ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELSEA, MA · 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/chelsea/2025-annual-report
Yearly Traffic Safety Analysis
696 CRASHES IN
CHELSEA, MA
2025
In 2025, Chelsea recorded 696 total traffic crashes, a 29% decrease from the 980 crashes reported in 2024. This downward trend was also reflected in total fatalities, which fell from three to one, and total injuries, which decreased from 358 to 269. The most notable year-over-year shift was the significant reduction in overall crash volume across the city.
696
▼ -29.0%was 980
Total Crash Events
1
▼ -66.7%was 3
Persons Killed
269
▼ -24.9%was 358
Persons Injured
45
▲ 9.8%was 41
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. 16 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Chelsea showed a significant downward trend year-over-year. Total crashes fell by 29% from 980 in 2024 to 696 in 2025. Similarly, the number of people injured in these incidents decreased by 25% from 358 to 269, and fatalities were reduced from three to one.
45
Hit-and-Run Crashes — 2025
▲ 9.8% vs prior (41)
The trend for hit-and-run crashes moved counter to the overall decrease in collisions. The absolute number of hit-and-run incidents increased from 41 in 2024 to 45 in 2025. This resulted in a notable increase in the hit-and-run rate, which rose from 4.2% of all crashes in the prior year to 6.5% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
25
Pedestrians Injured
11
Cyclists Injured
220
Motorists Injured
13
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The daily and hourly crash patterns saw some changes between the two periods. The peak day for crashes shifted from Thursday (159 crashes) in 2024 to Wednesday (109 crashes) in 2025. The peak hour for collisions remained consistent at 3 PM in both years, though the crash count during this hour dropped from 84 to 70.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the total number of crashes decreased, the severity distribution shifted. The fatal crash rate fell from 0.3% to 0.1% of all crashes. However, the count of serious injury crashes increased from 14 to 18, representing a rise in their share of total crashes from 1.4% in 2024 to 2.6% in 2025. The proportion of crashes with no reported injuries remained stable at approximately 72%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' remained the most common factor in both years, its count dropped from 324 to 248. Notably, the count for crashes involving 'Disregarded traffic signs, signals, road markings' increased by 40%, from 20 incidents in 2024 to 28 in 2025. The count for 'Failure to keep in proper lane' also rose from 17 to 22, a 29% increase.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in both years predominantly occurred in clear weather and daylight on dry roads. In 2025, 76.3% of crashes happened on dry surfaces, a decrease from 84.1% in 2024. Consequently, the proportion of crashes on non-dry surfaces like wet, snow, or ice, increased from 15.7% in 2024 to 19.1% in 2025. Proportions for lighting and weather conditions remained largely stable year-over-year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained the same in both 2024 and 2025, with counts decreasing for all three in line with the overall crash reduction. The age distribution of persons involved in crashes was also consistent, with the 26-34 age group being the largest in both periods. There was a slight proportional increase in the involvement of the 16-20 age group, from 5.4% of all persons in 2024 to 6.2% in 2025.
Top Vehicle Makes (1,388 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
232 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,524 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The vast majority of crashes in both years occurred in 25 mph zones, accounting for 771 crashes in 2024 and 539 in 2025. The single fatal crash in 2025 was in a 25 mph zone, whereas 2024 saw fatalities in both 25 mph and 50 mph zones. While overall crashes decreased, the number of incidents in speed zones of 45 mph or higher remained nearly identical, with 52 in 2024 and 53 in 2025.
Fatal crashes by zone: 25 mph: 1 of 539 (0.186%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: CHELSEA, MA
- Total crash records analyzed: 696
- Total persons involved: 1,780
- Total vehicles involved: 1,388
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelsea/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved