ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WALTHAM, 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/waltham/september-2025-report
Monthly Traffic Safety Analysis
93 CRASHES IN
WALTHAM, MA
SEPTEMBER 2025
In September 2025, Waltham experienced 93 total crashes, marking a 19.1% decrease from the 115 crashes reported in September 2024. Total injuries also decreased by 18.5%, from 27 to 22. A notable shift includes a 100% increase in DUI crashes, rising from 1 to 2, while speeding-related crashes decreased by 66.7%, from 3 to 1.
93
▼ -19.1%was 115
Total Crash Events
0
Persons Killed
22
▼ -18.5%was 27
Persons Injured
7
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. 2 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 September 2025 indicates a downward trend in traffic incidents compared to the same month in the prior year. Total crashes decreased by 19.1%, from 115 to 93, and total injuries fell by 18.5%, from 27 to 22. Fatalities remained at zero in both periods.
7
Hit-and-Run Crashes — September 2025
▼ 0.0% vs prior (7)
The number of hit-and-run crashes remained constant at 7 incidents in both September 2024 and September 2025. However, due to the overall decrease in total crashes, the hit-and-run rate increased from 6.1% in the prior period to 7.5% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
0
Other Killed
1
Pedestrians Injured
20
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 distribution of crashes shifted year-over-year, with the peak day moving from Sunday (19 crashes) in September 2024 to Friday (19 crashes) in September 2025. The peak hour for crashes also changed, from 4 PM (12 crashes) in the prior period to 2 PM (10 crashes) in the current period. Weekend crashes on Saturday and Sunday collectively decreased from 36 to 19, suggesting a shift in crash occurrence towards weekdays.
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 showed notable changes, although no fatalities occurred in either period. Serious injuries (Severity A) increased from 0 in September 2024 to 1 in September 2025. Minor injuries (Severity B) saw a significant decrease of 66.7%, falling from 21 to 7, while possible injuries (Severity C) increased by 75%, from 4 to 7. The proportion of crashes resulting in any injury (A, B, or C) decreased from 21.7% to 16.1% 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
The leading contributing factors saw shifts in their prevalence and ranking. 'No improper driving' increased by 4 crashes, from 19 to 23, and became the most frequent factor, up from second. Conversely, 'Inattention' decreased by 5 crashes, from 23 to 18, dropping from the top factor to second. 'Followed too closely' experienced a 50% decrease in count, from 12 crashes to 6, while 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' remained constant at 7 crashes.
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
Crashes occurring on dry road surfaces increased proportionally from 87.8% in September 2024 to 91.4% in September 2025. Conversely, crashes on wet road surfaces decreased from 13 to 8. The proportion of crashes occurring in daylight conditions increased from 76.5% to 83.9% year-over-year, indicating a higher concentration of incidents during daytime hours in the current period.
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
Among the top vehicle makes involved in crashes, Toyota, Honda, and Ford all experienced decreases in crash involvement. Toyota decreased from 40 to 34, Honda from 34 to 25, and Ford from 30 to 25. Significant shifts in person age distribution were observed, with the 0-15 age group increasing by 75% (from 8 to 14 persons) and the 21-25 age group increasing by 72.2% (from 18 to 31 persons).
Top Vehicle Makes (180 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records
16 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (201 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
Crashes in 25 mph zones decreased from 56 to 47, while those in 55 mph zones decreased from 13 to 9. Similarly, crashes in 30 mph zones dropped from 15 to 8, and 35 mph zones saw a decrease from 11 to 7. No fatal crashes were recorded in any speed zone during either period.
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: WALTHAM, MA
- Total crash records analyzed: 93
- Total persons involved: 216
- Total vehicles involved: 180
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). "WALTHAM, 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/waltham/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