Monthly Traffic Safety Analysis

251 CRASHES IN
FALL RIVER, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

Total crashes in Fall River, MA decreased by 3.09%, from 259 in November 2024 to 251 in November 2025. A notable positive shift is the absence of fatalities in the current period, compared to one fatality in the prior period. Overall injuries also saw a decrease, falling from 89 to 81.

251

-3.1%was 259

Total Crash Events

0

-100.0%was 1

Persons Killed

81

-9.0%was 89

Persons Injured

44

29.4%was 34

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. 17 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

The overall trend indicates a slight decrease in crash activity year-over-year, with total crashes falling by 8 incidents. Total injuries also decreased by 8, representing an 8.99% reduction. Fatalities dropped from one in the prior period to zero in the current period.

44

Hit-and-Run Crashes — November 2025

29.4% vs prior (34)

Hit-and-run crashes increased by 10 incidents, rising from 34 in November 2024 to 44 in November 2025. This change represents an increase in the hit-and-run rate from 13.1% to 17.5% of all crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

81

Motorists Injured

Prior: 810.0%

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 peak day for crashes shifted from Friday with 49 incidents in November 2024 to Saturday with 42 incidents in November 2025. While 5 PM remained the peak hour for crashes in both periods, the number of crashes at this hour decreased from 32 to 25. There was an increase in crashes on Monday and Tuesday, and a decrease on Wednesday, Thursday, and Friday.

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

The most significant change in severity is the reduction of fatal crashes from one in November 2024 to zero in November 2025. Minor injuries decreased by 14, from 52 to 38, a 26.9% reduction, and possible injuries decreased by 5, from 13 to 8, a 38.5% reduction. Serious injuries remained constant at one in both periods.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes0.4%
0.0%prior 1
Minor Injury38minor injury crashes15.1%
-26.9%prior 52
Possible Injury8possible injury crashes3.2%
-38.5%prior 13
No Injury187no injury crashes74.5%
3.9%prior 180

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

The count of 'No improper driving' as a contributing factor decreased by 28, from 103 in the prior period to 75 in the current period. Conversely, 'Failed to yield right of way' saw a 63.6% increase in count, rising from 11 to 18 crashes. 'Inattention' also increased by 5 crashes, from 29 to 34, while 'Followed too closely' decreased by 3 crashes, from 17 to 14.

Officer-Reported Primary Contributing Cause

No improper driving75 (29.9%)-27.2%prior 103
Inattention34 (13.5%)17.2%prior 29
Failure to keep in proper lane or running off road20 (8%)25.0%prior 16
Failed to yield right of way18 (7.2%)63.6%prior 11
Followed too closely14 (5.6%)-17.6%prior 17
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner10 (4%)
Made an improper turn9 (3.6%)50.0%prior 6
Other improper action8 (3.2%)-55.6%prior 18
Distracted6 (2.4%)
Disregarded traffic signs, signals, road markings6 (2.4%)-14.3%prior 7

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' weather conditions decreased from 220 in the prior period to 208 in the current period. Similarly, crashes on 'Wet' road surfaces decreased from 36 to 30. There was a notable increase in crashes occurring at 'Dawn', rising from 2 in the prior period to 8 in the current period.

Weather

Clear166 (67.2%)
2.5%prior 162
Clear/Clear25 (10.1%)
31.6%prior 19
Rain13 (5.3%)
0.0%prior 13
Clear/Cloudy11 (4.5%)
-65.6%prior 32
Cloudy9 (3.6%)
0.0%prior 9
Cloudy/Cloudy4 (1.6%)
Clear/Other4 (1.6%)
Rain/Rain3 (1.2%)
Cloudy/Rain2 (0.8%)
Clear/Unknown2 (0.8%)

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

Lighting

Daylight147 (59.5%)
-3.3%prior 152
Dark - lighted roadway66 (26.7%)
-8.3%prior 72
Dark - roadway not lighted11 (4.5%)
83.3%prior 6
Dusk9 (3.6%)
-30.8%prior 13
Dawn8 (3.2%)
Dark - unknown roadway lighting5 (2.0%)
-61.5%prior 13
Other1 (0.4%)

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

Road Surface

Dry217 (87.9%)
-2.3%prior 222
Wet30 (12.1%)
-16.7%prior 36

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 640 to 604 year-over-year. The 0-15 age group saw a significant decrease of 16 persons, falling from 45 to 29, and the 16-20 age group decreased by 30 persons, from 65 to 35. Conversely, the 45-54 age group increased by 17 persons, from 55 to 72, and the 65+ age group increased by 8 persons, from 51 to 59.

Top Vehicle Makes (498 vehicles)

1
TOYOTA83 (16.7%)
6.4%prior 78
2
HONDA57 (11.4%)
14.0%prior 50
3
CHEVROLET46 (9.2%)
12.2%prior 41
4
FORD42 (8.4%)
-17.6%prior 51
5
NISSAN41 (8.2%)
-4.7%prior 43
6
HYUNDAI34 (6.8%)
0.0%prior 34
7
KIA18 (3.6%)
12.5%prior 16
8
JEEP13 (2.6%)
-51.9%prior 27
9
SUBARU12 (2.4%)
-7.7%prior 13
10
GMC12 (2.4%)
9.1%prior 11

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

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

Sex Distribution (458 persons with recorded sex)

Male271 (59.2%)
-2.5%prior 278
Female187 (40.8%)
-13.0%prior 215

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 25 mph zones decreased by 10, from 116 in the prior period to 106 in the current period, and the single fatality previously reported in this zone was eliminated. Crashes in 55 mph zones increased by 7, from 7 to 14, while 65 mph zones saw an increase of 2 crashes, from 13 to 15. There were no fatalities recorded in any speed zone in the current 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: FALL RIVER, MA
  • Total crash records analyzed: 251
  • Total persons involved: 604
  • Total vehicles involved: 498

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). "FALL RIVER, 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/fall-river/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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Fall River, MA Crash Report — November 2025 | ThatCarHitMe.com