Yearly Traffic Safety Analysis

125 CRASHES IN
IOWA, IA
2015

In 2015, Sac County recorded 125 traffic crashes, resulting in 1 fatality and 49 injuries. The single most prominent contributing factor was collisions involving animals, which accounted for 32 crashes, representing 25.6% of all incidents during this period.

125

Total Crash Events

1

Persons Killed

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 · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

All killed or seriously injured persons were vehicle motorists. In total, 1 motorist was killed and 49 were injured in crashes during this period. There were no fatalities or injuries involving pedestrians or cyclists recorded in the data.

1

Motorists Killed

49

Motorists Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crashes occurred most frequently on Fridays, with 23 incidents, and the peak time for collisions was the 6 p.m. hour, which saw 10 crashes. A majority of incidents, 70 crashes or 56%, happened during daylight hours. Crashes in darkness occurred in 22 instances, while 8 crashes took place during dawn or dusk.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

A majority of crashes, 85 out of 125 (68%), resulted in no injuries and were classified as property-damage-only. The remaining 40 crashes involved injuries or a fatality. There was one fatal crash recorded during this period, which resulted in one person's death.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.8%
Serious Injury6serious injury crashes4.8%
Minor Injury18minor injury crashes14.4%
Possible Injury15possible injury crashes12%
No Injury85no injury crashes68%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor identified in crashes was an animal, cited in 32 incidents (25.6%). The next most common factors were drivers losing control (11 crashes, 8.8%), running off a straight road (7 crashes, 5.6%), and failure to yield the right-of-way from a stop sign (7 crashes, 5.6%).

Officer-Reported Primary Contributing Cause

Animal32 (25.6%)
Lost Control11 (8.8%)
Other (explain in narrative): Other9 (7.2%)
Ran off road - straight7 (5.6%)
FTYROW: From stop sign7 (5.6%)
Followed too close6 (4.8%)
Driving too fast for conditions6 (4.8%)
Other (explain in narrative): No improper action5 (4%)
Driver Distraction: Other interior distraction4 (3.2%)
FTYROW: From yield sign4 (3.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A majority of crashes occurred in favorable conditions, with 56.8% (71 crashes) happening in clear weather and 50.4% (63 crashes) on dry road surfaces. Daylight conditions were present for 70 of the 125 total crashes (56%). Adverse road surface conditions such as ice, snow, or slush were noted in a combined 18 incidents.

Weather

Clear71 (70.3%)
Cloudy12 (11.9%)
Rain8 (7.9%)
Snow5 (5.0%)
Blowing Snow3 (3.0%)
Freezing rain/drizzle1 (1.0%)
Severe Winds1 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash

Lighting

Daylight70 (70.0%)
Dark - roadway not lighted17 (17.0%)
Dawn6 (6.0%)
Dark - roadway lighted5 (5.0%)
Dusk2 (2.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field

Road Surface

Dry63 (62.4%)
Ice/frost11 (10.9%)
Wet10 (9.9%)
Gravel7 (6.9%)
Snow5 (5.0%)
Other (explain in narrative)2 (2.0%)
Slush2 (2.0%)
Mud, dirt1 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field

Vehicles & Demographics

Individuals in the 65 and older age group were the most frequently involved demographic in crashes, with 43 persons recorded. The most common vehicle makes involved in collisions were Ford with 32 vehicles, CHEV with 23 vehicles, and both GMC and CHEVROLET with 16 vehicles each.

Top Vehicle Makes (187 vehicles)

1
FORD32 (17.1%)
2
CHEV23 (12.3%)
3
GMC16 (8.6%)
4
CHEVROLET16 (8.6%)
5
DODG9 (4.8%)
6
BUIC9 (4.8%)
7
DODGE7 (3.7%)
8
JEEP7 (3.7%)
9
PONT6 (3.2%)
10
FREIGHTLINER5 (2.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

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

Sex Distribution (173 persons with recorded sex)

Male91 (52.6%)
Female82 (47.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Major Cause

The most frequently recorded major cause of crashes was an animal, accounting for 32 incidents (25.6%). This was followed by a driver losing control, which was cited in 11 crashes (8.8%). Failure to yield from a stop sign and running off a straight road were each listed as the major cause for 7 crashes.

