Monthly Traffic Safety Analysis

99 CRASHES IN
FRAMINGHAM, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, FRAMINGHAM experienced 99 crashes, a 28.3% decrease compared to the 138 crashes recorded in November 2024. Despite the overall reduction in crashes, the number of pedestrians injured increased by 150%, rising from 2 to 5, and there was one cyclist fatality in November 2025 compared to none in the prior year.

99

▼ -28.3%was 138

Total Crash Events

1

Persons Killed

37

▼ -26.0%was 50

Persons Injured

10

▼ -50.0%was 20

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. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in FRAMINGHAM decreased year-over-year. The total number of crashes fell by 28.3%, from 138 crashes in November 2024 to 99 crashes in November 2025. Total fatalities remained stable at 1, while total injuries decreased by 26%, from 50 to 37.

10

Hit-and-Run Crashes — November 2025

▼ -50.0% vs prior (20)

Hit-and-run crashes decreased by 50%, falling from 20 in November 2024 to 10 in November 2025. Correspondingly, the hit-and-run crash rate decreased from 14.5% of all crashes in November 2024 to 10.1% in November 2025, indicating a downward trend in these incidents.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Cyclists Killed

Prior: 0→%

0

Motorists Killed

Prior: 1↓-100.0%

5

Pedestrians Injured

Prior: 2↑150.0%

2

Cyclists Injured

Prior: 2→0.0%

30

Motorists Injured

Prior: 46↓-34.8%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak crash day shifted from Friday, which had 28 crashes in November 2024, to both Friday and Saturday, each recording 16 crashes in November 2025. The peak crash hour also shifted significantly, moving from 7 PM with 15 crashes in November 2024 to 7 AM with 11 crashes in November 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained constant at 1 in both periods, but the fatal crash rate increased from 0.72% in November 2024 to 1.01% in November 2025 due to fewer total crashes. Serious injuries decreased by 2, from 5 to 3, while possible injuries saw a substantial reduction of 9, falling from 15 to 6. Minor injuries remained stable at 16 in both periods.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1%
→0.0%prior 1
Serious Injury3serious injury crashes3%
↓-40.0%prior 5
Minor Injury16minor injury crashes16.2%
→0.0%prior 16
Possible Injury6possible injury crashes6.1%
↓-60.0%prior 15
No Injury70no injury crashes70.7%
↓-25.5%prior 94

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' decreased by 14, from 32 in November 2024 to 18 in November 2025, a 43.75% reduction in count. 'Failed to yield right of way' crashes also saw a significant decrease of 13, from 25 to 12, a 52% reduction in count. Conversely, crashes involving 'Fatigued/asleep' as a factor increased by 4, from 1 crash to 5 crashes, representing a 400% increase in count.

Officer-Reported Primary Contributing Cause

No improper driving18 (18.2%)↓-43.8%prior 32
Followed too closely15 (15.2%)↓-11.8%prior 17
Failure to keep in proper lane or running off road13 (13.1%)↑30.0%prior 10
Failed to yield right of way12 (12.1%)↓-52.0%prior 25
Inattention5 (5.1%)→0.0%prior 5
Fatigued/asleep5 (5.1%)
Disregarded traffic signs, signals, road markings4 (4%)↓-63.6%prior 11
Wrong side or wrong way2 (2%)
Made an improper turn1 (1%)↓-80.0%prior 5
Other improper action1 (1%)↓-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear/Clear' weather conditions decreased from 74 in November 2024 to 59 in November 2025. Crashes in 'Rain/Rain' conditions also decreased by more than half, from 11 to 5. Similarly, crashes on 'Dry' road surfaces decreased from 116 to 89, and on 'Wet' road surfaces from 21 to 10.

Weather

Clear/Clear59 (59.6%)
↓-20.3%prior 74
Clear20 (20.2%)
↓-42.9%prior 35
Cloudy/Cloudy7 (7.1%)
Rain/Rain5 (5.1%)
↓-54.5%prior 11
Cloudy3 (3.0%)
Rain3 (3.0%)
↓-40.0%prior 5
Clear/Cloudy2 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash

Lighting

Daylight43 (43.4%)
↓-32.8%prior 64
Dark - lighted roadway38 (38.4%)
↓-36.7%prior 60
Dusk8 (8.1%)
↑33.3%prior 6
Dark - roadway not lighted5 (5.1%)
Dawn5 (5.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field

Road Surface

Dry89 (89.9%)
↓-23.3%prior 116
Wet10 (10.1%)
↓-52.4%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes decreased from 338 in November 2024 to 222 in November 2025. All reported age groups saw a reduction in involved persons, with the 26-34 age group experiencing the largest numerical decrease of 17 persons. Toyota, Honda, and Ford remained the top three vehicle makes involved in crashes, though their individual counts decreased year-over-year.

Top Vehicle Makes (177 vehicles)

1
TOYOTA33 (18.6%)
↓-34.0%prior 50
2
HONDA32 (18.1%)
↓-13.5%prior 37
3
FORD18 (10.2%)
↓-35.7%prior 28
4
SUBARU11 (6.2%)
↓-21.4%prior 14
5
CHEVROLET10 (5.6%)
↓-23.1%prior 13
6
JEEP9 (5.1%)
→0.0%prior 9
7
NISSAN8 (4.5%)
↓-33.3%prior 12
8
VOLKSWAGEN6 (3.4%)
↓-25.0%prior 8
9
HYUNDAI5 (2.8%)
↓-58.3%prior 12
10
MERCEDES-BENZ5 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records

17 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (203 persons with recorded sex)

Male115 (56.7%)
↓-27.2%prior 158
Female88 (43.3%)
↓-34.3%prior 134

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes reported in 25 mph zones decreased by 2, from 6 in November 2024 to 4 in November 2025, a 33.3% reduction in count. Crashes in 30 mph zones also decreased by 2, from 6 to 4, representing a 33.3% reduction. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-11-01 through 2025-11-30 (30 days)
  • Geographic scope: FRAMINGHAM, MA
  • Total crash records analyzed: 99
  • Total persons involved: 222
  • 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). "FRAMINGHAM, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/framingham/november-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

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Framingham, MA Crash Report — November 2025 | ThatCarHitMe.com