ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · FALL RIVER, MA · NOVEMBER 2023
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/fall-river/november-2023-report
Monthly Traffic Safety Analysis
259 CRASHES IN
FALL RIVER, MA
NOVEMBER 2023
In November 2023, Fall River, MA experienced 259 crashes, a 13.1% increase compared to 229 crashes in November 2022. The most notable year-over-year shift was the increase in total fatalities from 0 in the prior period to 1 in the current period.
259
▲ 13.1%was 229
Total Crash Events
1
Persons Killed
95
▲ 50.8%was 63
Persons Injured
32
▲ 52.4%was 21
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. 10 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in Fall River, MA trended upwards in November 2023 compared to November 2022. Total crashes increased by 30, from 229 to 259, representing a 13.1% rise. Fatalities also increased from 0 to 1, while total injuries rose by 50.8%, from 63 to 95.
32
Hit-and-Run Crashes — November 2023
▲ 52.4% vs prior (21)
Hit-and-run crashes increased significantly, rising from 21 incidents in November 2022 to 32 incidents in November 2023, a 52.4% increase in count. The hit-and-run rate also increased from a 9.2% share of all crashes in the prior period to a 12.4% share in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Other Killed
8
Pedestrians Injured
86
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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 Tuesday with 51 crashes in November 2022 to Wednesday with 47 crashes in November 2023. Similarly, the peak hour for crashes moved from 3 PM with 25 crashes in the prior period to 12 PM with 22 crashes in the current period. While the peak day and hour shifted, the counts for both peak periods decreased year-over-year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The most significant change in crash severity was the occurrence of 1 fatal crash and 1 fatality in November 2023, compared to 0 fatal crashes and 0 fatalities in November 2022. Injury crashes also saw increases, with serious injuries (A) rising from 4 to 6, minor injuries (B) from 31 to 49, and possible injuries (C) from 12 to 21. The proportion of crashes resulting in serious injury (A) increased from a 1.7% share in the prior period to a 2.3% share in the current period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'No improper driving' increased by 28 crashes, from 49 to 77, a 57.1% increase in count. 'Followed too closely' saw a 64.3% increase in count, rising from 14 to 23 crashes. Conversely, 'Failed to yield right of way' decreased by 7 crashes, from 25 to 18, representing a 28% decrease in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The number of crashes occurring in 'Clear' weather conditions increased from 159 in November 2022 to 185 in November 2023. Crashes on 'Dry' road surfaces also rose from 197 to 233 year-over-year. However, crashes in 'Wet' conditions decreased from 30 to 23, and crashes in 'Rain' decreased from 13 to 9.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 540 in November 2022 to 638 in November 2023. Notably, the count of persons in the '0-15' age group increased from 28 to 44, and in the '35-44' age group from 71 to 100. Toyota remained the top vehicle make involved, increasing from 66 to 81 vehicles, while Ford decreased from 49 to 41 vehicles involved.
Top Vehicle Makes (505 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records
104 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (502 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed zones increased from 56 in November 2022 to 100 in November 2023. Conversely, crashes in 30 mph speed zones decreased from 109 to 92. The 65 mph speed zone recorded 1 fatal crash in November 2023, compared to 0 fatal crashes in the prior period, with total crashes in this zone increasing from 20 to 24.
Fatal crashes by zone: 65 mph: 1 of 24 (4.167%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-11-01 through 2023-11-30 (30 days)
- Geographic scope: FALL RIVER, MA
- Total crash records analyzed: 259
- Total persons involved: 638
- Total vehicles involved: 505
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 2023." Published June 21, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fall-river/november-2023-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-11-01 – 2023-11-30
Generated: June 21, 2026 · All rights reserved