ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WESTFORD, 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/westford/2025-annual-report
Yearly Traffic Safety Analysis
511 CRASHES IN
WESTFORD, MA
2025
In 2025, Westford recorded 511 total crashes, a 14.6% increase from the 446 crashes reported in 2024. While the overall number of collisions rose, the number of traffic fatalities decreased from 3 in the prior year to 1 in the current year. The most significant trend was the overall increase in crash volume.
511
▲ 14.6%was 446
Total Crash Events
1
▼ -66.7%was 3
Persons Killed
86
▲ 21.1%was 71
Persons Injured
26
▲ 4.0%was 25
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. 15 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
Crash data for Westford shows an upward trend in collision frequency year-over-year. Total crashes increased by 14.6% from 446 to 511, and total injuries rose by 21.1% from 71 to 86. In contrast, traffic fatalities declined from 3 in the prior year to 1 in the current period.
26
Hit-and-Run Crashes — 2025
▲ 4.0% vs prior (25)
The total count of hit-and-run crashes remained stable, with 26 incidents in the current period compared to 25 in the prior period. As a result of the increase in total collisions, the hit-and-run rate decreased slightly. These incidents accounted for 5.1% of all crashes in the current year, down from 5.6% in the previous year.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
0
Cyclists Injured
85
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 remained largely consistent between the two periods. Thursday continued to be the peak day for crashes, with the count increasing from 79 to 94, and 4 p.m. remained the peak hour for collisions. The daily distribution of crashes in the current year was most concentrated on Wednesday, Thursday, and Friday, a slight shift from the Tuesday, Wednesday, and Thursday peaks of the prior 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 total crashes increased, the severity profile shifted. The number of fatal crashes decreased from 3 to 1 year-over-year, lowering the fatal crash rate from 0.7% to 0.2% of all incidents. Conversely, the count of crashes resulting in serious injuries doubled from 3 to 6. The proportion of non-injury crashes remained stable, accounting for 84.1% of incidents in the current year compared to 83.4% in the prior year.
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 top three contributing factors cited in crashes were consistent across both years: 'No improper driving,' 'Inattention,' and 'Followed too closely.' The count of crashes attributed to 'Inattention' decreased by 14.8% (from 81 to 69), while crashes involving 'Failure to keep in proper lane' increased by 39.1% (from 23 to 32). Crashes where 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' was a factor also rose in count from 18 to 25.
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
Crashes occurred more frequently in adverse conditions compared to the previous year. The count of collisions in rain increased by 70% (from 20 to 34), and crashes on wet roads rose by 78% (from 37 to 66). Crashes on icy roads also doubled from 7 to 14. Although clear, dry conditions still accounted for the majority of incidents, their share of total crashes decreased.
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 top vehicle makes involved in crashes, Toyota and Honda, remained consistent in rank and volume year-over-year. However, the number of Ford vehicles in collisions increased by 45.5%, from 66 to 96. The age distribution of all persons involved showed a slight increase in the proportion of the 21-25 age group, which grew from representing 8.9% to 10.3% of individuals, while other age demographics remained stable.
Top Vehicle Makes (887 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
73 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (999 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
A notable shift occurred in the location of fatal crashes, with the current year's single fatality happening in a 30 mph zone, whereas all 3 fatalities in the prior year occurred in 65 mph zones. Overall crash counts grew in higher speed zones, with a 33.8% increase in 40 mph zones (from 71 to 95) and a 28.6% increase in 65 mph zones (from 63 to 81). The 30 mph zone remained the most common location for crashes in both periods, with counts holding steady at 229 versus 228.
Fatal crashes by zone: 30 mph: 1 of 229 (0.437%)
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: WESTFORD, MA
- Total crash records analyzed: 511
- Total persons involved: 1,082
- Total vehicles involved: 887
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). "WESTFORD, 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/westford/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