ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BELLINGHAM, MA · DECEMBER 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/bellingham/december-2025-report
Monthly Traffic Safety Analysis
52 CRASHES IN
BELLINGHAM, MA
DECEMBER 2025
Total crashes in December 2025 were 52, a decrease from 54 crashes in December 2024, representing a 3.7% reduction. The most notable shift was a 43.75% decrease in total injuries, falling from 16 in the prior year to 9 in the current period. Additionally, DUI crashes decreased by 100%, from 2 in December 2024 to 0 in December 2025.
52
▼ -3.7%was 54
Total Crash Events
0
Persons Killed
9
▼ -43.8%was 16
Persons Injured
2
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the trend for crashes in December shows a slight decrease year-over-year, with total crashes falling by 3.7% from 54 to 52. More significantly, total injuries experienced a substantial decline of 43.75%, decreasing from 16 persons injured in December 2024 to 9 in December 2025. Fatalities remained at 0 for both periods.
2
Hit-and-Run Crashes — December 2025
▼ 0.0% vs prior (2)
The number of hit-and-run crashes remained constant at 2 for both December 2024 and December 2025. The hit-and-run crash rate saw a minor increase from 3.7% in the prior period to 3.8% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
8
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 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 shifted from Friday with 10 crashes in December 2024 to Tuesday with 11 crashes in December 2025. The peak hour for crashes also changed, moving from 1 PM with 8 crashes in the prior period to 4 PM with 6 crashes in the current period. Crashes on Mondays increased from 9 to 9, Tuesdays increased from 6 to 11, Thursdays decreased from 10 to 6, and Fridays decreased from 10 to 8.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at 0 for both periods. The proportion of serious injury crashes decreased from 3.7% (2 crashes) in December 2024 to 1.9% (1 crash) in December 2025. Possible injury crashes also saw a reduction in proportion, from 7.4% (4 crashes) to 3.8% (2 crashes), while minor injury crashes remained stable at 4 crashes, representing 7.4% and 7.7% respectively.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to "No improper driving" decreased by 2, from 18 in December 2024 to 16 in December 2025. "Failed to yield right of way" crashes saw a significant increase, rising from 1 crash in the prior period to 13 crashes in the current period. "Followed too closely" crashes increased by 2, from 6 to 8 crashes year-over-year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Clear" weather conditions remained constant at 32 for both periods. Crashes during "Rain" increased from 5 to 9, while those during "Snow" decreased from 7 to 1. Crashes on "Wet" road surfaces nearly doubled, increasing from 10 in December 2024 to 19 in December 2025, whereas crashes on "Dry" surfaces decreased from 35 to 31.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved decreased slightly from 102 to 100. The top vehicle make involved shifted, with Ford decreasing from 18 to 11, while Toyota increased from 12 to 13. Regarding persons involved, there was an increase in younger age groups, with persons aged 0-15 increasing from 5 to 8, and 16-20 increasing from 10 to 16.
Top Vehicle Makes (100 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records
8 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (114 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones saw a notable decrease, falling from 22 to 11 crashes year-over-year. Conversely, crashes in 35 mph zones increased from 14 to 20, and crashes in 40 mph zones increased from 2 to 7. Crashes in 65 mph zones also saw an increase, rising from 1 to 5.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 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: 2025-12-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-12-01 through 2025-12-31 (31 days)
- Geographic scope: BELLINGHAM, MA
- Total crash records analyzed: 52
- Total persons involved: 123
- Total vehicles involved: 100
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). "BELLINGHAM, MA Crash Intelligence Report: December 2025." Published June 21, 2026. Reporting period: 2025-12-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/bellingham/december-2025-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: 2025-12-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved