ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SWANSEA, MA · NOVEMBER 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/swansea/november-2022-report
Monthly Traffic Safety Analysis
62 CRASHES IN
SWANSEA, MA
NOVEMBER 2022
In November 2022, Swansea experienced 62 total crashes, a decrease of 4.6% compared to the 65 crashes recorded in November 2021. The most significant year-over-year shift was the occurrence of 1 fatality in the current period, whereas no fatalities were reported in the prior period. Total injuries also decreased from 19 to 14.
62
▼ -4.6%was 65
Total Crash Events
1
Persons Killed
14
▼ -26.3%was 19
Persons Injured
2
▼ -50.0%was 4
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the trend for total crashes in Swansea shows a slight decrease, with 62 crashes in November 2022 compared to 65 in November 2021, representing a 4.6% reduction. However, a concerning trend is the emergence of 1 fatality in the current period, compared to 0 fatalities in the prior year. Total injuries also decreased by 26.3%, from 19 to 14.
2
Hit-and-Run Crashes — November 2022
▼ -50.0% vs prior (4)
Hit-and-run crashes decreased from 4 incidents in November 2021 to 2 incidents in November 2022. Consequently, the hit-and-run rate decreased from 6.2% to 3.2% of all crashes, indicating a downward trend for this type of incident.
Vulnerable Road User Casualties
1
Motorists Killed
14
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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 Friday with 12 crashes in November 2021 to Tuesday with 14 crashes in November 2022. While the peak hour remained 3 PM or 4 PM with 7 crashes in both periods, there was a notable decrease in crashes on Fridays, from 12 in the prior period to 3 in the current period. Conversely, crashes on Sundays, Mondays, Tuesdays, and Wednesdays all increased by 3 or 4 incidents each.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution saw a significant change with the introduction of 1 fatal crash (1.6% of all crashes) and 1 fatality in November 2022, compared to no fatal crashes or fatalities in November 2021. Serious injuries, which accounted for 2 incidents (3.1% of crashes) in the prior period, were not reported in the current period. The proportion of possible injury crashes decreased from 12.3% (8 incidents) to 8.1% (5 incidents), while 'no injury' crashes increased their share from 70.8% to 77.4%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'No improper driving,' decreased by 4 incidents from 26 in the prior period to 22 in the current period. 'Inattention' saw the largest increase, rising by 5 incidents from 4 to 9, and its share of crashes more than doubled from 6.2% to 14.5%. Conversely, 'Followed too closely' decreased by 3 incidents, from 11 to 8, and its share dropped from 16.9% to 12.9%.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
There was a shift towards more adverse weather conditions contributing to crashes, with 'Rain' incidents increasing from 1 in November 2021 to 7 in November 2022, while 'Clear' conditions decreased by 13 incidents. Crashes occurring in 'Daylight' decreased from 40 to 34, while those in 'Dark - lighted roadway' increased from 11 to 16. The number of crashes on 'Wet' road surfaces doubled from 6 to 12, indicating a higher proportion of crashes under wet conditions in the current period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 114 in November 2021 to 96 in November 2022. TOYOTA moved from the second to the first most common make involved, increasing by 2 vehicles from 14 to 16, while FORD dropped from first to second, decreasing by 4 vehicles from 15 to 11. The 26-34 age group saw a significant decrease in persons involved, from 27 to 14, while the 35-44 age group increased from 16 to 23 persons involved.
Top Vehicle Makes (96 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records
4 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (116 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph and 40 mph speed limit zones decreased by 5 and 4 incidents respectively, while crashes in the 10 mph, 20 mph, and 50 mph zones each increased by 1 to 3 incidents. Notably, a fatal crash occurred in a 20 mph zone in November 2022, which was the only fatal crash recorded in either period. The 65 mph zone saw a slight increase of 1 crash, from 14 to 15.
Fatal crashes by zone: 20 mph: 1 of 2 (50%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-11-01 through 2022-11-30 (30 days)
- Geographic scope: SWANSEA, MA
- Total crash records analyzed: 62
- Total persons involved: 121
- Total vehicles involved: 96
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). "SWANSEA, MA Crash Intelligence Report: November 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/swansea/november-2022-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: 2022-11-01 – 2022-11-30
Generated: June 21, 2026 · All rights reserved