Monthly Traffic Safety Analysis

221 CRASHES IN
FALL RIVER, MA
APRIL 2025

All metrics benchmarked againstApril 2024

Total crashes in Fall River, MA, for April 2025 were 221, a decrease from 246 crashes in April 2024. This represents a 10.16% reduction in overall crashes year-over-year. The most notable shift was a 19.6% decrease in total injuries, falling from 102 to 82.

221

-10.2%was 246

Total Crash Events

0

Persons Killed

82

-19.6%was 102

Persons Injured

36

-7.7%was 39

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 · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for April 2025 shows a downward trend compared to April 2024. Total crashes decreased by 25, representing a 10.16% reduction. Total injuries also saw a significant decline, dropping by 20 individuals, or 19.6%, year-over-year.

36

Hit-and-Run Crashes — April 2025

-7.7% vs prior (39)

The number of hit-and-run crashes decreased by 3, from 39 in April 2024 to 36 in April 2025. Despite this decrease in count, the hit-and-run rate increased slightly from 15.9% to 16.3% of total crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 6-83.3%

81

Motorists Injured

Prior: 95-14.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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 43 incidents in April 2024 to Tuesday with 41 incidents in April 2025. The peak hour for crashes also changed, moving from 6 PM with 20 incidents in the prior year to 3 PM with 22 incidents in the current year. Overall, total crashes decreased from 246 to 221, and total injuries decreased from 102 to 82.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both April 2025 and April 2024. Serious injuries decreased from 6 (2.4% share of crashes) in April 2024 to 4 (1.8% share of crashes) in April 2025. Minor injuries also saw a reduction, dropping from 43 to 38 year-over-year, while possible injuries decreased from 17 to 9.

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes1.8%
-33.3%prior 6
Minor Injury38minor injury crashes17.2%
-11.6%prior 43
Possible Injury9possible injury crashes4.1%
-47.1%prior 17
No Injury155no injury crashes70.1%
-5.5%prior 164

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "No improper driving" decreased by 26 incidents, from 79 in April 2024 to 53 in April 2025. "Inattention" as a factor also saw a reduction of 10 incidents, falling from 33 to 23. Conversely, "Followed too closely" increased by 10 incidents, rising from 13 to 23 year-over-year, and "Failure to keep in proper lane or running off road" increased by 6 incidents, from 17 to 23.

Officer-Reported Primary Contributing Cause

No improper driving53 (24%)-32.9%prior 79
Failure to keep in proper lane or running off road23 (10.4%)35.3%prior 17
Followed too closely23 (10.4%)76.9%prior 13
Inattention23 (10.4%)-30.3%prior 33
Other improper action18 (8.1%)63.6%prior 11
Failed to yield right of way17 (7.7%)-19.0%prior 21
Disregarded traffic signs, signals, road markings10 (4.5%)25.0%prior 8
Operating defective equipment4 (1.8%)
Exceeded authorized speed limit4 (1.8%)
Made an improper turn4 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Clear" weather conditions decreased by 42 incidents, from 148 in April 2024 to 106 in April 2025. Crashes during "Daylight" conditions also saw a decrease, falling from 181 to 172. The number of crashes on "Wet" road surfaces remained stable at 39 incidents in both periods, while crashes on "Dry" surfaces decreased by 25.

Weather

Clear106 (48.0%)
-28.4%prior 148
Clear/Clear28 (12.7%)
Clear/Cloudy28 (12.7%)
-12.5%prior 32
Rain17 (7.7%)
-34.6%prior 26
Cloudy16 (7.2%)
-11.1%prior 18
Clear/Unknown10 (4.5%)
0.0%prior 10
Cloudy/Rain4 (1.8%)
Rain/Cloudy2 (0.9%)
Rain/Rain2 (0.9%)
Rain/Unknown2 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash

Lighting

Daylight172 (78.2%)
-5.0%prior 181
Dark - lighted roadway37 (16.8%)
-2.6%prior 38
Dusk4 (1.8%)
-73.3%prior 15
Dark - roadway not lighted3 (1.4%)
-66.7%prior 9
Dawn2 (0.9%)
Dark - unknown roadway lighting1 (0.5%)
Other1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field

Road Surface

Dry180 (81.4%)
-12.2%prior 205
Wet39 (17.6%)
0.0%prior 39
Other1 (0.5%)
Water (standing, moving)1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 470 in April 2024 to 437 in April 2025. TOYOTA remained the top vehicle make involved, increasing slightly from 71 to 73, while HONDA vehicles involved decreased from 52 to 30. The 16-20 age group saw a notable decrease in persons involved, dropping from 71 to 34.

Top Vehicle Makes (437 vehicles)

1
TOYOTA73 (16.7%)
2.8%prior 71
2
FORD44 (10.1%)
-15.4%prior 52
3
CHEVROLET43 (9.8%)
48.3%prior 29
4
NISSAN40 (9.2%)
-2.4%prior 41
5
HONDA30 (6.9%)
-42.3%prior 52
6
HYUNDAI27 (6.2%)
-6.9%prior 29
7
KIA24 (5.5%)
20.0%prior 20
8
GMC17 (3.9%)
88.9%prior 9
9
DODGE13 (3%)
44.4%prior 9
10
JEEP12 (2.7%)
-29.4%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records

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

Sex Distribution (430 persons with recorded sex)

Male243 (56.5%)
-17.3%prior 294
Female187 (43.5%)
-8.8%prior 205

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones saw a significant decrease of 49 incidents, falling from 98 in April 2024 to 49 in April 2025. Conversely, crashes in 25 mph zones increased by 10 incidents, from 90 to 100. Crashes in 55 mph zones also increased, rising from 7 to 16 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-04-01 through 2025-04-30 (30 days)
  • Geographic scope: FALL RIVER, MA
  • Total crash records analyzed: 221
  • Total persons involved: 549
  • Total vehicles involved: 437

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: April 2025." Published June 21, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fall-river/april-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 — April 2025 | ThatCarHitMe.com