ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MILFORD, 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/milford/december-2025-report
Monthly Traffic Safety Analysis
94 CRASHES IN
MILFORD, MA
DECEMBER 2025
Total crashes in Milford decreased from 132 in December 2024 to 94 in December 2025, representing a 28.8% reduction year-over-year. The most notable shift was the significant decrease in total injuries, which fell by 50% from 26 to 13. This overall trend indicates an improvement in traffic safety for the city during this period.
94
▼ -28.8%was 132
Total Crash Events
0
Persons Killed
13
▼ -50.0%was 26
Persons Injured
6
▼ -57.1%was 14
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, crash activity in Milford showed a significant downward trend year-over-year. Total crashes decreased by 28.8%, from 132 in December 2024 to 94 in December 2025. Concurrently, total injuries also saw a substantial reduction of 50%, falling from 26 to 13 over the same period. Fatalities remained at zero in both December 2024 and December 2025.
6
Hit-and-Run Crashes — December 2025
▼ -57.1% vs prior (14)
Hit-and-run crashes decreased significantly year-over-year, falling from 14 in December 2024 to 6 in December 2025, a 57.1% reduction. The overall hit-and-run rate also decreased, from 10.6% of all crashes in December 2024 to 6.4% in December 2025. This indicates a positive trend in the reduction of hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
12
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 Tuesday in December 2024 (28 crashes) to Monday in December 2025 (20 crashes). While Monday saw a decrease from 27 crashes to 20, Tuesday crashes decreased more significantly from 28 to 17. The peak hour for crashes also shifted, moving from 3 p.m. with 16 crashes in December 2024 to 2 p.m. with 9 crashes in December 2025.
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
Milford experienced a decrease in all injury severities year-over-year, with total injuries falling from 26 in December 2024 to 13 in December 2025. Serious injuries decreased from 2 to 1, while possible injuries saw the largest numerical drop, from 9 to 3. The proportion of crashes resulting in no injury increased from 81.1% in December 2024 to 87.2% in December 2025.
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
Inattention remained the leading contributing factor, though its count decreased from 35 crashes in December 2024 to 27 in December 2025, a 22.9% reduction. Failed to yield right of way saw a significant decrease of 13 crashes (from 23 to 10), dropping from the second to the third most frequent factor. Conversely, No improper driving increased by 4 crashes (from 19 to 23), moving from the third to the second most common factor.
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 decreased from 80 in December 2024 to 62 in December 2025, while Rain related crashes fell from 12 to 5. Similarly, crashes on Dry road surfaces decreased from 91 to 66, and Daylight crashes reduced from 62 to 56. Notably, crashes in Snow weather conditions slightly increased from 6 to 7, and on Snow road surfaces from 12 to 14.
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 in crashes decreased from 250 in December 2024 to 169 in December 2025. TOYOTA and FORD remained the top two vehicle makes involved, despite both seeing a decrease in crash involvement (TOYOTA from 39 to 32, FORD from 33 to 29). There was a notable decrease in persons aged 0-15 involved in crashes, from 22 to 6, and in the 21-25 age group, from 31 to 13.
Top Vehicle Makes (169 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records
19 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (174 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 occurring in 30 mph speed zones decreased from 70 in December 2024 to 56 in December 2025, a 20% reduction, but remained the most common speed zone for crashes. Crashes in 25 mph zones saw a 52.9% decrease, falling from 17 to 8. There were no fatal crashes reported in any speed limit zone for either December 2024 or December 2025.
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: MILFORD, MA
- Total crash records analyzed: 94
- Total persons involved: 195
- Total vehicles involved: 169
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). "MILFORD, 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/milford/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