Major Cause

1
Animal32 (26.4%)
2
Lost Control11 (9.1%)
3
Other (explain in narrative): Other9 (7.4%)
4
Ran off road - straight7 (5.8%)
5
FTYROW: From stop sign7 (5.8%)
6
Followed too close6 (5%)
7
Driving too fast for conditions6 (5%)
8
Other (explain in narrative): No improper action5 (4.1%)
9
Driver Distraction: Other interior distraction4 (3.3%)

Showing top 9 of 29 reported. 20 additional (34 total) not shown: FTYROW: From yield sign, Improper Backing, Operating vehicle in an reckless, erratic, careless, negligent manner, FTYROW: Making left turn, Swerving/Evasive Action, Driver Distraction: Exterior distraction, Driver Distraction: Adjusting devices (radio, climate), Exceeded authorized speed, Other (explain in narrative): Vision obstructed, Passing: On wrong side, Passing: With insufficient distance/inadequate visibility, Ran Stop Sign, FTYROW: At uncontrolled intersection, Failed to keep in proper lane, FTYROW: From driveway, FTYROW: Other (explain in narrative), Made improper turn, Other (explain in narrative): Disregarded signs/road markings, Equipment failure, Driver Distraction: Other electronic device activity.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

First Harmful Event

The most common first harmful event was a collision with another vehicle in traffic, which occurred in 51 crashes. The second most frequent event was a collision with an animal, recorded in 32 incidents. An overturn or rollover was the first harmful event in 10 crashes.

First Harmful Event

1
Collision with: Vehicle in traffic51 (41.1%)
2
Collision with: Animal32 (25.8%)
3
Non-collision events: Overturn/rollover10 (8.1%)
4
Collision with fixed object: Ditch8 (6.5%)
5
Collision with: Parked motor vehicle3 (2.4%)
6
Collision with fixed object: Bridge/bridge rail parapet3 (2.4%)
7
Collision with: Struck/struck by object/cargo/person from other vehicle3 (2.4%)
8
Collision with fixed object: Ground2 (1.6%)
9
Collision with fixed object: Tree2 (1.6%)

Showing top 9 of 18 reported. 9 additional (10 total) not shown: Other (explain in narrative), Non-collision events: Jackknife, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Building, Non-collision events: Vehicle went airborne, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Mailbox, Collision with: Re-entering roadway, Collision with fixed object: Fence.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Junction / Feature

The majority of crashes, 58 in total, occurred on non-intersection road segments. Intersection-related crashes accounted for 32 incidents, of which 20 were at four-way intersections and 7 were at T-intersections.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature58 (57.4%)
2
Intersection: Four-way intersection20 (19.8%)
3
Intersection: T-intersection7 (6.9%)
4
Intersection: Other intersection (explain in narrative)5 (5%)
5
Non-intersection: Driveway access (related, not in)3 (3%)
6
Non-intersection: Driveway access (within)3 (3%)
7
Interchange-related: Off-ramp2 (2%)
8
Non-intersection: Other non-intersection (explain in narrative)2 (2%)
9
Non-intersection: Crossover-related1 (1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most prevalent vehicle type involved in crashes, with 70 vehicles recorded. Four-tire light trucks or pickups were the next most common with 48 vehicles, followed by sport utility vehicles with 33. There were 12 tractor/semi-trailers and 3 motorcycles involved in crashes.

Vehicle Type

"Other" combines 6 smaller categories (6 records): Truck/trailer (1), Farm tractor (1), Other (explain in narrative) (1), School bus (seats > 15) (1), Single-unit truck (>= 3 axles) (1), All-terrain vehicle (ATV) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Traffic Control Device

For a large number of vehicles involved in collisions, no traffic controls were present, with 130 such instances documented. Where traffic controls were noted, stop signs were the most common, being a factor for 17 vehicles. Traffic signals were present for 3 vehicles involved in crashes.

