ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · IOWA, IA · 2017
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/iowa/statewide/2017-annual-report
Yearly Traffic Safety Analysis
910 CRASHES IN
IOWA, IA
2017
In Webster County, the total number of crashes remained unchanged year-over-year, with 910 incidents recorded in both 2017 and 2016. While the number of fatalities decreased from 6 to 5, the total number of people injured increased by 26.2%, rising from 225 in 2016 to 284 in 2017. This increase in injuries, despite a stable crash volume, represents the most significant trend in the data.
910
Total Crash Events
5
▼ -16.7%was 6
Persons Killed
284
▲ 26.2%was 225
Persons Injured
4
▼ -33.3%was 6
Fatal Crash Events
Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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, the total volume of traffic crashes in Webster County was stable between 2016 and 2017, with 910 incidents reported in each period. While the total number of crashes did not change, the number of people injured in these incidents increased by 26.2%, from 225 to 284. Concurrently, the number of fatalities saw a slight decrease from 6 to 5.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
5
Motorists Killed
0
Other Killed
8
Pedestrians Injured
7
Cyclists Injured
268
Motorists Injured
1
Other Injured
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 remained largely consistent year-over-year. The peak day for crashes in both 2017 and 2016 was Friday, with 167 and 159 incidents, respectively. Similarly, the 3 p.m. hour was the peak time for crashes in both periods, recording 83 crashes in 2017 and 82 in 2016. While the overall daily and hourly distributions were similar, crashes on Tuesdays increased from 133 to 152, while Saturday crashes decreased from 143 to 118.
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
The severity of crashes shifted year-over-year, with a notable increase in injury-producing incidents. The number of fatal crashes decreased from 6 in 2016 to 4 in 2017, lowering the fatal crash rate from 0.66 to 0.44 per 100 crashes. Conversely, the total number of crashes resulting in an injury rose from 210 to 246. This was driven by increases across all injury categories, with serious injury crashes rising from 18 to 20, minor injury crashes from 60 to 70, and possible injury crashes from 132 to 156.
Severity is per crash event (most severe injury). 4 fatal crash events resulted in 5 persons killed.
Outcome by Severity (Crash Events)
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
The leading contributing factors for crashes saw notable shifts between 2016 and 2017. While collisions involving an 'Animal' were the top factor in 2016 with 109 crashes, this number decreased to 84 crashes in 2017, moving it to the second-ranked cause. The category 'Other (explain in narrative): Other' saw a significant increase in count, rising from 82 crashes to become the leading factor in 2017 with 122 crashes. Crashes attributed to 'Driving too fast for conditions' also increased from 50 to 58 incidents, while those due to 'FTYROW: From stop sign' decreased from 61 to 50.
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of environmental conditions at the time of crashes remained broadly stable year-over-year, with most incidents in both periods occurring in daylight and on dry roads. There was a slight increase in the proportion of crashes occurring on dry road surfaces, which rose from 61.0% of all crashes in 2016 to 64.6% in 2017. Correspondingly, the share of crashes on wet, snowy, or icy roads saw minor decreases. The proportions of crashes by lighting and weather conditions showed minimal change between the two periods.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes were consistent across both periods, with Ford and Chevrolet remaining the most common. In 2017, there were 234 Fords and a combined 330 Chevrolet vehicles involved, compared to 232 Fords and 349 Chevrolets in 2016. Analysis of persons involved in crashes shows a shift in age demographics; the number of individuals aged 65 and older increased from 177 to 215, while the number of persons aged 16-20 decreased from 271 to 236. The number of males involved in crashes decreased from 620 to 585, while the number of females remained stable.
Top Vehicle Makes (1,595 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Vehicle unit records
400 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,115 persons with recorded sex)
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: 910
- Total persons involved: 1,865
- Total vehicles involved: 1,595
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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Iowa Crash Data · ArcGIS
Period: 2017-01-01 – 2017-12-31
Generated: September 9, 2026 · All rights reserved