58.3%prior 12
Snow3 (2.6%)
↓-50.0%prior 6
Mud, dirt1 (0.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet models being the most frequent in both 2021 and 2020. Analysis of the age of persons involved in crashes reveals a significant shift in demographic representation. The share of persons aged 65 and older increased from 11.3% of the total in 2020 to 17.7% in 2021. Conversely, the involvement of individuals in the 35-44 and 45-54 age groups saw a proportional decrease.

Top Vehicle Makes (203 vehicles)

1
FORD36 (17.7%)
↓-10.0%prior 40
2
CHEV30 (14.8%)
↓-21.1%prior 38
3
CHEVROLET21 (10.3%)
→0.0%prior 21
4
GMC12 (5.9%)
↑100.0%prior 6
5
DODG9 (4.4%)
→0.0%prior 9
6
BUIC6 (3%)
7
JEEP6 (3%)
↑20.0%prior 5
8
DODGE6 (3%)
↓-25.0%prior 8
9
CHRYSLER6 (3%)
10
HOND5 (2.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

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

Sex Distribution (166 persons with recorded sex)

Male90 (54.2%)
↓-29.7%prior 128
Female76 (45.8%)
↓-7.3%prior 82

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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: 2021-01-01 through 2021-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 147
  • Total persons involved: 260
  • Total vehicles involved: 203

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: 2021." Published September 9, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2021-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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