Monthly Traffic Safety Analysis

38 CRASHES IN
RAYNHAM, MA
APRIL 2023

All metrics benchmarked againstApril 2022

In April 2023, RAYNHAM experienced 38 total crashes, a decrease of 25.5% compared to 51 crashes in April 2022. Total injuries also decreased from 17 to 13, a reduction of 23.5%. The most notable shift was the 66.7% reduction in hit-and-run crashes, decreasing from 3 to 1 year-over-year.

38

-25.5%was 51

Total Crash Events

0

Persons Killed

13

-23.5%was 17

Persons Injured

1

-66.7%was 3

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 · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant decrease in crash activity in RAYNHAM, with total crashes falling from 51 in April 2022 to 38 in April 2023. This represents a 25.5% reduction in total crashes year-over-year. Similarly, total injuries decreased by 23.5%, from 17 to 13.

1

Hit-and-Run Crashes — April 2023

-66.7% vs prior (3)

Hit-and-run crashes decreased significantly from 3 in April 2022 to 1 in April 2023, representing a 66.7% reduction. The hit-and-run rate also decreased, falling from 5.9% in the prior period to 2.6% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

13

Motorists Injured

Prior: 16-18.8%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns shifted year-over-year, with the peak day for crashes moving from Wednesday (11 crashes) in April 2022 to Friday (10 crashes) in April 2023. The peak hour also shifted from 3 PM (5 crashes) in April 2022 to 4 PM (8 crashes) in April 2023. Crashes on Tuesdays, Wednesdays, and Thursdays saw notable decreases, while Friday crashes increased by 42.9% from 7 to 10.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Both April 2022 and April 2023 reported no fatal crashes or fatalities. Total injuries decreased by 23.5%, from 17 to 13. The proportion of serious injury crashes remained stable at 1 crash in both periods, representing 2.6% of crashes in the current period and 2% in the prior period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.6%
0.0%prior 1
Minor Injury6minor injury crashes15.8%
-25.0%prior 8
Possible Injury2possible injury crashes5.3%
-33.3%prior 3
No Injury29no injury crashes76.3%
-25.6%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor shifted from 'Inattention' in April 2022 (13 crashes) to 'Failed to yield right of way' in April 2023 (13 crashes). 'Inattention' crashes decreased by 30.8% (from 13 to 9), while 'Failed to yield right of way' crashes increased by 30% (from 10 to 13). 'Followed too closely' crashes saw a 57.1% reduction, decreasing from 7 to 3.

Officer-Reported Primary Contributing Cause

Failed to yield right of way13 (34.2%)30.0%prior 10
Inattention9 (23.7%)-30.8%prior 13
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner5 (13.2%)
No improper driving4 (10.5%)-42.9%prior 7
Followed too closely3 (7.9%)-57.1%prior 7
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.6%)
Fatigued/asleep1 (2.6%)
Over-correcting/over-steering1 (2.6%)
Disregarded traffic signs, signals, road markings1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under clear weather conditions decreased by 30.8%, from 39 in April 2022 to 27 in April 2023. Similarly, crashes under daylight conditions decreased by 22%, from 41 to 32. Crashes on dry road surfaces also saw a 25.6% reduction, decreasing from 43 to 32.

Weather

Clear27 (73.0%)
-30.8%prior 39
Cloudy5 (13.5%)
-16.7%prior 6
Rain3 (8.1%)
Clear/Unknown1 (2.7%)
Rain/Cloudy1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash

Lighting

Daylight32 (84.2%)
-22.0%prior 41
Dark - roadway not lighted4 (10.5%)
-20.0%prior 5
Dark - lighted roadway2 (5.3%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field

Road Surface

Dry32 (84.2%)
-25.6%prior 43
Wet6 (15.8%)
-14.3%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased by 21.1%, from 95 in April 2022 to 75 in April 2023. Toyota vehicles involved in crashes increased by 36.4% (from 11 to 15), moving to the top rank. Conversely, Nissan and Ford vehicles involved decreased by 50% each, from 12 to 6 and 10 to 5 respectively.

Top Vehicle Makes (75 vehicles)

1
TOYOTA15 (20%)
36.4%prior 11
2
HONDA8 (10.7%)
-33.3%prior 12
3
HYUNDAI7 (9.3%)
16.7%prior 6
4
NISSAN6 (8%)
-50.0%prior 12
5
FORD5 (6.7%)
-50.0%prior 10
6
CHEVROLET5 (6.7%)
-16.7%prior 6
7
SUBARU3 (4%)
8
MERCEDES-BENZ3 (4%)
9
VOLKSWAGEN3 (4%)
10
AUDI2 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records

2 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (84 persons with recorded sex)

Male49 (58.3%)
-21.0%prior 62
Female35 (41.7%)
-32.7%prior 52

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 mph speed zone saw a 55.6% decrease, falling from 18 in April 2022 to 8 in April 2023. Crashes in the 30 mph zone also decreased by 40%, from 10 to 6. Conversely, crashes in the 45 mph speed zone increased by 80%, from 5 to 9.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-04-01 through 2023-04-30 (30 days)
  • Geographic scope: RAYNHAM, MA
  • Total crash records analyzed: 38
  • Total persons involved: 90
  • Total vehicles involved: 75

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 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/raynham/april-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

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Raynham, MA Crash Report — April 2023 | ThatCarHitMe.com