ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELSEA, MA · FEBRUARY 2023
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/february-2023-report
Monthly Traffic Safety Analysis
71 CRASHES IN
CHELSEA, MA
FEBRUARY 2023
Total crashes in Chelsea increased by 9.23%, from 65 in February 2022 to 71 in February 2023. This period saw a notable shift with the occurrence of 1 fatal crash, compared to 0 in the prior year, while total injuries decreased from 27 to 15.
71
▲ 9.2%was 65
Total Crash Events
1
Persons Killed
15
▼ -44.4%was 27
Persons Injured
2
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. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in Chelsea showed an upward trend, increasing by 9.23% from 65 incidents in February 2022 to 71 in February 2023. Fatalities rose from 0 to 1, marking a significant change, while total injuries decreased by 44.4% from 27 to 15.
2
Hit-and-Run Crashes — February 2023
▼ 0.0% vs prior (2)
The number of hit-and-run crashes remained consistent at 2 incidents in both February 2022 and February 2023. Consequently, the hit-and-run rate decreased slightly from 3.1% in the prior period to 2.8% in the current period, relative to the overall increase in total crashes.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
1
Pedestrians Injured
1
Cyclists Injured
12
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Wednesday, with 13 crashes in February 2022, to Friday, with 15 crashes in February 2023. Similarly, the peak hour for crashes moved from 6 p.m. (5 crashes) in the prior period to 12 p.m. (6 crashes) in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The current period recorded 1 fatal crash, accounting for 1.4% of all crashes, a change from 0 fatal crashes in the prior period. Minor injury crashes decreased from 14 (21.5% share) to 6 (8.5% share), while possible injury crashes increased from 3 (4.6% share) to 7 (9.9% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'No improper driving' increased by 10, from 23 in the prior period to 33 in the current period, a 43.5% increase in count. Crashes involving 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased by 2, from 1 to 3, a 200% increase in count. Factors such as 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway' and 'Physical impairment' were present in the prior period but not in the current period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased by 19, from 36 to 55, while crashes in 'Rain' conditions decreased by 6, from 7 to 1. Crashes on 'Dry' road surfaces saw a substantial increase of 33, from 20 to 53, contrasting with a decrease of 17 crashes on 'Wet' road surfaces, from 24 to 7. Crashes in 'Daylight' and 'Dark - lighted roadway' conditions both increased by 4 incidents each.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Road surface condition field
Vehicles & Demographics
The age group 35-44 saw the largest increase in persons involved in crashes, rising by 13 from 30 to 43, while the 26-34 age group experienced the largest decrease, falling by 9 from 45 to 36. Toyota became the most frequently involved vehicle make with 26 incidents, surpassing Honda, which dropped to 20 incidents from 24 in the prior period.
Top Vehicle Makes (135 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Vehicle unit records
18 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (166 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Person-level records linked to crash events
Speed Limit Zones
The number of crashes in 25 mph speed zones increased by 7, from 45 to 52, and this zone accounted for the single fatal crash in the current period, compared to none in the prior period. Crashes in 20 mph zones decreased by 2, from 6 to 4, and crashes in 55 mph zones also decreased by 2, from 3 to 1.
Fatal crashes by zone: 25 mph: 1 of 52 (1.923%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-02-01 through 2023-02-28 (28 days)
- Geographic scope: CHELSEA, MA
- Total crash records analyzed: 71
- Total persons involved: 184
- Total vehicles involved: 135
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: February 2023." Published June 21, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelsea/february-2023-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: 2023-02-01 – 2023-02-28
Generated: June 21, 2026 · All rights reserved