Monthly Traffic Safety Analysis

27 CRASHES IN
REHOBOTH, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, REHOBOTH experienced 27 total crashes, a 10% decrease compared to the 30 crashes recorded in November 2024. While total injuries remained constant at 8 in both periods, a notable shift occurred in DUI-related incidents, which increased from 0 in November 2024 to 1 crash in November 2025.

27

▼ -10.0%was 30

Total Crash Events

0

Persons Killed

8

Persons Injured

0

▼ -100.0%was 1

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. 1 crash with unreported severity is 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

Overall, crashes in REHOBOTH decreased year-over-year, falling from 30 crashes in November 2024 to 27 crashes in November 2025, representing a 10% reduction. Both total fatalities and total injuries remained stable, with 0 fatalities and 8 injuries reported in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

8

Motorists Injured

Prior: 8→0.0%

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 remained Friday in both periods, though the count decreased from 7 crashes in November 2024 to 6 crashes in November 2025. The peak hour shifted from 3 PM with 5 crashes in November 2024 to 6 PM with 4 crashes in November 2025. Overall, the distribution of crashes across days and hours showed minor shifts rather than a significant change in temporal patterns.

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

Fatal crashes remained at 0 in both November 2024 and November 2025. There was a decrease in serious injury crashes, from 2 (6.7% share) in the prior period to 1 (3.7% share) in the current period. Minor injury crashes also decreased from 2 (6.7% share) to 1 (3.7% share), while possible injury crashes decreased from 3 (10% share) to 2 (7.4% share).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.7%
↓-50.0%prior 2
Minor Injury1minor injury crashes3.7%
↓-50.0%prior 2
Possible Injury2possible injury crashes7.4%
↓-33.3%prior 3
No Injury22no injury crashes81.5%
↓-4.3%prior 23

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 crashes attributed to 'No improper driving' increased from 11 in November 2024 to 19 in November 2025. Conversely, crashes where 'Failed to yield right of way' was a factor decreased from 3 to 1. Factors like 'Other improper action' (3 crashes) and 'Followed too closely' (2 crashes) were present in the prior period but not listed in the current period's top factors.

Officer-Reported Primary Contributing Cause

No improper driving19 (70.4%)↑72.7%prior 11
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (7.4%)
Failure to keep in proper lane or running off road2 (7.4%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (3.7%)
Inattention1 (3.7%)
Failed to yield right of way1 (3.7%)
Disregarded traffic signs, signals, road markings1 (3.7%)

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 decreased from 24 in November 2024 to 19 in November 2025, while 'Cloudy' weather crashes increased from 2 to 4. For lighting conditions, 'Daylight' crashes decreased from 13 to 9, and crashes in 'Dark - roadway not lighted' increased from 11 to 12. The number of crashes on 'Dry' road surfaces decreased from 27 to 23, while 'Wet' surface crashes increased from 2 to 4.

Weather

Clear19 (73.1%)
↓-20.8%prior 24
Cloudy4 (15.4%)
Clear/Clear1 (3.8%)
Cloudy/Rain1 (3.8%)
Rain1 (3.8%)

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

Lighting

Dark - roadway not lighted12 (44.4%)
↑9.1%prior 11
Daylight9 (33.3%)
↓-30.8%prior 13
Dark - lighted roadway3 (11.1%)
Dark - unknown roadway lighting2 (7.4%)
Dawn1 (3.7%)

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

Road Surface

Dry23 (85.2%)
↓-14.8%prior 27
Wet4 (14.8%)

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

Vehicles & Demographics

Top Vehicle Makes (34 vehicles)

1
TOYOTA9 (26.5%)
↑28.6%prior 7
2
HONDA4 (11.8%)
3
BMW3 (8.8%)
4
FORD3 (8.8%)
↓-50.0%prior 6
5
HYUNDAI2 (5.9%)
6
CHEVROLET2 (5.9%)
7
NISSAN2 (5.9%)
8
JEEP2 (5.9%)
9
VOLVO1 (2.9%)
10
AUDI1 (2.9%)

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

Sex Distribution (43 persons with recorded sex)

Male24 (55.8%)
↓-31.4%prior 35
Female19 (44.2%)
↓-13.6%prior 22

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 the 40 mph speed zone saw the largest decrease, falling from 12 in November 2024 to 6 in November 2025. Conversely, crashes in the 35 mph speed zone increased from 5 to 8, and in the 50 mph zone, they increased from 3 to 6. Crashes were also recorded in 10 mph and 15 mph zones in the current period (1 crash each), which were not present in the prior 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: REHOBOTH, MA
  • Total crash records analyzed: 27
  • Total persons involved: 43
  • Total vehicles involved: 34

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). "REHOBOTH, 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/rehoboth/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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Rehoboth, MA Crash Report — November 2025 | ThatCarHitMe.com