ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SWANSEA, MA · OCTOBER 2023
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/october-2023-report
Monthly Traffic Safety Analysis
41 CRASHES IN
SWANSEA, MA
OCTOBER 2023
In October 2023, Swansea experienced 41 crashes, a decrease of 16 crashes or 28.1% compared to the 57 crashes recorded in October 2022. The most notable year-over-year shift was the reduction in total fatalities from 1 in the prior period to 0 in the current period.
41
▼ -28.1%was 57
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
16
▼ -38.5%was 26
Persons Injured
2
▲ 100.0%was 1
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.
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
Overall crash data for Swansea indicates a downward trend year-over-year, with total crashes decreasing by 16, from 57 in October 2022 to 41 in October 2023. This decline also extended to total injuries, which fell from 26 to 16, and total fatalities, which decreased from 1 to 0.
2
Hit-and-Run Crashes — October 2023
▲ 100.0% vs prior (1)
Hit-and-run incidents increased year-over-year, with 2 such crashes recorded in October 2023 compared to 1 in October 2022. Consequently, the hit-and-run rate rose from 1.8% of all crashes in the prior period to 4.9% in the current period.
Vulnerable Road User Casualties
0
Motorists Killed
16
Motorists Injured
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 temporal patterns of crashes showed shifts between the two periods. In October 2023, both Sunday and Saturday recorded the highest crash counts with 8 crashes each, whereas in October 2022, Sunday alone had the highest count with 16 crashes. The peak hour for crashes also shifted, with 2 p.m. having 6 crashes in the current period compared to 6 p.m. with 7 crashes in the prior 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
The severity distribution saw a significant improvement year-over-year, with no fatalities recorded in October 2023 compared to 1 fatality in October 2022, reducing the fatal crash rate from 1.75% to 0%. Total injuries decreased from 26 to 16, though serious injuries increased slightly from 2 to 3, while possible injuries decreased from 7 to 2.
Outcome by Severity (Crash Events)
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
The top contributing factors experienced shifts in crash counts. 'Followed too closely' saw a decrease from 12 crashes in October 2022 to 6 crashes in October 2023, and 'Inattention' also decreased from 8 crashes to 2 crashes. Conversely, crashes attributed to 'No improper driving' increased from 8 to 11, making it the most frequent factor in the current period.
Officer-Reported Primary Contributing Cause
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
Crash conditions remained largely consistent, with the majority of incidents occurring in clear weather, daylight, and on dry road surfaces in both periods. Crashes in clear weather decreased from 46 to 32, and those on dry road surfaces decreased from 49 to 34. The number of crashes occurring in dark conditions also saw a reduction, with 'Dark - lighted roadway' incidents falling from 11 to 8, and 'Dark - roadway not lighted' from 6 to 3.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 97 in October 2022 to 66 in October 2023. A notable shift in person demographics was observed in the 16-20 age group, which saw a significant reduction from 29 persons involved in the prior period to 6 in the current period, and the 65+ age group also decreased from 18 to 8. While Ford and Toyota were top makes in both periods, Toyota became the most frequent make in the current period with 9 vehicles, while Ford and Toyota shared the top spot in the prior period with 14 vehicles each.
Top Vehicle Makes (66 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (72 persons with recorded sex)
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 across various speed limits generally decreased in line with the overall reduction in incidents. The 40 mph speed zone saw a decrease from 13 crashes in October 2022 to 9 crashes in October 2023. Conversely, crashes in the 65 mph speed zone increased from 5 to 8. There was 1 fatal crash in the 50 mph zone in the prior period, while no fatal crashes were recorded in any speed zone in the current 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: SWANSEA, MA
- Total crash records analyzed: 41
- Total persons involved: 76
- Total vehicles involved: 66
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: 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/swansea/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-10-01 – 2023-10-31
Generated: June 21, 2026 · All rights reserved