Traffic Control Device

"Other" combines 1 smaller categories (1 records): Work zone sign (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Most Damaged Area

The front of the vehicle was the most common point of initial impact, with 39 vehicles sustaining primary damage there. Rear damage, indicative of rear-end collisions, was the most severe damage for 17 vehicles. Combined, front-corner impacts on the driver and passenger sides were recorded for 26 vehicles.

Most Damaged Area

"Other" combines 9 smaller categories (46 records): Other (explain in narrative) (9), Driver side - front (6), Driver side - rear (6), Passenger side - middle (6), Top (6), Passenger side - rear (5), Non-collision/no damage (4), Rear - passenger side corner (3), Undercarriage (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Crashes by City

Within city limits, Sac City had the highest crash volume with 18 incidents recorded. Lake View followed with 13 crashes, and Odebolt recorded 6 crashes during the period.

Crashes by City

1
SAC CITY18 (35.3%)
2
LAKE VIEW13 (25.5%)
3
ODEBOLT6 (11.8%)
4
AUBURN5 (9.8%)
5
SCHALLER4 (7.8%)
6
EARLY3 (5.9%)
7
WALL LAKE2 (3.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Paved vs Unpaved Road

The vast majority of crashes, 109 incidents, occurred on paved roadways. Crashes on unpaved surfaces like gravel or dirt accounted for 15 incidents, representing 12.1% of crashes where this information was recorded.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Contributing Factor

In cases where a roadway factor was identified as a contributor, surface conditions such as wet or icy pavement were the most common, cited in 20 crashes. A work zone was noted as a contributing roadway factor in one crash.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)20 (95.2%)
2
Work Zone (roadway-related)1 (4.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Property Damage

The most frequent officer-estimated property damage cost fell within the $1,500 to $7,500 range, accounting for 93 crashes. An additional 31 crashes resulted in damages estimated between $7,500 and $25,000, while one crash had damage exceeding $25,000.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Manner of Collision

Nearly half of all incidents were single-vehicle, non-collision events, accounting for 59 crashes (47.2%). The most common type of multi-vehicle crash was a rear-end collision, with 19 incidents (15.2%), followed by broadside collisions with 15 incidents (12%).

Manner of Collision

"Other" combines 3 smaller categories (4 records): Angle, oncoming left turn (2), Head-on (front to front) (1), Rear to rear (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Pre-Crash Driver Action

The most common action by drivers immediately before a crash was moving straight ahead, which was recorded for 114 vehicles. Turning left was the next most frequent pre-crash action with 15 vehicles, followed by slowing or stopping for 8 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight114 (65.9%)
2
Turning left15 (8.7%)
3
Slowing/stopping (deceleration)8 (4.6%)
4
Turning right7 (4%)
5
Backing6 (3.5%)
6
Stopped in traffic5 (2.9%)
7
Negotiating a curve5 (2.9%)
8
Overtaking/passing4 (2.3%)
9
Legally Parked4 (2.3%)

Showing top 9 of 13 reported. 4 additional (5 total) not shown: Other (explain in narrative), Illegally Parked/Unattended, Entering a parked position, Leaving traffic lane.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Person Type

Of the 239 individuals involved in crashes, the vast majority were drivers, accounting for 233 people. The remaining 6 individuals were recorded as passengers.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Person Injury Severity

Across all persons involved in crashes, 1 individual sustained a fatal injury. An additional 49 people were injured, including 6 with serious injuries, 21 with minor injuries, and 22 with possible injuries.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Occupant Safety Equipment

Among the 45 vehicle occupants for whom safety equipment use was documented, 40 were reported to have used a shoulder and lap belt. One occupant was recorded as not using any safety equipment.

Occupant Safety Equipment

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Vehicles Per Crash

Single-vehicle crashes were the most common incident type, comprising 67 of the 125 total crashes (53.6%). Two-vehicle collisions were also frequent, with 54 incidents. There were 4 crashes that involved three vehicles.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

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: 2015-01-01 through 2015-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-01-01 through 2015-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 125
  • Total persons involved: 239
  • Total vehicles involved: 187

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: 2015." Published September 9, 2026. Reporting period: 2015-01-01 to 2015-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2015-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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