ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FRAMINGHAM, MA · FEBRUARY 2026
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/framingham/february-2026-report
Monthly Traffic Safety Analysis
104 CRASHES IN
FRAMINGHAM, MA
FEBRUARY 2026
In February 2026, FRAMINGHAM experienced 104 crashes, an increase from the 97 crashes reported in February 2025, representing a 7.22% rise. The most notable year-over-year shift was a 60% increase in hit-and-run crashes, which rose from 15 to 24 incidents.
104
▲ 7.2%was 97
Total Crash Events
0
Persons Killed
21
▼ -8.7%was 23
Persons Injured
24
▲ 60.0%was 15
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. 10 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in FRAMINGHAM show an upward trend year-over-year, with total crashes increasing from 97 in February 2025 to 104 in February 2026. This represents a 7.22% increase in crash incidents for the month.
24
Hit-and-Run Crashes — February 2026
▲ 60.0% vs prior (15)
Hit-and-run crashes increased significantly from 15 incidents in February 2025 to 24 incidents in February 2026. This change resulted in the hit-and-run rate rising from 15.5% to 23.1% of all crashes, indicating an upward trend in these types of incidents.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
20
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year, with the peak day moving from Wednesday in February 2025 (15 crashes) to Saturday in February 2026 (21 crashes). The peak hour for crashes also changed, moving from 7 AM (10 crashes) in the prior period to 6 PM (10 crashes) in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either February 2025 or February 2026. Total injuries decreased slightly from 23 in the prior period to 21 in the current period. Notably, the current period recorded one serious injury crash (code A), which was not present in the prior period, while minor injury crashes decreased from 12 (12.4% share) to 9 (8.7% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, 'No improper driving,' increased from 31 crashes in the prior period to 36 crashes in the current period. 'Followed too closely' saw a significant increase, rising from 6 crashes to 13 crashes year-over-year. 'Driving too fast for conditions' also increased from 6 crashes to 7 crashes, while 'Failed to yield right of way' remained consistent at 10 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear/Clear' weather conditions increased from 43 to 50 incidents year-over-year, and crashes during 'Snow/Snow' conditions more than doubled from 6 to 13. While crashes on 'Dry' road surfaces decreased from 62 to 58, incidents on 'Snow' road surfaces notably increased from 15 to 28. Crashes during 'Daylight' increased from 60 to 69, while those in 'Dark - lighted roadway' decreased from 30 to 25.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Road surface condition field
Vehicles & Demographics
TOYOTA remained the most frequently involved vehicle make, increasing slightly from 36 to 37 vehicles. HONDA involvement decreased from 29 to 24, while FORD involvement increased from 18 to 21. CHEVROLET involvement significantly increased from 6 to 19, entering the top 5, and JEEP also entered the top 5 with 13 vehicles, replacing NISSAN and SUBARU from the prior period's top rankings. The 21-25 age group saw an increase from 18 to 29 persons involved, and the 26-34 age group increased from 30 to 44 persons involved.
Top Vehicle Makes (199 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Vehicle unit records
41 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (186 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed zone increased from 3 to 4, and those in the 30 mph zone increased from 1 to 3. Conversely, crashes in the 35 mph zone decreased from 2 to 1, and in the 65 mph zone, crashes decreased from 11 to 10. No fatal crashes were reported in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · 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: 2026-02-01 through 2026-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-02-01 through 2026-02-28 (28 days)
- Geographic scope: FRAMINGHAM, MA
- Total crash records analyzed: 104
- Total persons involved: 231
- Total vehicles involved: 199
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). "FRAMINGHAM, MA Crash Intelligence Report: February 2026." Published June 21, 2026. Reporting period: 2026-02-01 to 2026-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/framingham/february-2026-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: 2026-02-01 – 2026-02-28
Generated: June 21, 2026 · All rights reserved