ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · HALIFAX, 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/halifax/2025-annual-report
Yearly Traffic Safety Analysis
105 CRASHES IN
HALIFAX, MA
2025
In Halifax, total traffic crashes increased from 88 in the prior year to 105 in the current year, a 19.3% rise. During this same period, total injuries from crashes grew by 29.7%, from 37 to 48, while fatalities remained unchanged at one. The most notable shift was a 167% increase in crashes attributed to erratic, reckless, careless, or aggressive driving, which rose from 3 to 8 incidents.
105
▲ 19.3%was 88
Total Crash Events
1
Persons Killed
48
▲ 29.7%was 37
Persons Injured
3
▲ 50.0%was 2
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.
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
Crash data indicates a rising trend in Halifax year-over-year. Total crashes increased by 19.3%, from 88 to 105. The number of people injured in these incidents also rose from 37 to 48, while the number of fatalities held steady at one.
3
Hit-and-Run Crashes — 2025
▲ 50.0% vs prior (2)
Hit-and-run incidents showed an upward trend. The total count of hit-and-run crashes increased from 2 in the prior year to 3 in the current year. Correspondingly, the hit-and-run rate as a percentage of total crashes rose from 2.3% to 2.9%.
Vulnerable Road User Casualties
1
Motorists Killed
0
Other Killed
47
Motorists Injured
1
Other 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 timing of crashes shifted between the two periods. In the current year, Monday and Friday were the peak days for crashes with 19 incidents each, a change from the prior year when Tuesday was the peak day with 15 crashes. The peak hour for collisions also shifted later into the day, moving from the 2 p.m. and 3 p.m. hours (11 crashes each) in the prior year to the 5 p.m. hour (14 crashes) in the current year.
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, the fatal crash rate decreased slightly from 1.14% to 0.95% of all crashes. The distribution of injury severity shifted, with crashes resulting in serious injuries decreasing from 5 to 4. Conversely, crashes involving minor injuries increased from 16 to 22, and those with possible injuries rose from 5 to 9.
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 contributing factor in both years was "No improper driving," with the count of such crashes increasing from 27 to 36. A significant change was observed in crashes attributed to "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner," which increased by 167% from 3 to 8 incidents. In contrast, crashes linked to "Inattention" decreased from a count of 14 to 10, and those attributed to being "Distracted" fell from 6 to 2.
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
In both periods, most crashes occurred in clear weather on dry roads. The number of crashes in clear weather increased from 66 to 85, and on dry roads from 70 to 83. However, the proportion of crashes happening in daylight decreased from 75% of all crashes in the prior year to 69.5% in the current year, indicating a relative increase in crashes during dark, dawn, or dusk conditions.
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 vehicle makes most frequently involved in crashes shifted year-over-year. Ford-involved crashes more than doubled from 13 to 28, making it the top make in the current period, up from third. Conversely, Toyota, the top make in the prior period with 33 crashes, saw its involvement decrease to 23 crashes. The age demographics of persons in crashes also changed, with the 26-34 age group being the largest in the current year (37 persons), compared to the 65+ age group in the prior year (35 persons).
Top Vehicle Makes (177 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
8 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (221 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 speed zones changed between periods. Crashes in 35 mph zones decreased from 41 to 34, while collisions in 30 mph zones increased from 21 to 31. The single fatal crash in the prior year occurred in a 35 mph zone, whereas the fatal crash in the current year took place in a 40 mph zone.
Fatal crashes by zone: 40 mph: 1 of 14 (7.143%)
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: HALIFAX, MA
- Total crash records analyzed: 105
- Total persons involved: 228
- Total vehicles involved: 177
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). "HALIFAX, 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/halifax/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