Monthly Traffic Safety Analysis

21 CRASHES IN
SCITUATE, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

In January 2023, SCITUATE experienced 21 total crashes, a substantial increase compared to the 6 crashes recorded in January 2022, representing a 250% rise. The most notable year-over-year shift is the significant increase in overall crash incidents and associated injuries.

21

250.0%was 6

Total Crash Events

0

Persons Killed

4

300.0%was 1

Persons Injured

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. 2 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 2023-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant increase in crash activity in January 2023 compared to the prior year. Total crashes rose from 6 to 21, marking a 250% increase, while total injuries increased from 1 to 4, a 300% rise. This suggests a worsening trend in traffic safety for the month.

1

Hit-and-Run Crashes — January 2023

4.8% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 1300.0%

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 remained Monday in both periods, increasing from 2 crashes in January 2022 to 6 crashes in January 2023. The peak hour shifted from 9 PM with 1 crash in January 2022 to 1 PM with 5 crashes in January 2023, indicating a shift in the most frequent crash times from evening to early afternoon.

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

Fatal crashes remained at 0 in both January 2022 and January 2023. Total injuries increased from 1 in January 2022 to 4 in January 2023. In January 2023, 14.3% of crashes resulted in minor injuries and 4.8% in possible injuries, compared to January 2022 where 16.7% of crashes resulted in possible injuries.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes14.3%
Possible Injury1possible injury crashes4.8%
0.0%prior 1
No Injury15no injury crashes71.4%
200.0%prior 5

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

No improper driving remained the most frequently cited contributing factor, increasing from 3 crashes (50% share) in January 2022 to 7 crashes (33.3% share) in January 2023. Failed to yield right of way also increased, from 1 crash (16.7% share) in the prior period to 2 crashes (9.5% share) in the current period. Several factors, such as Fatigued/asleep (2 crashes) and Driving too fast for conditions (1 crash), appeared in January 2023 but were not present in January 2022.

Officer-Reported Primary Contributing Cause

No improper driving7 (33.3%)
Failed to yield right of way2 (9.5%)
Fatigued/asleep2 (9.5%)
Inattention1 (4.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.8%)
Other improper action1 (4.8%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.8%)
Driving too fast for conditions1 (4.8%)
Illness1 (4.8%)

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 in Clear weather conditions remained constant at 5 crashes in both periods. However, crashes in adverse weather conditions significantly increased, with Snow related conditions (Snow/Sleet, Snow/Cloudy, Snow, Sleet/Blowing sand, snow) totaling 9 crashes in January 2023 compared to 1 Snow crash in January 2022. Similarly, Wet road surface crashes increased from 1 in January 2022 to 7 in January 2023, while Dry road surface crashes decreased from 4 to 3.

Weather

Clear5 (23.8%)
0.0%prior 5
Snow/Sleet, hail (freezing rain or drizzle)3 (14.3%)
Snow/Cloudy3 (14.3%)
Rain2 (9.5%)
Rain/Cloudy2 (9.5%)
Snow2 (9.5%)
Cloudy2 (9.5%)
Sleet, hail (freezing rain or drizzle)/Blowing sand, snow1 (4.8%)
Cloudy/Rain1 (4.8%)

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

Lighting

Daylight10 (50.0%)
100.0%prior 5
Dark - lighted roadway4 (20.0%)
Dusk3 (15.0%)
Dark - roadway not lighted2 (10.0%)
Other1 (5.0%)

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

Road Surface

Snow8 (38.1%)
Wet7 (33.3%)
Dry3 (14.3%)
Ice2 (9.5%)
Slush1 (4.8%)

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

Vehicles & Demographics

Top Vehicle Makes (33 vehicles)

1
TOYOTA5 (15.2%)
2
CHEVROLET5 (15.2%)
3
NISSAN4 (12.1%)
4
FORD3 (9.1%)
5
MERCEDES-BENZ3 (9.1%)
6
AUDI2 (6.1%)
7
DODGE2 (6.1%)
8
LEXUS2 (6.1%)
9
CADI1 (3%)
10
MNNI1 (3%)

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

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

Sex Distribution (43 persons with recorded sex)

Male26 (60.5%)
766.7%prior 3
Female17 (39.5%)
240.0%prior 5

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

The distribution of crashes across speed zones changed, with 25 MPH zones seeing a notable increase from 1 crash in January 2022 to 9 crashes in January 2023. Crashes in 35 MPH zones increased from 1 to 5, and in 50 MPH zones from 1 to 3. A new speed zone of 10 MPH appeared in January 2023 with 1 crash, while the 45 MPH zone present in January 2022 (1 crash) was not observed in January 2023. No fatal crashes were recorded in any speed zone in 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: SCITUATE, MA
  • Total crash records analyzed: 21
  • Total persons involved: 44
  • Total vehicles involved: 33

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). "SCITUATE, 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/scituate/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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Scituate, MA Crash Report — January 2023 | ThatCarHitMe.com