ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MALDEN, MA · 2023
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/2023-annual-report
Yearly Traffic Safety Analysis
892 CRASHES IN
MALDEN, MA
2023
In 2023, Malden recorded 892 total traffic crashes, a 5.6% decrease from the 945 crashes reported in 2022. Despite the overall reduction in collisions, the number of resulting injuries increased from 273 to 299, and the number of fatalities doubled from one to two. The most notable year-over-year shift was this divergence, with fewer total crashes but more severe outcomes in terms of injuries and deaths.
892
▼ -5.6%was 945
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
299
▲ 9.5%was 273
Persons Injured
303
▲ 1.0%was 300
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 215 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 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crashes in Malden showed a downward trend, decreasing by 5.6% from 945 in 2022 to 892 in 2023. This trend did not extend to crash severity, as total reported injuries rose by 9.5% from 273 to 299. Fatalities also increased, from one person killed in 2022 to two in 2023.
303
Hit-and-Run Crashes — 2023
▲ 1.0% vs prior (300)
Hit-and-run incidents increased in both absolute count and as a proportion of total crashes between the two periods. The number of hit-and-run crashes rose from 300 in 2022 to 303 in 2023. As a percentage of all crashes, the hit-and-run rate trended upward from 31.7% to 34.0%, indicating that more than one in three crashes in 2023 involved a driver leaving the scene.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
26
Pedestrians Injured
12
Cyclists Injured
256
Motorists Injured
5
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 broadly consistent, with Monday being the peak day for crashes in both 2023 (153 crashes) and 2022 (148 crashes). However, the single busiest hour for collisions shifted later in the afternoon commute period. In 2023, the peak was the 4 PM hour with 70 crashes, compared to the 2 PM hour peak of 67 crashes in 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity outcomes worsened in 2023 compared to the prior year. The number of fatal crashes doubled from one to two, and the corresponding fatal crash rate increased from 0.11 to 0.22 per 100 crashes. While the count of serious injury crashes decreased slightly from 20 to 18, the total number of persons injured across all severities rose by 9.5%, from 273 in 2022 to 299 in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors cited in crashes were consistent year-over-year, with 'No improper driving' being the most common finding, followed by 'Inattention' and 'Failed to yield right of way'. While the top rankings were stable, there were notable shifts in the counts for specific behaviors. Crashes attributed to 'Failure to keep in proper lane or running off road' more than doubled, increasing from 5 to 12 incidents, and those involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' rose from 13 to 19.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
A notable shift occurred in crash conditions, with a higher proportion of incidents happening on wet roads in 2023. Crashes on wet surfaces increased from 105 in 2022 to 182 in 2023, representing a rise from 11.1% to 20.4% of all collisions. Correspondingly, crashes during rainy weather also increased. While most crashes in both years occurred in daylight, the proportion of incidents in 'Dark - lighted roadway' conditions saw a slight increase from 29.2% to 31.3% of the total.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained Toyota, Honda, and Ford across both periods. While Toyota and Ford saw fewer involvements in 2023, the number of crashes involving Hondas increased by 20.7%, from 237 to 286. An analysis of the age distribution of all persons involved in crashes shows an increased count for the 16-20 age group, which rose from 98 individuals in 2022 to 126 in 2023. Conversely, the 26-34 age group, while still the largest, saw its count decrease from 339 to 328.
Top Vehicle Makes (1,564 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
786 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,461 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The majority of crashes in both years occurred in 25 MPH speed zones, which saw 675 crashes in 2023, down from 711 in 2022. A significant shift occurred in the location of fatal crashes; the single fatality in 2022 was in a 30 MPH zone, whereas both fatalities in 2023 occurred in 25 MPH zones. While crashes in the dominant 25 MPH zone decreased, incidents in 35 MPH zones increased from 13 to 24.
Fatal crashes by zone: 25 mph: 2 of 675 (0.296%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: MALDEN, MA
- Total crash records analyzed: 892
- Total persons involved: 2,236
- Total vehicles involved: 1,564
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/malden/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved