Monthly Traffic Safety Analysis

60 CRASHES IN
BELLINGHAM, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

In October 2023, Bellingham experienced 60 crashes, a slight increase from 59 crashes in October 2022, representing a 1.7% rise. The most notable shift was a significant increase in total injuries, which rose by 142.9% from 7 in the prior year to 17 in the current period.

60

1.7%was 59

Total Crash Events

0

Persons Killed

17

142.9%was 7

Persons Injured

5

25.0%was 4

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. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend shows a slight increase in total crashes year-over-year, rising from 59 to 60, a 1.7% increase. More significantly, total injuries increased by 142.9%, from 7 in October 2022 to 17 in October 2023.

5

Hit-and-Run Crashes — October 2023

25.0% vs prior (4)

Hit-and-run crashes increased from 4 in October 2022 to 5 in October 2023, representing a 25% increase in count. The hit-and-run rate also rose from 6.8% to 8.3% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

17

Motorists Injured

Prior: 7142.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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 Monday with 15 crashes in October 2022 to Sunday with 14 crashes in October 2023. The peak hour for crashes also shifted, from 3 PM with 9 crashes in the prior period to 6 PM with 8 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities reported in either October 2022 or October 2023. Total injuries increased from 7 to 17 year-over-year. Minor injuries more than doubled, rising from 3 in October 2022 to 7 in October 2023, while serious injuries decreased from 1 to 0.

Outcome by Severity (Crash Events)

Minor Injury7minor injury crashes11.7%
133.3%prior 3
Possible Injury1possible injury crashes1.7%
-50.0%prior 2
No Injury49no injury crashes81.7%
-7.5%prior 53

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' increased from 14 to 17, a 21.4% rise in count. 'Inattention' decreased by 20% in count, from 10 crashes to 8 crashes. 'Followed too closely' crashes saw a 150% increase in count, rising from 2 to 5 year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving17 (28.3%)21.4%prior 14
Inattention8 (13.3%)-20.0%prior 10
Failed to yield right of way7 (11.7%)16.7%prior 6
Followed too closely5 (8.3%)
Other improper action3 (5%)
Over-correcting/over-steering2 (3.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.3%)
Failure to keep in proper lane or running off road1 (1.7%)
Distracted1 (1.7%)
Glare1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Daylight' conditions decreased from 45 in October 2022 to 37 in October 2023, while crashes in 'Dark - lighted roadway' conditions increased from 11 to 15. Crashes on 'Wet' road surfaces decreased from 14 to 8, whereas those on 'Dry' surfaces increased from 45 to 52.

Weather

Clear44 (74.6%)
18.9%prior 37
Rain5 (8.5%)
0.0%prior 5
Clear/Cloudy3 (5.1%)
-40.0%prior 5
Clear/Unknown2 (3.4%)
Cloudy2 (3.4%)
-60.0%prior 5
Rain/Unknown1 (1.7%)
Cloudy/Rain1 (1.7%)
Rain/Cloudy1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight37 (61.7%)
-17.8%prior 45
Dark - lighted roadway15 (25.0%)
36.4%prior 11
Dark - roadway not lighted3 (5.0%)
Dusk3 (5.0%)
Dark - unknown roadway lighting1 (1.7%)
Dawn1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry52 (86.7%)
15.6%prior 45
Wet8 (13.3%)
-42.9%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

FORD-involved crashes saw a significant increase, rising from 10 in October 2022 to 19 in October 2023, making it the most frequent make in the current period. TOYOTA-involved crashes decreased from 16 to 12, and HONDA-involved crashes decreased from 14 to 12. The 0-15 age group saw a substantial increase in persons involved, rising from 5 to 15.

Top Vehicle Makes (121 vehicles)

1
FORD19 (15.7%)
90.0%prior 10
2
CHEVROLET18 (14.9%)
20.0%prior 15
3
TOYOTA12 (9.9%)
-25.0%prior 16
4
HONDA12 (9.9%)
-14.3%prior 14
5
JEEP8 (6.6%)
14.3%prior 7
6
GMC8 (6.6%)
60.0%prior 5
7
HYUNDAI6 (5%)
8
VOLKSWAGEN6 (5%)
9
NISSAN4 (3.3%)
-55.6%prior 9
10
RAM3 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

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

Sex Distribution (135 persons with recorded sex)

Male69 (51.1%)
-4.2%prior 72
Female66 (48.9%)
50.0%prior 44

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone increased from 11 in October 2022 to 24 in October 2023. Conversely, crashes in the 35 mph zone decreased from 20 to 16. There were no fatal crashes recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: BELLINGHAM, MA
  • Total crash records analyzed: 60
  • Total persons involved: 152
  • Total vehicles involved: 121

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: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/bellingham/october-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 — October 2023 | ThatCarHitMe.com