Monthly Traffic Safety Analysis

35 CRASHES IN
RAYNHAM, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

Total crashes in RAYNHAM, MA decreased by 20.5% year-over-year, from 44 crashes in January 2022 to 35 crashes in January 2023. The most notable shift was a 50% reduction in crashes attributed to 'Inattention', decreasing from 14 to 7 incidents. Despite fewer crashes overall, total injuries increased by 15.4%, from 13 to 15.

35

-20.5%was 44

Total Crash Events

0

Persons Killed

15

15.4%was 13

Persons Injured

2

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 · 2023-01-01 to 2023-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in RAYNHAM, MA decreased by 20.5% year-over-year, from 44 crashes in January 2022 to 35 crashes in January 2023. This indicates a downward trend in crash frequency for the specified month. The number of vehicles involved also decreased by 24.7%, from 85 to 64.

2

Hit-and-Run Crashes — January 2023

0.0% vs prior (2)

The number of hit-and-run crashes remained constant at 2 in both January 2022 and January 2023. However, the hit-and-run rate increased from 4.5% of total crashes in the prior period to 5.7% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

15

Motorists Injured

Prior: 1225.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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 January 2022 (14 crashes) to Saturday in January 2023 (8 crashes). Similarly, the peak crash hour changed from 10 PM (4 crashes) in the prior period to 3 PM (6 crashes) in the current period. Crashes on Thursdays saw a significant decrease, from 9 in January 2022 to just 1 in January 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities reported in either January 2022 or January 2023. Total injuries increased by 15.4%, from 13 persons injured in January 2022 to 15 persons injured in January 2023. Crashes resulting in 'No Injury' decreased from 77.3% of all crashes in January 2022 to 68.6% in January 2023.

Outcome by Severity (Crash Events)

Minor Injury9minor injury crashes25.7%
50.0%prior 6
Possible Injury2possible injury crashes5.7%
100.0%prior 1
No Injury24no injury crashes68.6%
-29.4%prior 34

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Most severe injury per crash record

Top Contributing Factors

'Inattention' crashes decreased by 50% in count, from 14 in January 2022 to 7 in January 2023, while 'Failed to yield right of way' remained constant at 7 crashes in both periods. Crashes attributed to 'No improper driving' decreased by 37.5%, from 8 to 5. Conversely, 'Driving too fast for conditions' crashes increased from 1 to 3, a 200% change in count.

Officer-Reported Primary Contributing Cause

Inattention7 (20%)-50.0%prior 14
Failed to yield right of way7 (20%)0.0%prior 7
No improper driving5 (14.3%)-37.5%prior 8
Followed too closely5 (14.3%)
Driving too fast for conditions3 (8.6%)
Disregarded traffic signs, signals, road markings2 (5.7%)
Failure to keep in proper lane or running off road1 (2.9%)
Operating defective equipment1 (2.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.9%)
Physical impairment1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on dry road surfaces decreased by 43.3%, from 30 in January 2022 to 17 in January 2023. Conversely, crashes on wet road surfaces increased by 275%, rising from 4 to 15. Crashes during 'Dark - roadway not lighted' conditions saw an 83.3% decrease, falling from 6 to 1.

Weather

Clear20 (57.1%)
-23.1%prior 26
Rain5 (14.3%)
Cloudy/Rain3 (8.6%)
Snow3 (8.6%)
-57.1%prior 7
Cloudy2 (5.7%)
Rain/Cloudy1 (2.9%)
Rain/Snow1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Weather condition at time of crash

Lighting

Daylight21 (60.0%)
-12.5%prior 24
Dark - lighted roadway9 (25.7%)
-30.8%prior 13
Dark - unknown roadway lighting1 (2.9%)
Dusk1 (2.9%)
Other1 (2.9%)
Dawn1 (2.9%)
Dark - roadway not lighted1 (2.9%)
-83.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Lighting condition field

Road Surface

Dry17 (48.6%)
-43.3%prior 30
Wet15 (42.9%)
Snow3 (8.6%)
-66.7%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased by 24.7%, from 85 in January 2022 to 64 in January 2023. The top vehicle make involved shifted, with Ford decreasing from 19 to 6 incidents (-68.4%) and Chevrolet increasing from 3 to 9 incidents (+200%). The number of persons aged 26-34 involved in crashes decreased by 48%, from 25 to 13.

Top Vehicle Makes (64 vehicles)

1
TOYOTA13 (20.3%)
-13.3%prior 15
2
CHEVROLET9 (14.1%)
3
FORD6 (9.4%)
-68.4%prior 19
4
JEEP5 (7.8%)
5
DODGE4 (6.3%)
6
HONDA3 (4.7%)
-62.5%prior 8
7
NISSAN3 (4.7%)
-50.0%prior 6
8
KIA2 (3.1%)
9
CHRYSLER2 (3.1%)
10
SUBARU2 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Vehicle unit records

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

Sex Distribution (78 persons with recorded sex)

Male46 (59.0%)
9.5%prior 42
Female32 (41.0%)
-27.3%prior 44

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 MPH speed limit zone decreased by 54.5%, from 11 in January 2022 to 5 in January 2023. Crashes in the 65 MPH speed limit zone slightly increased from 9 to 10, an 11.1% change. There were no fatal crashes in any speed limit zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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 2023-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-01-31 (31 days)
  • Geographic scope: RAYNHAM, MA
  • Total crash records analyzed: 35
  • Total persons involved: 83
  • Total vehicles involved: 64

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: January 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/raynham/january-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 — January 2023 | ThatCarHitMe.com