ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELSEA, 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/chelsea/november-2024-report
Monthly Traffic Safety Analysis
86 CRASHES IN
CHELSEA, MA
NOVEMBER 2024
In November 2024, Chelsea experienced 86 crashes, a decrease of 7.53% compared to the 93 crashes recorded in November 2023. The most significant year-over-year shift was the emergence of one fatality in the current period, compared to zero fatalities in the prior year.
86
▼ -7.5%was 93
Total Crash Events
1
Persons Killed
30
▼ -28.6%was 42
Persons Injured
7
▲ 133.3%was 3
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.
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, crashes in Chelsea decreased by 7.53% year-over-year, falling from 93 in November 2023 to 86 in November 2024. Despite this reduction in total crashes, fatalities increased from 0 to 1, while total injuries saw a notable decrease of 28.57%, from 42 to 30.
7
Hit-and-Run Crashes — November 2024
▲ 133.3% vs prior (3)
Hit-and-run crashes increased significantly year-over-year, rising by 133.3% from 3 incidents in November 2023 to 7 in November 2024. This also led to an increase in the hit-and-run rate, which climbed from 3.2% of all crashes in the prior period to 8.1% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
3
Pedestrians Injured
1
Cyclists Injured
26
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 for crashes shifted year-over-year; in November 2024, Friday was the peak day with 18 crashes, whereas Wednesday had been the peak day in November 2023 with 21 crashes. The peak crash hour also changed from 5 p.m. with 11 crashes in the prior period to 7 p.m. with 8 crashes in the current period.
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
The severity distribution showed a critical change with one fatality recorded in November 2024, compared to zero in November 2023, resulting in a fatal crash rate of 1.16% for the current period. Total injuries decreased from 42 to 30, with minor injuries remaining relatively stable (17.4% of crashes in current vs 17.2% in prior) but possible injuries dropping from 12.9% to 5.8% of crashes.
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
Among contributing factors, 'No improper driving' decreased slightly from 31 to 30 crashes, a 3.2% reduction in count. Conversely, crashes attributed to 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased by 150%, from 2 to 5 incidents, and 'Disregarded traffic signs, signals, road markings' rose by 200%, from 1 to 3 crashes. 'Followed too closely' incidents decreased by 50%, from 4 to 2 crashes.
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 by 20%, from 75 in November 2023 to 60 in November 2024, while crashes in rainy conditions increased by 75%, from 4 to 7. Similarly, incidents on dry road surfaces decreased by 13.09% (from 84 to 73 crashes), but those on wet road surfaces increased by 44.44%, from 9 to 13 crashes.
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 representation of certain age groups in crashes shifted, with persons aged 0-15 involved in 22 incidents in November 2024, a 69.2% increase from 13 in the prior year. Conversely, involvement for the 26-34 age group decreased by 21.7% (from 46 to 36 persons), and for the 55-64 age group by 25% (from 24 to 18 persons). Among vehicle makes, Honda-involved crashes increased by 23.3% (from 30 to 37), while Ford-involved crashes decreased by 30.4% (from 23 to 16).
Top Vehicle Makes (179 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records
37 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (196 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 25 mph zones decreased by 11.6%, from 69 in November 2023 to 61 in November 2024, notably including one fatal crash in the current period compared to zero previously. Crashes in 50 mph zones saw a 200% increase, rising from 1 to 3 incidents. Additionally, the 15 mph speed zone, which had no crashes in the prior period, recorded one crash in the current period.
Fatal crashes by zone: 25 mph: 1 of 61 (1.639%)
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: CHELSEA, MA
- Total crash records analyzed: 86
- Total persons involved: 236
- Total vehicles involved: 179
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). "CHELSEA, 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/chelsea/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