Yearly Traffic Safety Analysis

163 CRASHES IN
IOWA, IA
2017

All metrics benchmarked against2016

In Wright County, total crashes fell from 211 in 2016 to 163 in 2017, a 22.7% decrease. While overall crashes and injuries declined, the most notable shift was the registration of one fatal crash in 2017, whereas none occurred in the prior year. This decline in total incidents was accompanied by a drop in injuries from 51 to 45.

163

▼ -22.7%was 211

Total Crash Events

1

Persons Killed

45

▼ -11.8%was 51

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 · 2017-01-01 to 2017-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Wright County show a notable decrease year-over-year. Total collisions dropped by 22.7%, from 211 in 2016 to 163 in 2017. Correspondingly, the number of people injured fell by 11.8% from 51 to 45, though one fatality was recorded in 2017 compared to zero in 2016.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0→%

45

Motorists Injured

Prior: 50↓-10.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · 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 minor shifts between the two periods. The peak day for crashes moved from Wednesday, with 36 incidents in 2016, to Monday, with 34 incidents in 2017. The peak hour also shifted slightly later, from the 5 p.m. hour (18 crashes) in 2016 to the 6 p.m. hour (15 crashes) in 2017.

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

In 2017, Wright County recorded one fatal crash, which accounted for 0.6% of all incidents, a category absent in 2016. The number of serious injury crashes remained constant at six in both years, though their share of total crashes increased from 2.8% to 3.7% due to the lower overall crash volume in 2017. Crashes resulting in possible injuries saw a notable decline from 24 in 2016 to 15 in 2017.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
Serious Injury6serious injury crashes3.7%
→0.0%prior 6
Minor Injury14minor injury crashes8.6%
↓-12.5%prior 16
Possible Injury15possible injury crashes9.2%
↓-37.5%prior 24
No Injury127no injury crashes77.9%
↓-23.0%prior 165

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both years, though the count decreased from 43 incidents in 2016 to 30 in 2017. The count for crashes attributed to "Lost Control" was nearly stable, changing from 22 to 21 incidents. A notable increase was seen in the "Other (explain in narrative): Other" category, which grew from 14 incidents in 2016 to 25 in 2017.

Officer-Reported Primary Contributing Cause

Animal30 (18.4%)↓-30.2%prior 43
Other (explain in narrative): Other25 (15.3%)↑78.6%prior 14
Lost Control21 (12.9%)↓-4.5%prior 22
Driving too fast for conditions11 (6.7%)↓-15.4%prior 13
FTYROW: From stop sign8 (4.9%)↑14.3%prior 7
Ran off road - left7 (4.3%)↑16.7%prior 6
FTYROW: Other (explain in narrative)6 (3.7%)
FTYROW: At uncontrolled intersection6 (3.7%)↑20.0%prior 5
Driver Distraction: Other interior distraction5 (3.1%)↓-50.0%prior 10
Ran off road - straight4 (2.5%)↓-63.6%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a marked decrease in crashes occurring during adverse conditions year-over-year. Crashes on roads with snow or ice/frost dropped from a combined 42 incidents in 2016 to 20 in 2017. Similarly, crashes reported during snowy weather fell from 16 in 2016 to 4 in 2017, indicating a significant reduction in incidents under these specific conditions.

Weather

Clear87 (64.9%)
↓-18.7%prior 107
Cloudy26 (19.4%)
↓-10.3%prior 29
Rain5 (3.7%)
↓-37.5%prior 8
Snow4 (3.0%)
↓-75.0%prior 16
Fog, smoke, smog3 (2.2%)
Other (explain in narrative)3 (2.2%)
Blowing Snow2 (1.5%)
Freezing rain/drizzle2 (1.5%)
Severe Winds2 (1.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Weather condition at time of crash

Lighting

Daylight88 (66.7%)
↓-26.7%prior 120
Dark - roadway not lighted22 (16.7%)
↓-21.4%prior 28
Dark - roadway lighted16 (12.1%)
↑23.1%prior 13
Dawn3 (2.3%)
↓-40.0%prior 5
Dusk2 (1.5%)
↓-60.0%prior 5
Dark - unknown roadway lighting1 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Lighting condition field

Road Surface

Dry93 (68.9%)
↓-8.8%prior 102
Wet16 (11.9%)
→0.0%prior 16
Ice/frost15 (11.1%)
↓-37.5%prior 24
Gravel5 (3.7%)
↓-44.4%prior 9
Snow5 (3.7%)
↓-72.2%prior 18
Slush1 (0.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet were the most common vehicle makes involved in crashes in both periods, and their involvement counts decreased in line with the overall drop in total crashes. The demographic data of persons involved shows a significant year-over-year reduction for older age groups. The combined count of persons in the 45-54, 55-64, and 65+ age brackets fell from 141 in 2016 to 77 in 2017.

Top Vehicle Makes (244 vehicles)

1
FORD43 (17.6%)
↓-23.2%prior 56
2
CHEVROLET29 (11.9%)
↓-19.4%prior 36
3
CHEV22 (9%)
↓-15.4%prior 26
4
DODG14 (5.7%)
↑40.0%prior 10
5
TOYT13 (5.3%)
↑62.5%prior 8
6
PONT9 (3.7%)
↑12.5%prior 8
7
CHRYSLER8 (3.3%)
↑60.0%prior 5
8
NR8 (3.3%)
↑33.3%prior 6
9
CHRY8 (3.3%)
↓-20.0%prior 10
10
DODGE7 (2.9%)
↓-53.3%prior 15

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Vehicle unit records

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

Sex Distribution (160 persons with recorded sex)

Male96 (60.0%)
↓-35.6%prior 149
Female64 (40.0%)
↓-19.0%prior 79

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · 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: 2017-01-01 through 2017-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2017-01-01 through 2017-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 163
  • Total persons involved: 282
  • Total vehicles involved: 244

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: 2017." Published September 9, 2026. Reporting period: 2017-01-01 to 2017-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2017-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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