ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MALDEN, 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/malden/2025-annual-report
Yearly Traffic Safety Analysis
827 CRASHES IN
MALDEN, MA
2025
In 2025, Malden recorded 827 total crashes, a 13.3% decrease from the 954 crashes reported in 2024. Despite the overall reduction in collisions, the most notable year-over-year shift was the occurrence of one fatal crash in 2025, whereas there were no fatal crashes in the prior year. The total number of injuries also decreased from 347 in 2024 to 283 in 2025.
827
▼ -13.3%was 954
Total Crash Events
1
Persons Killed
283
▼ -18.4%was 347
Persons Injured
263
▼ -9.3%was 290
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 208 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
Year-over-year data indicates a downward trend in the overall number of traffic collisions in Malden. Total crashes decreased by 13.3%, from 954 in 2024 to 827 in 2025. Similarly, the number of people injured in these incidents fell by 18.4%, from 347 to 283.
263
Hit-and-Run Crashes — 2025
▼ -9.3% vs prior (290)
While the absolute number of hit-and-run incidents decreased from 290 in 2024 to 263 in 2025, the hit-and-run rate as a percentage of total crashes showed a slight increase. In 2025, hit-and-runs constituted 31.8% of all crashes, up from 30.4% in the prior year. This indicates that although overall crashes and hit-and-runs both declined, the drop in non-hit-and-run crashes was proportionally larger.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
26
Pedestrians Injured
16
Cyclists Injured
234
Motorists Injured
7
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 temporal patterns of crashes remained largely consistent year-over-year, with Monday being the peak day and 3 PM the peak hour in both periods. While the afternoon rush hour continues to be the most frequent time for incidents, there was a notable decrease in crashes on Sundays, which fell from 135 in 2024 to 92 in 2025. Crash counts on other weekdays like Tuesday and Wednesday also saw significant declines.
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
The severity of crashes shifted in 2025, marked by the appearance of one fatal crash after none were recorded in 2024, raising the fatal crash rate from 0% to 0.12%. Conversely, the count of serious injury crashes was more than halved, falling from 23 incidents in 2024 to 11 in 2025. The proportions of crashes resulting in minor or possible injuries also saw a slight decrease.
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
The leading contributing factors for crashes remained consistent, with "No improper driving" and "Inattention" being the top two cited factors in both 2025 and 2024. The count of crashes attributed to "Inattention" decreased from 72 in 2024 to 58 in 2025. Notably, crashes involving "Failure to keep in proper lane or running off road" increased from 5 incidents to 14, and those involving "Swerving or avoiding" rose from 2 to 12 incidents.
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 different conditions showed some shifts between 2024 and 2025. While most crashes in both years occurred on dry roads in daylight, the number of incidents in dark, but lighted, roadway conditions decreased from 272 to 192. Crashes occurring on adverse road surfaces like ice or snow saw an increase, rising from a combined 30 incidents in 2024 to 51 in 2025.
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 makes of vehicles involved in collisions remained consistent, with Toyota, Honda, and Ford being the top three most frequent makes in both 2024 and 2025, though the count for each decreased. An analysis of the age of persons involved shows a general decrease across most age groups, corresponding to the overall reduction in crashes. The largest drop in involvement was seen in the 26-34 age group, which decreased from 388 individuals in 2024 to 283 in 2025.
Top Vehicle Makes (1,422 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
439 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,330 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
The vast majority of crashes in both periods occurred in 25 mph speed zones, which accounted for 628 crashes in 2025 and 747 in 2024. The single fatal crash recorded in 2025 took place within a 25 mph zone. There was an increase in the number of crashes reported in zones with speed limits below 25 mph, rising from 60 incidents in 2024 to 86 in 2025.
Fatal crashes by zone: 25 mph: 1 of 628 (0.159%)
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: MALDEN, MA
- Total crash records analyzed: 827
- Total persons involved: 1,746
- Total vehicles involved: 1,422
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: 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/malden/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