ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BELLINGHAM, MA · 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/bellingham/2022-annual-report
Yearly Traffic Safety Analysis
551 CRASHES IN
BELLINGHAM, MA
2022
In 2022, Bellingham recorded 551 total vehicle crashes, a 4.8% decrease from the 579 crashes reported in 2021. Despite the overall decline in collisions, the number of persons injured rose by 27.4% from 117 to 149, and total fatalities doubled from one to two. The most significant statistical shift was a 177.8% increase in hit-and-run incidents, which rose from 9 in the prior year to 25 in the current period.
551
▼ -4.8%was 579
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
149
▲ 27.4%was 117
Persons Injured
25
▲ 177.8%was 9
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 8 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic collisions in Bellingham saw a modest year-over-year decrease of 4.8%, falling from 579 to 551. However, this downward trend in crash volume was accompanied by a notable increase in crash severity. The number of individuals injured in crashes grew by 27.4% from 117 to 149, and the number of fatalities increased from one to two.
25
Hit-and-Run Crashes — 2022
▲ 177.8% vs prior (9)
Hit-and-run incidents increased significantly between the two periods. The total count of hit-and-run crashes rose from 9 in 2021 to 25 in 2022, a 177.8% increase. Consequently, the hit-and-run rate, as a percentage of all crashes, nearly tripled from 1.6% to 4.5% year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
2
Motorists Killed
2
Pedestrians Injured
147
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The daily and hourly patterns of crashes showed some changes between the two periods. The peak day for crashes shifted from Thursday in 2021 (95 incidents) to Friday in 2022 (102 incidents). The peak hour for collisions remained consistent at the 4 p.m. hour for both years, with 58 crashes in 2022 compared to 62 in 2021.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased from 2021 to 2022. The number of fatal crashes doubled from one to two, raising the fatal crash rate from 0.2% to 0.4% of all collisions. The count of serious injury crashes also nearly doubled, rising from 7 to 13, while the proportion of crashes resulting in no injuries decreased from 83.9% to 80.0%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors—'No improper driving,' 'Inattention,' and 'Failed to yield right of way'—remained the same across both years. However, the count for 'Failed to yield right of way' decreased by 18.0%, from 61 incidents in 2021 to 50 in 2022. The count of crashes attributed to 'Followed too closely' also saw a significant 34.9% drop, from 43 to 28 incidents year-over-year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
A higher proportion of crashes in 2022 occurred in favorable conditions compared to the prior year. Crashes in 'Clear' weather made up 75.3% of the total in 2022, up from 67.4% in 2021. Similarly, incidents on 'Dry' road surfaces accounted for 83.5% of crashes, an increase from 80.1% in the previous year, while crashes on 'Wet' surfaces decreased from 95 to 77.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent, with Toyota, Ford, and Honda leading in both periods. While Toyota's involvement increased slightly from 161 to 168 vehicles, Ford's decreased from 155 to 121. Analysis of persons involved shows a demographic shift, with the 65+ age group's representation growing from 10.8% of all persons in 2021 to 13.8% in 2022.
Top Vehicle Makes (1,037 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
57 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,184 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones shifted slightly year-over-year. Crashes in 35 mph zones decreased from 193 to 165, while those in 40 mph zones increased from 32 to 43. Notably, the location of fatal crashes moved to higher speed zones; in 2022, one fatal crash occurred in a 40 mph zone and another in a 65 mph zone, whereas 2021's single fatal crash was in a 25 mph zone.
Fatal crashes by zone: 40 mph: 1 of 43 (2.326%) · 65 mph: 1 of 25 (4%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: BELLINGHAM, MA
- Total crash records analyzed: 551
- Total persons involved: 1,255
- Total vehicles involved: 1,037
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/bellingham/2022-annual-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved