ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SWANSEA, MA · 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/2023-annual-report
Yearly Traffic Safety Analysis
568 CRASHES IN
SWANSEA, MA
2023
In 2023, Swansea recorded 568 total crashes, a 3.7% decrease from the 590 crashes documented in 2022. During this period, the number of fatalities resulting from these crashes fell from 5 to 2. A notable change was the increase in hit-and-run crashes, which rose from 21 to 33.
568
▼ -3.7%was 590
Total Crash Events
2
▼ -60.0%was 5
Persons Killed
192
▼ -10.3%was 214
Persons Injured
33
▲ 57.1%was 21
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. 13 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, key traffic safety metrics in Swansea showed a downward trend from 2022 to 2023. The total number of crashes decreased by 3.7%, from 590 to 568. The number of people injured in these incidents also fell by 10.3%, from 214 to 192, and total fatalities decreased from 5 to 2.
33
Hit-and-Run Crashes — 2023
▲ 57.1% vs prior (21)
Hit-and-run incidents increased notably from 2022 to 2023. The total count of hit-and-run crashes rose by 57.1%, from 21 to 33. The hit-and-run rate, which measures the percentage of all crashes that are hit-and-runs, also trended upward from 3.6% in 2022 to 5.8% in 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
2
Motorists Killed
1
Pedestrians Injured
191
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In 2023, the peak day for crashes was Thursday with 98 incidents, a change from Wednesday, which was the peak day in 2022 with 100 incidents. The busiest time of day also shifted slightly, with the peak hour for crashes moving from the 4 p.m. hour in 2022 (53 crashes) to the 5 p.m. hour in 2023 (50 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes showed mixed changes year-over-year. The number of fatal crashes decreased from 5 in 2022 to 2 in 2023, with the fatal crash rate falling from 0.85 to 0.35 per 100 crashes. However, crashes resulting in serious injuries increased from 12 to 17, and minor injury crashes rose from 85 to 91. The proportion of crashes with no reported injuries increased from 71.0% to 73.6% of all incidents.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The ranking of top contributing factors changed from 2022 to 2023. 'Failed to yield right of way' became the most cited factor in 2023, with its count increasing from 106 to 120 incidents. 'No improper driving' was the second most common factor in 2023 with 119 incidents, up from 113 the prior year. Crashes attributed to 'Followed too closely' decreased from 95 to 91, and those involving 'Inattention' dropped from 62 to 58 incidents.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained largely consistent, with most incidents in both years occurring in clear weather on dry roads during daylight hours. Crashes in clear weather accounted for 73.6% of the total in 2023, compared to 76.6% in 2022. The proportion of crashes on wet roads increased from 14.1% (83 crashes) in 2022 to 17.2% (98 crashes) in 2023. Incidents in daylight represented 70.1% of crashes in 2023, a slight increase from 68.5% in the previous year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained Toyota, Honda, and Ford, with some shifts in their counts. The number of Toyotas in crashes decreased from 169 to 157, while Hondas increased from 89 to 102. The age demographics of people involved in crashes also changed, with the number of individuals in the 26-34 age group increasing from 198 to 210 and the 55-64 age group growing from 138 to 161. Conversely, the 16-20 age group saw a decrease from 175 to 142 individuals.
Top Vehicle Makes (1,023 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
86 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,164 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes shifted toward higher speed zones in 2023. Incidents in zones of 40 mph or greater accounted for 58.1% of crashes with a recorded speed limit, an increase from 54.6% in 2022. Consequently, crashes in zones of 35 mph or less decreased from 45.4% to 41.9% of the total. The two fatal crashes in 2023 occurred in 30 mph and 65 mph zones, whereas the five fatalities in 2022 were spread across five different speed zones.
Fatal crashes by zone: 30 mph: 1 of 68 (1.471%) · 65 mph: 1 of 81 (1.235%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: SWANSEA, MA
- Total crash records analyzed: 568
- Total persons involved: 1,262
- Total vehicles involved: 1,023
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/swansea/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved