ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SCITUATE, MA · 2025
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/scituate/2025-annual-report
Yearly Traffic Safety Analysis
117 CRASHES IN
SCITUATE, MA
2025
In Scituate, total vehicle crashes decreased by 24% from 154 in 2024 to 117 in 2025. This overall reduction was accompanied by a drop in total injuries from 42 to 31 and a decrease in fatalities from one to zero. The most notable year-over-year shift was the elimination of fatal crashes and a significant drop in incidents attributed to erratic or reckless driving.
117
▼ -24.0%was 154
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
31
▼ -26.2%was 42
Persons Injured
7
▲ 40.0%was 5
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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety data for Scituate shows a positive year-over-year trend, with significant reductions across key metrics. Total crashes fell by 24% from 154 to 117, and the number of people injured in these incidents decreased by 26% from 42 to 31. Furthermore, there were no fatalities recorded in 2025, compared to one in the prior year.
7
Hit-and-Run Crashes — 2025
▲ 40.0% vs prior (5)
Despite a significant decrease in total crashes, the number of hit-and-run incidents increased from 5 in 2024 to 7 in 2025. This increase in count, combined with the lower overall crash total, resulted in the hit-and-run rate nearly doubling. The rate grew from 3.2% of all crashes in 2024 to 6.0% in 2025, indicating an upward trend for this specific crash type.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
1
Cyclists Injured
29
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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 2025, the peak day for crashes was Saturday with 26 incidents, and the peak hour was 12 p.m. with 13 incidents. This contrasts with 2024, when the peak day was Thursday (27 crashes) and the peak hours were 2 p.m. and 4 p.m. (15 crashes each), indicating a shift from weekday afternoon peaks to a weekend midday peak.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity improved year-over-year, with fatal crashes decreasing from one in 2024 to zero in 2025. The proportion of crashes involving minor injuries decreased from 14.3% of all incidents to 10.3%, while the share of possible injury crashes increased from 5.2% to 9.4%. The number of serious injury crashes remained unchanged at one incident in both years.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' remained the most common finding in both years, its count decreased from 52 to 37. 'Failed to yield right of way' was the second-leading factor in both periods, with its count declining slightly from 18 to 16. Notably, crashes attributed to 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' saw a significant drop in count from 13 in 2024 to 5 in 2025, a 61.5% decrease.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across environmental conditions remained largely consistent year-over-year, despite the overall reduction in incidents. Crashes in clear weather accounted for approximately 70% of the total in both 2025 and 2024. Similarly, incidents on wet road surfaces made up 18.8% of crashes in both periods, though the absolute count fell from 29 to 22.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Ford, and Honda—remained consistent across both years, with Toyota leading in both periods. Analysis of person demographics shows a notable decrease in crash involvement for the 16-20 age group (from 43 to 27 persons) and the 65+ age group (from 61 to 45 persons). Conversely, the 35-44 age group saw a slight increase in involvement from 35 to 41 persons.
Top Vehicle Makes (196 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (225 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
In both 2025 and 2024, the 30 mph speed zone was the site of the most crashes, with counts of 30 and 46, respectively. The overall number of crashes decreased across most speed zones, in line with the city-wide trend. The single fatal crash in 2024 occurred in a 45 mph zone, a speed zone which saw no fatal crashes in 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: SCITUATE, MA
- Total crash records analyzed: 117
- Total persons involved: 239
- Total vehicles involved: 196
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/scituate/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved