ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · RAYNHAM, MA · APRIL 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/raynham/april-2022-report
Monthly Traffic Safety Analysis
51 CRASHES IN
RAYNHAM, MA
APRIL 2022
Total crashes in RAYNHAM, MA increased by 27.5% year-over-year, rising from 40 in April 2021 to 51 in April 2022. Concurrently, total injuries increased by 41.7%, from 12 to 17. A notable shift was the increase in crashes where 'Failed to yield right of way' was a contributing factor, which doubled from 5 to 10 crashes.
51
▲ 27.5%was 40
Total Crash Events
0
Persons Killed
17
▲ 41.7%was 12
Persons Injured
3
▲ 200.0%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 · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash activity in RAYNHAM, MA showed an upward trend year-over-year, with total crashes increasing by 27.5% from 40 to 51. This rise was accompanied by a 41.7% increase in total injuries, climbing from 12 to 17. Fatalities remained at zero in both periods.
3
Hit-and-Run Crashes — April 2022
▲ 200.0% vs prior (1)
Hit-and-run crashes increased significantly year-over-year, rising from 1 crash in April 2021 to 3 crashes in April 2022. This represents a 200% increase in the count of hit-and-run incidents. The hit-and-run crash rate also increased from 2.5% of all crashes in April 2021 to 5.9% in April 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
16
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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 in April 2021, with 13 crashes, to Wednesday in April 2022, with 11 crashes. The peak crash hour also shifted from 1 PM in April 2021 to 3 PM in April 2022, though both hours recorded 5 crashes. The distribution of crashes across days of the week and hours of the day varied between the two periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of serious injury crashes remained constant at 1 in both April 2021 and April 2022. Minor injury crashes increased from 7 to 8, and possible injury crashes increased from 2 to 3 year-over-year. The proportion of crashes resulting in no injury also increased, from 72.5% (29 crashes) in April 2021 to 76.5% (39 crashes) in April 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw significant year-over-year changes in count. Crashes attributed to 'Failed to yield right of way' doubled from 5 in April 2021 to 10 in April 2022, a 100% increase in count. 'Inattention' related crashes increased by 30% in count, from 10 to 13, while 'Followed too closely' crashes decreased by 22.2% in count, from 9 to 7. The number of crashes with 'No improper driving' increased from 5 to 7, a 40% rise in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased by 18.2% in count, from 33 to 39, while 'Rain' condition crashes saw a 300% increase in count, rising from 1 to 4. For lighting conditions, crashes during 'Daylight' increased by 24.2% in count (from 33 to 41), and crashes in 'Dark - roadway not lighted' conditions increased by 400% in count, from 1 to 5. Crashes on 'Wet' road surfaces increased by 250% in count, from 2 to 7.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 79 in April 2021 to 95 in April 2022. Nissan and Honda vehicles each saw a 100% increase in their involvement count, rising from 6 to 12 for both makes. Conversely, Toyota involvement decreased by 8.3% in count (from 12 to 11), and Chevrolet involvement decreased by 25% in count (from 8 to 6). Among persons involved, the 65+ age group experienced a 225% increase in count, from 4 to 13, while the 21-25 age group saw a 47.1% decrease in count, from 17 to 9.
Top Vehicle Makes (95 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (114 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 MPH speed zones increased by 66.7% in count, from 6 in April 2021 to 10 in April 2022. Crashes in 40 MPH zones rose by 40% in count, from 10 to 14, and those in 65 MPH zones increased by 63.6% in count, from 11 to 18. Conversely, crashes in 50 MPH speed zones decreased by 50% in count, from 6 to 3. Fatal crashes remained at zero across all speed zones in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-04-01 through 2022-04-30 (30 days)
- Geographic scope: RAYNHAM, MA
- Total crash records analyzed: 51
- Total persons involved: 119
- Total vehicles involved: 95
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). "RAYNHAM, MA Crash Intelligence Report: April 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/raynham/april-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: 2022-04-01 – 2022-04-30
Generated: June 21, 2026 · All rights reserved