Monthly Traffic Safety Analysis

31 CRASHES IN
FREETOWN, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, FREETOWN experienced 31 crashes, an increase of 6.9% compared to the 29 crashes reported in November 2024. Total injuries saw a significant increase of 150%, rising from 4 in the prior period to 10 in the current period. Fatal crashes remained stable with 1 recorded in both periods.

31

6.9%was 29

Total Crash Events

1

Persons Killed

10

150.0%was 4

Persons Injured

1

-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 · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in crash activity year-over-year in FREETOWN. Total crashes increased by 6.9%, from 29 in November 2024 to 31 in November 2025. This was accompanied by a substantial 150% rise in total injuries, from 4 to 10.

1

Hit-and-Run Crashes — November 2025

-50.0% vs prior (2)

Hit-and-run crashes decreased by 50%, falling from 2 crashes in November 2024 to 1 crash in November 2025. The hit-and-run rate also decreased from 6.9% to 3.2% year-over-year.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 10.0%

10

Motorists Injured

Prior: 4150.0%

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 temporal patterns of crashes shifted year-over-year, with the peak crash day moving from Tuesday (7 crashes) in November 2024 to Monday, Thursday, and Friday (6 crashes each) in November 2025. The peak crash hour also shifted from 9 AM (4 crashes) in the prior period to 5 PM (4 crashes) in the current period. Overall, Sunday crashes increased from 1 to 5, while Wednesday crashes decreased from 5 to 1.

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

While fatal crashes remained constant at 1 in both periods, the number of minor injury crashes increased significantly from 1 in November 2024 to 7 in November 2025. Consequently, the share of minor injury crashes rose from 3.4% to 22.6% year-over-year. Crashes with no injury decreased in share from 86.2% to 74.2%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes3.2%
0.0%prior 1
Minor Injury7minor injury crashes22.6%
600.0%prior 1
No Injury23no injury crashes74.2%
-8.0%prior 25

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 3, from 17 crashes in the prior period to 14 crashes in the current period. Conversely, 'Inattention' crashes increased by 1, from 3 to 4 crashes, representing a 33.3% increase in count. 'Followed too closely' also increased by 1 crash, from 1 to 2, marking a 100% increase in count.

Officer-Reported Primary Contributing Cause

No improper driving14 (45.2%)-17.6%prior 17
Inattention4 (12.9%)
Failure to keep in proper lane or running off road2 (6.5%)
Followed too closely2 (6.5%)
Over-correcting/over-steering2 (6.5%)
Failed to yield right of way1 (3.2%)
Exceeded authorized speed limit1 (3.2%)
Operating defective equipment1 (3.2%)
Fatigued/asleep1 (3.2%)
Distracted1 (3.2%)

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

There was a notable shift in lighting conditions, with crashes occurring in 'Dark - roadway not lighted' conditions increasing from 9 in November 2024 to 16 in November 2025. Crashes in daylight conditions decreased from 16 to 12 year-over-year. The number of crashes on dry road surfaces increased from 22 to 27, while crashes on wet surfaces increased from 3 to 4.

Weather

Clear16 (51.6%)
-15.8%prior 19
Clear/Clear10 (32.3%)
66.7%prior 6
Cloudy2 (6.5%)
Rain2 (6.5%)
Rain/Cloudy1 (3.2%)

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

Lighting

Dark - roadway not lighted16 (51.6%)
77.8%prior 9
Daylight12 (38.7%)
-25.0%prior 16
Dark - lighted roadway3 (9.7%)

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

Road Surface

Dry27 (87.1%)
22.7%prior 22
Wet4 (12.9%)

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

Vehicles & Demographics

Top Vehicle Makes (45 vehicles)

1
TOYOTA9 (20%)
80.0%prior 5
2
FORD6 (13.3%)
20.0%prior 5
3
HYUNDAI4 (8.9%)
4
JEEP4 (8.9%)
5
DODGE3 (6.7%)
6
NISSAN3 (6.7%)
7
VOLKSWAGEN2 (4.4%)
8
RAM2 (4.4%)
9
BMW1 (2.2%)
10
VOLVO1 (2.2%)

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

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

Sex Distribution (55 persons with recorded sex)

Male37 (67.3%)
37.0%prior 27
Female18 (32.7%)
28.6%prior 14

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 in the 65 mph speed zone increased by 50%, rising from 8 crashes in November 2024 to 12 crashes in November 2025. The current period recorded 1 fatal crash in the 65 mph zone, while no fatal crashes were recorded across any listed speed zones in the prior period. Crashes in the 40 mph zone also increased from 3 to 5.

Fatal crashes by zone: 65 mph: 1 of 12 (8.333%)

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: FREETOWN, MA
  • Total crash records analyzed: 31
  • Total persons involved: 59
  • Total vehicles involved: 45

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). "FREETOWN, 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/freetown/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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Freetown, MA Crash Report — November 2025 | ThatCarHitMe.com