ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ARLINGTON, MA · SEPTEMBER 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/arlington/september-2025-report
Monthly Traffic Safety Analysis
50 CRASHES IN
ARLINGTON, MA
SEPTEMBER 2025
In September 2025, Arlington experienced 50 crashes, a significant increase from the 32 crashes recorded in September 2024, representing a 56.25% rise. The most notable year-over-year shift was the substantial increase in hit-and-run incidents, which rose from 2 to 11 crashes. Despite the overall increase in crashes, there were no fatalities in the current period, compared to one fatality in the prior period.
50
▲ 56.3%was 32
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
8
▲ 100.0%was 4
Persons Injured
11
▲ 450.0%was 2
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. 6 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for Arlington indicates a rising trend year-over-year, with total crashes increasing by 56.25% from 32 in September 2024 to 50 in September 2025. Total injuries also saw a substantial increase, doubling from 4 to 8 during the same period. However, fatal crashes decreased from 1 in the prior year to 0 in the current year.
11
Hit-and-Run Crashes — September 2025
▲ 450.0% vs prior (2)
Hit-and-run incidents increased substantially year-over-year, with the number of crashes rising from 2 in September 2024 to 11 in September 2025. This increase is reflected in the hit-and-run rate, which climbed from 6.3% of all crashes in the prior period to 22% in the current period.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
2
Cyclists Injured
5
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns for crashes shifted between the two periods. In September 2025, the peak day for crashes was Wednesday with 12 incidents, differing from September 2024 where Monday saw the most crashes with 10. Similarly, the peak hour for crashes moved from 9 AM with 4 incidents in the prior year to 4 PM with 10 incidents in the current year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The distribution of crash severity shows a decrease in fatal crashes, moving from 1 (3.1% of total crashes) in September 2024 to 0 (0%) in September 2025. Conversely, minor injury crashes increased from 2 (6.3%) to 5 (10%) and possible injury crashes rose from 1 (3.1%) to 2 (4%). The proportion of no-injury crashes decreased from 84.4% to 74% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record
Top Contributing Factors
Comparing contributing factors, 'Failed to yield right of way' saw the largest increase, rising from 4 crashes in September 2024 to 14 crashes in September 2025. Crashes attributed to 'No improper driving' also increased from 8 to 15. Conversely, 'Inattention' decreased from 4 crashes to 2 crashes, and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from 3 crashes to 1 crash.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in wet road surface conditions increased notably, rising from 2 crashes (6.25% of total) in September 2024 to 8 crashes (16% of total) in September 2025. While the number of crashes in clear weather conditions increased from 26 to 35, their proportion of total crashes decreased from 81.25% to 70%. Daylight remained the dominant lighting condition for crashes, with its proportion stable at approximately 78% for both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field
Vehicles & Demographics
Toyota and Honda remained the top two vehicle makes involved in crashes, with Toyota increasing from 13 to 18 and Honda from 8 to 10. The age group 35-44 continued to represent the highest number of persons involved in crashes, increasing from 15 to 24. A new age group, 0-15, appeared in the current period with 6 persons involved, which was not present in the prior period's data.
Top Vehicle Makes (89 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records
10 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (93 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events
Speed Limit Zones
The 25 mph speed limit zone remained the most common location for crashes, with incidents increasing from 25 in September 2024 to 43 in September 2025. Crashes in the 35 mph zone decreased from 3 to 1, and the single fatal crash previously reported in this zone is absent in the current period. New speed zones of 5 mph, 20 mph, and 55 mph appeared in the current period, accounting for 2, 2, and 1 crash respectively.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-09-01 through 2025-09-30 (30 days)
- Geographic scope: ARLINGTON, MA
- Total crash records analyzed: 50
- Total persons involved: 105
- Total vehicles involved: 89
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). "ARLINGTON, MA Crash Intelligence Report: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/arlington/september-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: 2025-09-01 – 2025-09-30
Generated: June 21, 2026 · All rights reserved