Monthly Traffic Safety Analysis

22 CRASHES IN
FREETOWN, MA
OCTOBER 2025

All metrics benchmarked againstOctober 2024

In October 2025, Freetown experienced 22 total crashes, which is consistent with the 22 crashes reported in October 2024, representing a 0% change year-over-year. However, total injuries saw a significant decrease, falling by 45.45% from 11 in the prior period to 6 in the current period.

22

Total Crash Events

0

Persons Killed

6

-45.5%was 11

Persons Injured

0

Fatal Crash Events

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The total number of crashes remained stable year-over-year, with 22 crashes recorded in both October 2024 and October 2025. While fatalities remained at 0 in both periods, total injuries decreased by 45.45%, from 11 in October 2024 to 6 in October 2025.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 11-45.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Thursday, which had 7 crashes in October 2024, to Friday, with 6 crashes in October 2025. The peak hour also changed, moving from 2 PM with 3 crashes in the prior period to 4 PM with 4 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Both periods reported 0 total fatalities and 0 fatal crashes. Total injuries decreased from 11 in October 2024 to 6 in October 2025. Minor injury crashes increased from 3 (13.6% of crashes) to 4 (18.2% of crashes), while possible injury crashes decreased from 3 (13.6% of crashes) to 1 (4.5% of crashes).

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes18.2%
33.3%prior 3
Possible Injury1possible injury crashes4.5%
-66.7%prior 3
No Injury16no injury crashes72.7%
0.0%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' increased from 5 (22.7% share) in October 2024 to 7 (31.8% share) in October 2025. 'Followed too closely' crashes increased from a count of 2 (9.1% share) to 3 (13.6% share) year-over-year. Conversely, 'Failed to yield right of way' decreased from 3 crashes (13.6% share) in the prior period to 1 crash (4.5% share) in the current period.

Officer-Reported Primary Contributing Cause

No improper driving7 (31.8%)40.0%prior 5
Followed too closely3 (13.6%)
Inattention3 (13.6%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (9.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.5%)
Over-correcting/over-steering1 (4.5%)
Disregarded traffic signs, signals, road markings1 (4.5%)
Failed to yield right of way1 (4.5%)
Failure to keep in proper lane or running off road1 (4.5%)
Glare1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 17 in October 2024 to 14 in October 2025, while 'Rain' conditions saw an increase from 2 to 3 crashes. For lighting, 'Daylight' crashes decreased from 14 to 11, and crashes in 'Dark - roadway not lighted' conditions increased from 5 to 7. On road surfaces, 'Dry' conditions saw a decrease from 19 crashes to 17, while 'Wet' conditions increased from 2 to 5 crashes.

Weather

Clear14 (63.6%)
-17.6%prior 17
Rain3 (13.6%)
Clear/Clear2 (9.1%)
Rain/Cloudy2 (9.1%)
Cloudy1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Weather condition at time of crash

Lighting

Daylight11 (50.0%)
-21.4%prior 14
Dark - roadway not lighted7 (31.8%)
40.0%prior 5
Dark - lighted roadway2 (9.1%)
Dawn2 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Lighting condition field

Road Surface

Dry17 (77.3%)
-10.5%prior 19
Wet5 (22.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (32 vehicles)

1
TOYOTA7 (21.9%)
2
JEEP5 (15.6%)
3
KIA3 (9.4%)
4
AUDI2 (6.3%)
5
FORD2 (6.3%)
6
HONDA2 (6.3%)
-60.0%prior 5
7
HYUNDAI2 (6.3%)
8
UTIL1 (3.1%)
9
FRHT1 (3.1%)
10
CHEVROLET1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Vehicle unit records

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

Sex Distribution (43 persons with recorded sex)

Male24 (55.8%)
-4.0%prior 25
Female19 (44.2%)
26.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 7 in October 2024 to 4 in October 2025, while crashes in the 35 mph zone increased from 2 to 5. The 40 mph and 65 mph zones both saw an increase in crashes from 3 to 5 and 2 to 5, respectively. No fatal crashes were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · 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: 2025-10-01 through 2025-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-10-01 through 2025-10-31 (31 days)
  • Geographic scope: FREETOWN, MA
  • Total crash records analyzed: 22
  • Total persons involved: 45
  • Total vehicles involved: 32

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: October 2025." Published June 21, 2026. Reporting period: 2025-10-01 to 2025-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/freetown/october-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 — October 2025 | ThatCarHitMe.com