ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WILMINGTON, MA · NOVEMBER 2024
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/wilmington/november-2024-report
Monthly Traffic Safety Analysis
38 CRASHES IN
WILMINGTON, MA
NOVEMBER 2024
In November 2024, Wilmington recorded 38 total crashes, a decrease from 49 crashes in November 2023, representing a 22.4% reduction. Total injuries also saw a slight decrease from 15 to 14. The most notable shift was a 50% reduction in hit-and-run crashes, decreasing from 4 in the prior period to 2 in the current period.
38
▼ -22.4%was 49
Total Crash Events
0
Persons Killed
14
▼ -6.7%was 15
Persons Injured
2
▼ -50.0%was 4
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in Wilmington showed a downward trend year-over-year. Total crashes decreased by 11, from 49 in November 2023 to 38 in November 2024. Total injuries also slightly decreased from 15 to 14 during the same period, while fatalities remained at 0 in both periods.
2
Hit-and-Run Crashes — November 2024
▼ -50.0% vs prior (4)
Hit-and-run crashes decreased significantly, with the count falling from 4 in November 2023 to 2 in November 2024. This change resulted in a decrease in the hit-and-run rate from 8.2% in the prior period to 5.3% in the current period.
Vulnerable Road User Casualties
0
Motorists Killed
14
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted year-over-year. In November 2023, the peak day for crashes was Tuesday with 10 incidents, and the peak hour was 5 PM with 8 crashes. In contrast, November 2024 saw Friday as the peak day with 8 crashes, and 9 AM as the peak hour with 7 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either period. The distribution of injury severity shifted, with serious injuries increasing from 0 in November 2023 to 1 in November 2024. Minor injuries saw a substantial decrease from 11 to 3, while possible injuries increased from 1 to 5 crashes year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record
Top Contributing Factors
Several key contributing factors decreased year-over-year: 'Inattention' crashes decreased from 12 to 9 (a 25% decrease), 'Failed to yield right of way' decreased from 10 to 6 (a 40% decrease), and 'Followed too closely' decreased from 9 to 4 (a 55.6% decrease). Conversely, crashes attributed to 'No improper driving' increased from 6 to 8 (a 33.3% increase), and 'Driving too fast for conditions' emerged as a factor with 3 crashes in the current period, not being explicitly listed in the prior period's top factors.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 41 in November 2023 to 28 in November 2024, while crashes in rainy conditions increased from 1 to 6. Crashes during daylight hours increased from 22 to 26, but crashes in dark conditions, both 'lighted roadway' and 'roadway not lighted', decreased from 18 to 7 and 8 to 4 respectively. Crashes on dry road surfaces decreased from 45 to 28, while those on wet surfaces increased from 4 to 9, and 1 crash occurred on ice in the current period, which was not present in the prior period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 100 in November 2023 to 73 in November 2024. While Honda vehicles involved decreased from 19 to 11, Ford vehicles remained stable at 11. Toyota vehicles involved increased from 8 to 10, and Chevrolet increased from 6 to 8. In terms of persons involved, the 16-20, 21-25, 26-34, 55-64, and 65+ age groups all saw decreases in their counts, while the 0-15 and 35-44 age groups experienced increases.
Top Vehicle Makes (73 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records
5 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (87 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in speed limit zones of 30 mph, 35 mph, and 65 mph all decreased, from 8 to 4, 15 to 9, and 13 to 10 respectively. Conversely, crashes in 25 mph zones increased from 4 to 7 year-over-year. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-11-01 through 2024-11-30 (30 days)
- Geographic scope: WILMINGTON, MA
- Total crash records analyzed: 38
- Total persons involved: 91
- Total vehicles involved: 73
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). "WILMINGTON, MA Crash Intelligence Report: November 2024." Published June 21, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wilmington/november-2024-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: 2024-11-01 – 2024-11-30
Generated: June 21, 2026 · All rights reserved