Monthly Traffic Safety Analysis

43 CRASHES IN
BELLINGHAM, MA
APRIL 2025

All metrics benchmarked againstApril 2024

Total crashes in Bellingham decreased by 14% year-over-year, from 50 crashes in April 2024 to 43 crashes in April 2025. This period also saw a significant reduction in total injuries, decreasing from 17 to 10, a 41.2% decline.

43

-14.0%was 50

Total Crash Events

0

Persons Killed

10

-41.2%was 17

Persons Injured

2

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

Trend Summary

Overall, crash trends in Bellingham show a notable decrease year-over-year. Total crashes fell by 14%, from 50 in April 2024 to 43 in April 2025. Concurrently, the number of injured persons decreased by 41.2%, from 17 to 10. Fatalities remained at 0 in both periods.

2

Hit-and-Run Crashes — April 2025

0.0% vs prior (2)

The number of hit-and-run crashes remained constant at 2 in both April 2024 and April 2025. However, the hit-and-run rate increased slightly from 4% in the prior period to 4.7% in the current period, due to the overall decrease in total crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

10

Motorists Injured

Prior: 17-41.2%

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 Monday, with 11 crashes in April 2024, to Friday, with 9 crashes in April 2025. The peak hour also shifted, from 3 PM with 8 crashes in the prior period to 4 PM with 6 crashes in the current period. Crashes on Mondays decreased from 11 to 5, while crashes on Saturdays increased from 2 to 6.

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

Fatal crashes remained at zero in both April 2024 and April 2025. The number of crashes resulting in minor injuries (B) decreased from 8 in the prior period to 0 in the current period, while crashes with possible injuries (C) increased from 4 to 5. Overall, the total number of injured persons decreased by 41.2%, from 17 in April 2024 to 10 in April 2025.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.3%
Possible Injury5possible injury crashes11.6%
25.0%prior 4
No Injury36no injury crashes83.7%
-5.3%prior 38

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

No improper driving remained the most cited contributing factor, with its count increasing from 15 crashes in April 2024 to 17 crashes in April 2025. Failed to yield right of way saw a significant increase in count, rising from 1 crash to 5 crashes. Conversely, Inattention decreased from 6 crashes to 4 crashes year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving17 (39.5%)13.3%prior 15
Failed to yield right of way5 (11.6%)
Inattention4 (9.3%)-33.3%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (7%)
Other improper action3 (7%)
Followed too closely2 (4.7%)
Made an improper turn1 (2.3%)
Failure to keep in proper lane or running off road1 (2.3%)
Fatigued/asleep1 (2.3%)
Disregarded traffic signs, signals, road markings1 (2.3%)

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 from 32 to 28, while crashes in rainy conditions decreased from 8 to 3. Similarly, crashes on dry road surfaces decreased from 35 to 32, and on wet surfaces from 13 to 9. Crashes during daylight hours also saw a reduction, falling from 39 to 34.

Weather

Clear28 (66.7%)
-12.5%prior 32
Cloudy7 (16.7%)
Rain3 (7.1%)
-62.5%prior 8
Cloudy/Rain2 (4.8%)
Clear/Clear1 (2.4%)
Sleet, hail (freezing rain or drizzle)/Sleet, hail (freezing rain or drizzle)1 (2.4%)

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

Lighting

Daylight34 (81.0%)
-12.8%prior 39
Dark - lighted roadway4 (9.5%)
-50.0%prior 8
Dusk3 (7.1%)
Dark - roadway not lighted1 (2.4%)

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

Road Surface

Dry32 (76.2%)
-8.6%prior 35
Wet9 (21.4%)
-30.8%prior 13
Ice1 (2.4%)

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 97 in April 2024 to 81 in April 2025, a 16.5% reduction. Toyota remained the top make, with its count increasing slightly from 20 to 21. Ford saw a decrease in involvement, from 12 vehicles to 8, and Honda also decreased from 8 to 6.

Top Vehicle Makes (81 vehicles)

1
TOYOTA21 (25.9%)
5.0%prior 20
2
FORD8 (9.9%)
-33.3%prior 12
3
JEEP6 (7.4%)
4
NISSAN6 (7.4%)
20.0%prior 5
5
HONDA6 (7.4%)
-25.0%prior 8
6
DODGE4 (4.9%)
-33.3%prior 6
7
SUBARU4 (4.9%)
-42.9%prior 7
8
CHEVROLET3 (3.7%)
9
PONT2 (2.5%)
10
GMC2 (2.5%)

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

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

Sex Distribution (91 persons with recorded sex)

Male57 (62.6%)
-17.4%prior 69
Female34 (37.4%)
-19.0%prior 42

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 occurring in 35 mph speed zones saw a substantial decrease, falling from 21 crashes in April 2024 to 10 crashes in April 2025. Conversely, crashes in 25 mph zones increased from 11 to 15. All speed zones reported zero fatal crashes in both periods.

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: BELLINGHAM, MA
  • Total crash records analyzed: 43
  • Total persons involved: 97
  • Total vehicles involved: 81

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). "BELLINGHAM, 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/bellingham/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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Bellingham, MA Crash Report — April 2025 | ThatCarHitMe.com