ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MILFORD, MA · JULY 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/july-2025-report
Monthly Traffic Safety Analysis
91 CRASHES IN
MILFORD, MA
JULY 2025
Milford experienced a significant increase in crash activity from July 2024 to July 2025. Total crashes rose from 62 to 91, marking a 46.8% increase year-over-year. This period also saw a substantial rise in total injuries, increasing from 12 to 34. The most notable shift was the overall increase in crash volume.
91
▲ 46.8%was 62
Total Crash Events
0
Persons Killed
34
▲ 183.3%was 12
Persons Injured
7
▲ 75.0%was 4
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 · 2025-07-01 to 2025-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Milford experienced a rising trend in crash incidents, with total crashes increasing from 62 in July 2024 to 91 in July 2025. This constitutes a 46.8% year-over-year increase in crash volume. The data indicates an upward trend in crash occurrences.
7
Hit-and-Run Crashes — July 2025
▲ 75.0% vs prior (4)
Hit-and-run crashes increased from 4 incidents in July 2024 to 7 incidents in July 2025. Concurrently, the hit-and-run rate rose from 6.5% of all crashes to 7.7% year-over-year. This indicates an upward trend in both the number and proportion of hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
33
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · 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 year-over-year. The peak day for crashes moved from Monday in July 2024 with 12 crashes to Thursday in July 2025 with 24 crashes. Similarly, the peak crash hour changed from 3 p.m. with 7 crashes in July 2024 to 6 p.m. with 10 crashes in July 2025, indicating a shift in high-frequency periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While fatal crashes remained at zero in both July 2024 and July 2025, the total number of injuries significantly increased from 12 to 34. This represents a 183.3% rise in injuries year-over-year. Additionally, serious injury crashes, categorized as 'A', were reported in July 2025 with 1 incident, whereas none were recorded in July 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, 'Inattention,' saw a substantial increase from 17 crashes in July 2024 to 32 crashes in July 2025. Crashes due to 'Followed too closely' also rose from 6 to 11, and 'Failure to keep in proper lane or running off road' increased from 1 to 6. Conversely, 'Failed to yield right of way' crashes decreased from 13 to 9, and 'Driving too fast for conditions' decreased from 3 to 2.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 46 in July 2024 to 67 in July 2025. Similarly, incidents during 'Daylight' hours rose from 45 to 73 year-over-year. Crashes on 'Dry' road surfaces also increased from 57 to 81, while those on 'Wet' surfaces doubled from 5 to 10.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 118 in July 2024 to 174 in July 2025. Among top vehicle makes, Ford saw the largest increase, from 6 to 24 vehicles involved. All age groups saw an increase in representation, with the 0-15, 45-54, and 65+ age groups experiencing the most significant proportional rises in persons involved in crashes.
Top Vehicle Makes (174 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Vehicle unit records
23 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (194 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone increased from 35 in July 2024 to 53 in July 2025, remaining the most frequent speed zone for incidents. Crashes in the 25 mph zone also rose from 7 to 13, and in the 65 mph zone from 3 to 6. There were no fatal crashes recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · 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: 2025-07-01 through 2025-07-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-07-01 through 2025-07-31 (31 days)
- Geographic scope: MILFORD, MA
- Total crash records analyzed: 91
- Total persons involved: 219
- Total vehicles involved: 174
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: July 2025." Published June 21, 2026. Reporting period: 2025-07-01 to 2025-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milford/july-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: 2025-07-01 – 2025-07-31
Generated: June 21, 2026 · All rights reserved