Monthly Traffic Safety Analysis

316 CRASHES IN
FALL RIVER, MA
DECEMBER 2025

All metrics benchmarked againstDecember 2024

FALL RIVER, MA experienced an overall increase in total crashes in December 2025, rising by 10.1% from 287 crashes in December 2024 to 316 crashes. Despite this increase in crash volume, total injuries decreased significantly by 32.3%, from 99 to 67, and there were no fatalities reported in December 2025 compared to one fatality in December 2024. The most notable shift was the complete absence of pedestrian crashes and related injuries in the current period, down from 10 pedestrian crashes and 9 pedestrian injuries in the prior year.

316

10.1%was 287

Total Crash Events

0

-100.0%was 1

Persons Killed

67

-32.3%was 99

Persons Injured

44

25.7%was 35

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in FALL RIVER, MA showed an upward trend, increasing by 10.1% from 287 crashes in December 2024 to 316 crashes in December 2025. Conversely, total injuries decreased by 32.3% from 99 to 67, and fatalities dropped from one to zero year-over-year, indicating a decrease in crash severity despite the rise in incidents.

44

Hit-and-Run Crashes — December 2025

25.7% vs prior (35)

Hit-and-run crashes increased by 25.7% year-over-year, rising from 35 incidents in December 2024 to 44 in December 2025. Consequently, the hit-and-run rate also saw an increase, moving from 12.2% to 13.9% of all crashes. This indicates an upward trend in hit-and-run incidents relative to total crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

67

Motorists Injured

Prior: 90-25.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 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 patterns of crashes shifted year-over-year, with the peak crash day moving from Tuesday in December 2024 (52 crashes) to Monday in December 2025 (74 crashes), representing a 42.3% increase in Monday crashes. The peak crash hour remained consistent at 5 PM in both periods, with 31 crashes reported during that hour for both December 2024 and December 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes improved, as fatal crashes decreased from one (0.3% of total crashes) in December 2024 to zero in December 2025. Total injuries also saw a substantial reduction of 32.3%, from 99 persons injured to 67 persons injured. While serious injury crashes remained stable at 4 incidents, minor injury crashes decreased by 25.9% (from 54 to 40), and possible injury crashes decreased by 54.5% (from 11 to 5).

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes1.3%
0.0%prior 4
Minor Injury40minor injury crashes12.7%
-25.9%prior 54
Possible Injury5possible injury crashes1.6%
-54.5%prior 11
No Injury252no injury crashes79.7%
26.0%prior 200

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' crashes increased by 13.3% from 30 to 34, moving from the third to the second most frequent factor. Conversely, 'Failed to yield right of way' crashes decreased by 24.2%, from 33 to 25, dropping from second to fourth in ranking. 'Failure to keep in proper lane or running off road' saw a significant 47.1% increase in count, rising from 17 to 25 crashes, while 'Disregarded traffic signs, signals, road markings' decreased by 76.2% from 21 to 5 crashes.

Officer-Reported Primary Contributing Cause

No improper driving94 (29.7%)2.2%prior 92
Inattention34 (10.8%)13.3%prior 30
Failure to keep in proper lane or running off road25 (7.9%)47.1%prior 17
Failed to yield right of way25 (7.9%)-24.2%prior 33
Other improper action18 (5.7%)80.0%prior 10
Followed too closely15 (4.7%)-16.7%prior 18
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner11 (3.5%)22.2%prior 9
Driving too fast for conditions10 (3.2%)42.9%prior 7
Made an improper turn9 (2.8%)
Distracted5 (1.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased by 17.3% from 156 to 183 incidents. 'Snow' appeared as a significant condition in the current period with 18 crashes, whereas it was not a top condition in the prior period. Conversely, crashes under 'Rain' conditions (summing all rain-related categories) decreased by 43.9% from 41 to 23 incidents. On road surfaces, 'Dry' conditions saw a 10.2% increase from 216 to 238 crashes, while 'Snow' surface crashes surged by 800% from 3 to 27 incidents, and 'Wet' surface crashes decreased by 29.5% from 61 to 43.

Weather

Clear183 (58.1%)
17.3%prior 156
Clear/Cloudy27 (8.6%)
-12.9%prior 31
Clear/Clear18 (5.7%)
-14.3%prior 21
Snow18 (5.7%)
Rain17 (5.4%)
-10.5%prior 19
Clear/Other10 (3.2%)
100.0%prior 5
Cloudy9 (2.9%)
Cloudy/Cloudy4 (1.3%)
Clear/Unknown4 (1.3%)
-55.6%prior 9
Cloudy/Snow3 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight182 (58.1%)
15.9%prior 157
Dark - lighted roadway103 (32.9%)
33.8%prior 77
Dusk11 (3.5%)
-21.4%prior 14
Dark - roadway not lighted10 (3.2%)
-50.0%prior 20
Dawn5 (1.6%)
-16.7%prior 6
Dark - unknown roadway lighting2 (0.6%)
-77.8%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry238 (75.8%)
10.2%prior 216
Wet43 (13.7%)
-29.5%prior 61
Snow27 (8.6%)
Ice4 (1.3%)
-42.9%prior 7
Slush2 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 11.7%, from 556 to 621. While TOYOTA remained the top make, its involvement decreased by 14.3% from 106 to 91 vehicles, whereas HONDA and FORD involvement increased by 25.4% (from 63 to 79) and 28.3% (from 46 to 59) respectively. In terms of persons involved, the 26-34 age group saw a 25.5% increase (from 110 to 138 persons), while the 65+ age group experienced a 19.8% decrease (from 86 to 69 persons).

Top Vehicle Makes (621 vehicles)

1
TOYOTA91 (14.7%)
-14.2%prior 106
2
HONDA79 (12.7%)
25.4%prior 63
3
FORD59 (9.5%)
28.3%prior 46
4
CHEVROLET51 (8.2%)
8.5%prior 47
5
NISSAN46 (7.4%)
7.0%prior 43
6
HYUNDAI39 (6.3%)
30.0%prior 30
7
KIA28 (4.5%)
16.7%prior 24
8
SUBARU23 (3.7%)
0.0%prior 23
9
JEEP23 (3.7%)
21.1%prior 19
10
GMC16 (2.6%)
-20.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (605 persons with recorded sex)

Male321 (53.1%)
0.3%prior 320
Female284 (46.9%)
13.6%prior 250

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone increased by 22.7%, from 132 to 162 incidents, maintaining its status as the most frequent speed zone for crashes. Crashes in the 10 mph zone saw a significant 116.7% increase, rising from 6 to 13 incidents. Conversely, crashes in the 65 mph speed zone decreased by 18.2%, from 22 to 18 incidents. No fatalities were reported within the specific speed zone data for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 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: 2025-12-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-12-01 through 2025-12-31 (31 days)
  • Geographic scope: FALL RIVER, MA
  • Total crash records analyzed: 316
  • Total persons involved: 758
  • Total vehicles involved: 621

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: December 2025." Published June 21, 2026. Reporting period: 2025-12-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fall-river/december-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 — December 2025 | ThatCarHitMe.com