ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SANDWICH, 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/sandwich/2025-annual-report
Yearly Traffic Safety Analysis
309 CRASHES IN
SANDWICH, MA
2025
In 2025, Sandwich recorded 309 total crashes, a 13.7% decrease from the 358 crashes reported in 2024. The total number of injuries also declined from 86 to 77, while fatalities remained at zero for both years. A notable change was the significant reduction in rear-end collisions, which fell from 122 incidents in 2024 to 91 in 2025.
309
▼ -13.7%was 358
Total Crash Events
0
Persons Killed
77
▼ -10.5%was 86
Persons Injured
16
▼ -11.1%was 18
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 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 crashes in Sandwich showed a downward trend year-over-year. Total collisions decreased by 13.7%, from 358 in 2024 to 309 in 2025. This decline was accompanied by a 10.5% drop in total injuries, which fell from 86 to 77, while no fatal crashes were recorded in either period.
16
Hit-and-Run Crashes — 2025
▼ -11.1% vs prior (18)
The total number of hit-and-run crashes decreased slightly from 18 in 2024 to 16 in 2025. Despite this drop in the absolute count, the hit-and-run rate as a proportion of all crashes saw a marginal increase. The rate rose from 5.0% in 2024 to 5.2% in 2025, due to the larger overall decrease in total collisions.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
76
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 temporal patterns of crashes shifted between the two periods. In 2025, the peak day for crashes was Monday with 55 incidents, a change from 2024 when Friday was the peak day with 62 crashes. Similarly, the peak hour for collisions moved from 4 p.m. in 2024 (39 crashes) to 3 p.m. in 2025 (30 crashes).
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
No fatal crashes were recorded in either 2025 or 2024. The overall proportion of crashes resulting in an injury decreased, with serious injury crashes falling from 11 (3.1% of total) in 2024 to 8 (2.6% of total) in 2025. Crashes involving possible injuries saw a more significant drop, decreasing from 22 incidents (6.1% share) to 12 incidents (3.9% share). Consequently, the share of non-injury crashes increased from 79.3% to 81.6% of all collisions.
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
Inattention remained the leading contributing factor in both years, though its count decreased from 66 crashes in 2024 to 55 in 2025. The ranking of other top factors shifted, with 'Failed to yield right of way' moving from the third to the second most common cause, despite its count holding steady at 38 (down from 39). Crashes attributed to 'Followed too closely' saw a significant reduction, dropping from 48 incidents in 2024 to 30 in 2025, and moving from the second to the third-ranked factor.
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 largely consistent year-over-year, with the majority of incidents in both periods occurring in daylight and on dry roads. In 2025, 79.9% of crashes happened on dry surfaces, a slight decrease from 84.6% in 2024. Correspondingly, the share of crashes on wet roads increased from 11.2% to 14.2%. The proportion of crashes occurring in daylight also saw a minor decrease, from 73.7% in 2024 to 70.9% in 2025.
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
Toyota remained the most common vehicle make involved in crashes, though its count fell from 115 in 2024 to 94 in 2025. The top three rankings shifted, with Chevrolet (59 vehicles) replacing Honda (37 vehicles) in the top group alongside Ford. Regarding persons involved, the 65+ age group (138 persons) was the largest in 2025, whereas in 2024 it was tied with the 26-34 age group at 147 persons each. The number of persons from the 26-34 age group involved in crashes decreased to 110 in 2025.
Top Vehicle Makes (553 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
40 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (697 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 broadly consistent between the two years, with no fatalities reported in any zone for either period. The 30 mph zone saw a nearly identical number of crashes, with 89 in 2025 compared to 88 in 2024. However, there was a noticeable decrease in crashes in higher speed zones, with incidents in 55 mph zones falling from 62 to 40, and those in 40 mph zones decreasing from 83 to 72.
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: SANDWICH, MA
- Total crash records analyzed: 309
- Total persons involved: 733
- Total vehicles involved: 553
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). "SANDWICH, 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/sandwich/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