ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FRAMINGHAM, 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/framingham/2025-annual-report
Yearly Traffic Safety Analysis
1,203 CRASHES IN
FRAMINGHAM, MA
2025
In 2025, Framingham recorded 1,203 total traffic crashes, a 13.6% decrease from the 1,392 crashes reported in 2024. Despite the overall reduction in collisions and a 16.0% drop in total injuries, the number of fatalities doubled, increasing from 3 in the prior year to 6 in the current year.
1,203
▼ -13.6%was 1,392
Total Crash Events
6
▲ 100.0%was 3
Persons Killed
358
▼ -16.0%was 426
Persons Injured
171
▼ -26.3%was 232
Hit-and-Run Crashes
Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 44 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
Overall, the total number of crashes in Framingham saw a year-over-year decrease of 13.6%, falling from 1,392 in 2024 to 1,203 in 2025. This downward trend was also reflected in total injuries, which declined by 16.0% from 426 to 358. In contrast, the number of fatalities doubled from 3 to 6 over the same period.
171
Hit-and-Run Crashes — 2025
▼ -26.3% vs prior (232)
The number of hit-and-run incidents in Framingham decreased year-over-year. There were 171 hit-and-run crashes in 2025, a 26.3% reduction from the 232 incidents recorded in 2024. The hit-and-run rate, representing the proportion of all crashes that were hit-and-runs, also trended downward, falling from 16.7% to 14.2%.
Vulnerable Road User Casualties
2
Pedestrians Killed
1
Cyclists Killed
3
Motorists Killed
0
Other Killed
21
Pedestrians Injured
23
Cyclists Injured
306
Motorists Injured
8
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 temporal pattern of crashes showed some shifts between the two years. While the 5 p.m. hour remained the most frequent time for crashes in both periods, the number of incidents during this peak hour decreased from 110 to 95. The peak day for crashes shifted from Friday (213 crashes) in 2024 to Wednesday (212 crashes) in 2025.
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 decreased, the severity of outcomes worsened in 2025. The number of fatal crashes doubled from 3 to 6, and the corresponding fatal crash rate increased from 0.22% to 0.50% of all crashes. The proportion of crashes resulting in serious injury decreased slightly from 2.0% to 1.7%, but minor injury crashes increased as a share of the total, rising from 12.6% to 15.3%.
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 primary contributing factors cited in crashes remained consistent year-over-year, with 'Failed to yield right of way' and 'Followed too closely' being the top two driver-related factors after 'No improper driving'. The count of crashes attributed to failing to yield decreased by 14.0% from 186 to 160, while those for following too closely dropped by 15.9% from 182 to 153. Notably, crashes involving fatigued or asleep drivers doubled in count from 7 to 14, and incidents related to driving too fast for conditions were cut in half, falling from 55 to 27.
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
The distribution of environmental conditions during crashes remained largely stable year-over-year. Crashes on dry roads accounted for 81.1% of all incidents in 2025, compared to 81.9% in 2024. Similarly, the proportion of crashes occurring in daylight was consistent, making up 66.9% of the total in 2025 versus 64.4% in the prior year. There were no significant shifts in the proportion of crashes occurring during adverse weather or lighting 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 top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained unchanged between the two periods, though the number of Toyotas and Fords involved decreased by 21.8% and 17.2% respectively. Analysis of persons involved in crashes shows a shift in age demographics. While the total number of people involved decreased, the 35-44 age group saw its share increase from 16.3% to 17.3%, while the 26-34 age group's share decreased from 17.8% to 15.5%.
Top Vehicle Makes (2,251 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
346 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,301 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
Crashes in the 65 mph speed zone, the zone with the highest number of incidents in both periods, decreased from 160 in 2024 to 110 in 2025. A notable drop was also seen in zones with speed limits between 25 and 35 mph, where the combined crash count fell from 145 to 90. In 2025, one fatal crash was recorded in a 25 mph zone and another in a 35 mph zone, compared to a single fatal crash in a 35 mph zone in the prior year.
Fatal crashes by zone: 25 mph: 1 of 34 (2.941%) · 35 mph: 1 of 16 (6.25%)
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: FRAMINGHAM, MA
- Total crash records analyzed: 1,203
- Total persons involved: 2,707
- Total vehicles involved: 2,251
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: 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/framingham/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