ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MALDEN, MA · APRIL 2026
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/malden/april-2026-report
Monthly Traffic Safety Analysis
63 CRASHES IN
MALDEN, MA
APRIL 2026
In April 2026, MALDEN, MA recorded 63 total crashes, a decrease from 76 crashes in April 2025, representing a 17.1% reduction year-over-year. This period saw a notable increase in the hit-and-run crash rate, rising from 25% to 33.3%. Total fatalities remained at zero for both periods.
63
▼ -17.1%was 76
Total Crash Events
0
Persons Killed
24
▼ -4.0%was 25
Persons Injured
21
▲ 10.5%was 19
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. 16 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a decrease in total crashes in MALDEN, MA, falling from 76 in April 2025 to 63 in April 2026. This represents a 17.1% reduction in crashes year-over-year. Fatalities remained at zero in both periods.
21
Hit-and-Run Crashes — April 2026
▲ 10.5% vs prior (19)
Hit-and-run crashes increased from 19 in April 2025 to 21 in April 2026. The hit-and-run rate also increased from 25% of total crashes in April 2025 to 33.3% in April 2026, indicating an upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
3
Cyclists Injured
20
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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 with 16 crashes in April 2025 to Monday and Sunday, both with 12 crashes, in April 2026. The peak crash hour also changed, moving from 5 PM with 9 crashes in April 2025 to 12 PM with 6 crashes in April 2026.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero in both April 2025 and April 2026. Total injuries decreased slightly from 25 in April 2025 to 24 in April 2026. The proportion of serious injury crashes increased from 1.3% (1 crash) in April 2025 to 1.6% (1 crash) in April 2026, while minor injury crashes increased from 17.1% (13 crashes) to 22.2% (14 crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Most severe injury per crash record
Top Contributing Factors
No improper driving remained the most frequently cited contributing factor, decreasing from 26 crashes in April 2025 to 21 crashes in April 2026. Inattention crashes increased from 5 to 8 year-over-year, while Followed too closely and Other improper action remained stable at 2 crashes each. The factor Failed to yield right of way, which accounted for 1 crash in April 2025, was not present in the top factors for April 2026.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear or clear/clear weather conditions decreased from 51 in April 2025 to 43 in April 2026, while rain-related crashes decreased from 9 to 6. The number of crashes on dry road surfaces decreased from 57 to 48, and wet road surface crashes decreased from 14 to 9. Daylight conditions accounted for 48 crashes in April 2025, decreasing to 35 in April 2026.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Road surface condition field
Vehicles & Demographics
Toyota was the top vehicle make involved in crashes in April 2025 with 25 instances, but Honda became the top make in April 2026 with 20 instances, while Toyota decreased to 11. The 16-20 age group saw a decrease in persons involved from 16 to 9, while the 0-15 age group increased from 5 to 7.
Top Vehicle Makes (117 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Vehicle unit records
37 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (103 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed limit zones decreased from 63 in April 2025 to 48 in April 2026. There were no fatal crashes reported in any speed limit zone in either period. Crashes in 30 mph zones decreased from 6 to 3, while crashes in 10 mph zones increased from 2 to 3.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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: 2026-04-01 through 2026-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-04-01 through 2026-04-30 (30 days)
- Geographic scope: MALDEN, MA
- Total crash records analyzed: 63
- Total persons involved: 138
- Total vehicles involved: 117
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). "MALDEN, MA Crash Intelligence Report: April 2026." Published June 21, 2026. Reporting period: 2026-04-01 to 2026-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/malden/april-2026-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: 2026-04-01 – 2026-04-30
Generated: June 21, 2026 · All rights reserved