Monthly Traffic Safety Analysis

23 CRASHES IN
NORTH ATTLEBOROUGH, MA
JANUARY 2025

All metrics benchmarked againstJanuary 2024

Total crashes in January 2025 were 23, a significant decrease of 54% compared to 50 crashes in January 2024. This period saw a notable reduction in total injuries, falling from 11 to 6, marking a 45.45% decrease. The most significant year-over-year shift was the substantial decline in overall crash incidents.

23

▼ -54.0%was 50

Total Crash Events

0

Persons Killed

6

▼ -45.5%was 11

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 · 2025-01-01 to 2025-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the trend for crashes in January shows a substantial decrease year-over-year. Total crashes fell from 50 in January 2024 to 23 in January 2025, representing a 54% reduction. Similarly, total injuries decreased by 45.45%, from 11 to 6.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

6

Motorists Injured

Prior: 11↓-45.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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 10 incidents in January 2024 to Thursday with 6 incidents in January 2025. The peak hour also changed, moving from 2 PM with 7 crashes in the prior period to 5 PM with 5 crashes in the current period. This indicates a shift in the most frequent crash times.

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

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

Crash Severity Breakdown

There were no fatal crashes in either January 2024 or January 2025. The proportion of minor injury crashes decreased from 16% (8 crashes) in January 2024 to 8.7% (2 crashes) in January 2025. Possible injury crashes saw a proportional increase from 4% (2 crashes) to 8.7% (2 crashes), while crashes with no injuries remained proportionally stable, decreasing slightly from 80% to 78.3%.

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes8.7%
↓-75.0%prior 8
Possible Injury2possible injury crashes8.7%
→0.0%prior 2
No Injury18no injury crashes78.3%
↓-55.0%prior 40

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

The count of crashes attributed to "Driving too fast for conditions" decreased from 9 in January 2024 to 1 in January 2025, an 88.9% reduction in count. "Inattention" crashes also saw a significant drop from 9 to 2, a 77.8% decrease. "Followed too closely" remained the top contributing factor in January 2025 with 7 crashes, down from 8 in the prior year.

Officer-Reported Primary Contributing Cause

Followed too closely7 (30.4%)↓-12.5%prior 8
No improper driving6 (26.1%)↓-33.3%prior 9
Inattention2 (8.7%)↓-77.8%prior 9
Failed to yield right of way2 (8.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.3%)
Other improper action1 (4.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.3%)
Driving too fast for conditions1 (4.3%)↓-88.9%prior 9

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

Road & Environmental Conditions

Crashes occurring in "Clear" weather conditions decreased from 17 in January 2024 to 7 in January 2025, while "Clear/Clear" conditions saw an increase from 4 to 10 crashes. Incidents on "Dry" road surfaces decreased from 22 to 16, and crashes on "Wet" surfaces dropped from 12 to 3. Daylight crashes decreased from 30 to 10, while dusk crashes increased from 1 to 5.

Weather

Clear/Clear10 (43.5%)
Clear7 (30.4%)
↓-58.8%prior 17
Snow2 (8.7%)
↓-81.8%prior 11
Snow/Snow1 (4.3%)
Rain/Rain1 (4.3%)
Rain1 (4.3%)
↓-85.7%prior 7
Snow/Cloudy1 (4.3%)

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

Lighting

Daylight10 (43.5%)
↓-66.7%prior 30
Dusk5 (21.7%)
Dark - lighted roadway4 (17.4%)
↓-55.6%prior 9
Dark - roadway not lighted2 (8.7%)
↓-66.7%prior 6
Dark - unknown roadway lighting1 (4.3%)
Dawn1 (4.3%)

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

Road Surface

Dry16 (69.6%)
↓-27.3%prior 22
Snow3 (13.0%)
↓-66.7%prior 9
Wet3 (13.0%)
↓-75.0%prior 12
Ice1 (4.3%)

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

Vehicles & Demographics

Top Vehicle Makes (47 vehicles)

1
TOYOTA10 (21.3%)
↓-41.2%prior 17
2
HYUNDAI6 (12.8%)
3
FORD5 (10.6%)
↓-58.3%prior 12
4
HONDA3 (6.4%)
↓-40.0%prior 5
5
KIA2 (4.3%)
6
BMW2 (4.3%)
7
JEEP2 (4.3%)
8
VOLKSWAGEN2 (4.3%)
9
MERCEDESBENZ AU1 (2.1%)
10
MITSUBISHI AUTO1 (2.1%)

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

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

Sex Distribution (49 persons with recorded sex)

Male33 (67.3%)
↓-46.8%prior 62
Female16 (32.7%)
↓-57.9%prior 38

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

Speed Limit Zones

Crashes occurring in 30 mph zones decreased substantially from 18 in January 2024 to 2 in January 2025, an 88.9% reduction. Crashes in 65 mph zones also saw a significant decrease, falling from 17 to 6. There were no fatal crashes reported in any speed zone during either period.

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

Data Coverage

  • Reporting period: 2025-01-01 through 2025-01-31 (31 days)
  • Geographic scope: NORTH ATTLEBOROUGH, MA
  • Total crash records analyzed: 23
  • Total persons involved: 51
  • Total vehicles involved: 47

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). "NORTH ATTLEBOROUGH, MA Crash Intelligence Report: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-attleborough/january-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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North Attleborough, MA Crash Report — January 2025 | ThatCarHitMe.com