Monthly Traffic Safety Analysis

36 CRASHES IN
BELLINGHAM, MA
FEBRUARY 2023

All metrics benchmarked againstFebruary 2022

In February 2023, Bellingham experienced 36 crashes, an increase from 32 crashes in February 2022, representing a 12.5% rise. The most notable shift was the increase in total fatalities from 0 in the prior year to 1 in the current year, alongside a substantial 220% increase in total injuries.

36

12.5%was 32

Total Crash Events

1

Persons Killed

16

220.0%was 5

Persons Injured

1

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in Bellingham shows an upward trend year-over-year. Total crashes increased by 12.5%, from 32 to 36, and total injuries rose significantly from 5 to 16. Fatalities also increased from 0 to 1.

1

Hit-and-Run Crashes — February 2023

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 in both periods. Consequently, the hit-and-run rate saw a slight decrease from 3.1% in February 2022 to 2.8% in February 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

1

Pedestrians Injured

Prior: 0%

15

Motorists Injured

Prior: 5200.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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 Monday in both periods, with 7 crashes recorded. However, the peak crash hour shifted from 8 AM in February 2022 to 1 PM in February 2023, with both hours recording 5 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased year-over-year, with the number of fatal crashes rising from 0 to 1 and serious injury crashes from 0 to 1. The proportion of crashes resulting in no injury decreased from 90.6% in the prior period to 75% in the current period, indicating a higher severity distribution.

Outcome by Severity (Crash Events)

Fatal1fatal crashes2.8%
Serious Injury1serious injury crashes2.8%
Minor Injury5minor injury crashes13.9%
150.0%prior 2
Possible Injury2possible injury crashes5.6%
100.0%prior 1
No Injury27no injury crashes75%
-6.9%prior 29

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record

Top Contributing Factors

Comparing contributing factors, 'No improper driving' decreased from 10 crashes to 5 crashes, a 50% decrease in count. 'Inattention' also saw a decrease from 7 to 5 crashes. Conversely, 'Other improper action' increased significantly from 1 crash to 4 crashes, a 300% increase in count, and 'Distracted' crashes rose from 1 to 3, a 200% increase in count.

Officer-Reported Primary Contributing Cause

No improper driving5 (13.9%)-50.0%prior 10
Inattention5 (13.9%)-28.6%prior 7
Other improper action4 (11.1%)
Distracted3 (8.3%)
Failed to yield right of way3 (8.3%)-40.0%prior 5
Failure to keep in proper lane or running off road3 (8.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (5.6%)
Illness1 (2.8%)
Driving too fast for conditions1 (2.8%)
Followed too closely1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 21 to 29, while those on wet road surfaces decreased from 8 to 5. Crashes in dark-lighted roadway conditions saw a notable increase from 2 to 10, whereas daylight crashes slightly decreased from 24 to 22.

Weather

Clear29 (82.9%)
38.1%prior 21
Cloudy/Rain3 (8.6%)
Clear/Cloudy1 (2.9%)
Cloudy1 (2.9%)
Snow1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash

Lighting

Daylight22 (61.1%)
-8.3%prior 24
Dark - lighted roadway10 (27.8%)
Dark - roadway not lighted2 (5.6%)
Dusk2 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field

Road Surface

Dry30 (83.3%)
57.9%prior 19
Wet5 (13.9%)
-37.5%prior 8
Snow1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Road surface condition field

Vehicles & Demographics

The top-ranked vehicle make involved in crashes shifted, with Ford increasing from 7 to 12 crashes and moving to the top spot, while Toyota remained at 12 crashes. Among persons involved, the 21-25 age group saw a significant increase from 6 to 19 persons, and the 0-15 age group appeared with 5 persons in the current period, having none in the prior period.

Top Vehicle Makes (70 vehicles)

1
FORD12 (17.1%)
71.4%prior 7
2
TOYOTA10 (14.3%)
-16.7%prior 12
3
HONDA6 (8.6%)
-33.3%prior 9
4
NISSAN6 (8.6%)
5
CHEVROLET5 (7.1%)
-16.7%prior 6
6
JEEP4 (5.7%)
7
HYUNDAI4 (5.7%)
8
DODGE4 (5.7%)
-33.3%prior 6
9
SUBARU3 (4.3%)
10
KIA2 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Vehicle unit records

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

Sex Distribution (88 persons with recorded sex)

Male52 (59.1%)
33.3%prior 39
Female36 (40.9%)
56.5%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones increased from 9 to 14, while crashes in 35 mph zones decreased from 11 to 7. A fatal crash occurred in a 65 mph zone in the current period, which had 3 crashes, compared to 0 fatal crashes in the prior period's single crash in a 65 mph zone.

Fatal crashes by zone: 65 mph: 1 of 3 (33.333%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-02-01 through 2023-02-28 (28 days)
  • Geographic scope: BELLINGHAM, MA
  • Total crash records analyzed: 36
  • Total persons involved: 93
  • Total vehicles involved: 70

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: February 2023." Published June 21, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/bellingham/february-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

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Bellingham, MA Crash Report — February 2023 | ThatCarHitMe.com