ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BEVERLY, MA · APRIL 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/beverly/april-2025-report
Monthly Traffic Safety Analysis
42 CRASHES IN
BEVERLY, MA
APRIL 2025
In April 2025, BEVERLY experienced 42 total crashes, marking a 16.67% increase compared to the 36 crashes reported in April 2024. The most notable shift was a significant rise in total injuries, which increased by 77.78% from 9 in the prior year to 16 in the current period.
42
▲ 16.7%was 36
Total Crash Events
0
Persons Killed
16
▲ 77.8%was 9
Persons Injured
4
▲ 33.3%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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates an increase in crash incidents, with total crashes rising from 36 in April 2024 to 42 in April 2025. This represents a 16.67% year-over-year increase in crash volume for the month.
4
Hit-and-Run Crashes — April 2025
▲ 33.3% vs prior (3)
Hit-and-run crashes increased from 3 in April 2024 to 4 in April 2025. Concurrently, the hit-and-run rate also saw an upward trend, rising from 8.3% of total crashes in the prior period to 9.5% in the current period.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
While Tuesday remained the peak day for crashes in both periods, with 10 crashes in the current year compared to 8 in the prior, the peak hour shifted significantly. The peak crash hour moved from 9 AM with 4 crashes in April 2024 to 5 PM with 6 crashes in April 2025, indicating a shift towards late afternoon incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero for both April 2024 and April 2025. Total injuries increased by 77.78%, rising from 9 in the prior period to 16 in the current period. The proportion of crashes resulting in 'No Injury' decreased from 58.3% in April 2024 to 69% in April 2025, while 'Minor Injury' crashes increased from 5.6% to 23.8% of total crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Failed to yield right of way' increased from 5 crashes in the prior period to 7 crashes in the current period, becoming the leading factor. 'Followed too closely' also saw a substantial rise, increasing by 3 crashes from 3 to 6. 'Inattention' remained consistent with 6 crashes in both periods, while 'No improper driving' decreased from 5 to 4 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'wet' road surface conditions increased from 5 (13.9% share) in April 2024 to 10 (23.8% share) in April 2025. Incidents in 'Dark - lighted roadway' conditions also saw a notable increase, rising from 4 (11.1% share) to 9 (21.4% share) year-over-year. The proportion of crashes during 'Daylight' remained relatively stable, decreasing slightly from 80.6% to 78.6%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 72 in April 2024 to 105 in April 2025. The 21-25 age group saw a significant increase in representation, rising from 7 persons to 17 persons, while the 65+ age group also increased from 9 to 15 persons. Toyota became the top vehicle make involved in crashes, with 15 incidents in the current period compared to 10 in the prior period, surpassing Honda which had 13 incidents compared to 11 previously.
Top Vehicle Makes (82 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records
10 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (95 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 mph speed zones increased from 13 in April 2024 to 21 in April 2025. Similarly, crashes in 30 mph zones more than doubled, rising from 5 to 13 incidents. No fatal crashes were reported in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-04-01 through 2025-04-30 (30 days)
- Geographic scope: BEVERLY, MA
- Total crash records analyzed: 42
- Total persons involved: 105
- Total vehicles involved: 82
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). "BEVERLY, MA Crash Intelligence Report: April 2025." Published June 21, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/beverly/april-2025-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: 2025-04-01 – 2025-04-30
Generated: June 21, 2026 · All rights reserved