ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · IPSWICH, MA · 2025
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/massachusetts/ipswich/2025-annual-report
Yearly Traffic Safety Analysis
135 CRASHES IN
IPSWICH, MA
2025
In 2025, Ipswich recorded 135 total traffic crashes, a 25% decrease from the 180 crashes reported in 2024. This decline was accompanied by a significant 61.5% reduction in total injuries, which fell from 52 to 20. The most notable shift in contributing factors was a 71% drop in crashes attributed to inattention, which decreased from 42 incidents in 2024 to 12 in 2025.
135
▼ -25.0%was 180
Total Crash Events
1
Persons Killed
20
▼ -61.5%was 52
Persons Injured
3
▼ -40.0%was 5
Hit-and-Run Crashes
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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends in Ipswich improved year-over-year. Total crashes fell by 25%, from 180 in 2024 to 135 in 2025. The number of people injured in these incidents saw a more substantial decline of 61.5%, dropping from 52 to 20, while the number of fatalities remained unchanged at one for both periods.
3
Hit-and-Run Crashes — 2025
▼ -40.0% vs prior (5)
The occurrence of hit-and-run crashes decreased from 2024 to 2025. The total count of hit-and-run incidents fell from 5 to 3. The hit-and-run rate, measured as a percentage of total crashes, also trended down, decreasing from 2.8 in 2024 to 2.2 in 2025.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
18
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Tuesday in both periods, though the number of incidents on that day decreased from 32 in 2024 to 25 in 2025. A notable shift occurred in the peak hour for collisions, which moved from the 4 p.m. hour in 2024 (20 crashes) to the 12 p.m. hour in 2025 (15 crashes). The pronounced afternoon peak seen in 2024 was less evident in 2025, which had a more evenly distributed pattern throughout the daytime hours.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the number of fatal crashes remained stable at one in both 2024 and 2025, the fatal crash rate per 100 crashes increased from 0.56 to 0.74 due to the lower total number of crashes in 2025. The proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) decreased from 21.2% of all crashes in 2024 to 12.6% in 2025. Correspondingly, crashes resulting in no injury rose from representing 73.3% of the total in 2024 to 83.7% in 2025.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading reported contributing factor in both years was 'No improper driving,' with 55 instances in 2025 and 60 in 2024. The most significant year-over-year change was the reduction in crashes attributed to 'Inattention,' which fell from 42 incidents in 2024 to 12 in 2025, a 71.4% decrease in count. Conversely, crashes involving 'Failed to yield right of way' increased in count from 5 to 9, an 80% increase, making it the third most common factor in 2025.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained broadly consistent between 2024 and 2025. In both periods, the vast majority of crashes occurred in daylight (72.2% in 2024 and 75.6% in 2025) and on dry roads (82.8% in 2024 and 82.2% in 2025). The proportion of crashes occurring during clear weather was also stable, accounting for 64.4% of crashes in 2024 and 60.0% in 2025, showing no significant shift toward or away from adverse-condition crashes.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes saw a shift at the top of the rankings, with Ford (37 vehicles) becoming the most common make in 2025, replacing Toyota (33 vehicles), which was the most common in 2024 with 46 vehicles. An analysis of persons involved in crashes shows the proportion of individuals in the 16-20 age group increased from 8.6% of the total in 2024 to 11.6% in 2025. Meanwhile, the share of persons aged 65 and older decreased slightly from 21.4% to 19.6%.
Top Vehicle Makes (209 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
16 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (229 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones was similar year-over-year, with the 25 mph zone accounting for the highest number of incidents in both 2024 (61 crashes) and 2025 (46 crashes). There was a notable decrease in crashes occurring in zones posted at 40 mph or higher, which fell from 57 incidents in 2024 to 34 in 2025. In both periods, the single fatal crash occurred in a 40 mph speed zone.
Fatal crashes by zone: 40 mph: 1 of 13 (7.692%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly 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_yearly 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: IPSWICH, MA
- Total crash records analyzed: 135
- Total persons involved: 250
- Total vehicles involved: 209
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). "IPSWICH, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/ipswich/2025-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: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved