ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELSEA, MA · 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/2023-annual-report
Yearly Traffic Safety Analysis
1,051 CRASHES IN
CHELSEA, MA
2023
In 2023, Chelsea recorded 1,051 total traffic crashes, an 18.4% increase from the 888 crashes reported in 2022. Total injuries rose from 331 to 349, while fatalities remained stable at two. The most significant year-over-year change was a 71.9% increase in the number of hit-and-run incidents, which rose from 32 to 55.
1,051
▲ 18.4%was 888
Total Crash Events
2
Persons Killed
349
▲ 5.4%was 331
Persons Injured
55
▲ 71.9%was 32
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 43 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends in Chelsea worsened from 2022 to 2023. The total number of crashes rose by 18.4% from 888 to 1,051, and total injuries increased by 5.4% from 331 to 349. The number of fatalities remained unchanged at two for both years.
55
Hit-and-Run Crashes — 2023
▲ 71.9% vs prior (32)
Hit-and-run incidents increased significantly in 2023 compared to the prior year. The total count of hit-and-run crashes rose from 32 to 55, a 71.9% increase. This pushed the hit-and-run rate, as a percentage of all crashes, up from 3.6% in 2022 to 5.2% in 2023.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
31
Pedestrians Injured
11
Cyclists Injured
305
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal crash patterns shifted year-over-year, with the peak day for crashes moving from Monday (147 crashes) in 2022 to Saturday (183 crashes) in 2023. While the 4 p.m. hour remained the peak time for collisions in both periods, the number of crashes during this hour increased by 36.5%, from 63 to 86. Crashes on Saturdays saw a 45.2% increase from 126 in the prior year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes remained stable at two in both 2023 and 2022, though the fatal crash rate as a percentage of all crashes decreased from 0.23% to 0.19% due to the higher total crash volume. The proportion of crashes resulting in serious injuries fell from 2.7% to 1.4% year-over-year. Correspondingly, the share of non-injury crashes increased from 67.1% in 2022 to 73.9% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors saw a notable increase in reported instances between the two periods. Crashes attributed to 'Other improper action' grew by 86.4% in count, from 22 to 41 incidents, while those linked to an 'Operating vehicle in erratic... manner' increased by 58.3% from 24 to 38. Crashes involving 'Inattention' also rose by 50% in count, from 20 to 30. The top-ranked factor in both years, 'No improper driving', increased in count from 292 to 369.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes increased across all conditions, reflecting the overall upward trend. The largest absolute increase was in crashes occurring in daylight, which rose from 524 to 652, and on dry roads, which increased from 696 to 868. The proportional distribution of crashes by lighting, weather, and road surface condition remained largely consistent, with a slight increase in the share of crashes happening on dry roads (from 78.4% to 82.6%).
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—retained their rankings from the prior year, with all showing an increase in counts. Notably, the number of Nissans involved in crashes grew by 46.8%, from 109 to 160. Analysis of persons involved shows the largest year-over-year increases in the 35-44 age group (from 383 to 508 persons) and the 26-34 age group (from 447 to 563 persons).
Top Vehicle Makes (2,114 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
318 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,358 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones, which accounted for the majority of incidents, increased from 649 to 767 year-over-year. There were also substantial relative increases in higher speed zones, with crashes in 45 mph zones rising from 19 to 55 and in 40 mph zones increasing from 24 to 46. In 2023, both fatal crashes occurred in 25 mph zones, whereas in 2022, one fatality occurred in a 25 mph zone and the other in a 55 mph zone.
Fatal crashes by zone: 25 mph: 2 of 767 (0.261%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: CHELSEA, MA
- Total crash records analyzed: 1,051
- Total persons involved: 2,698
- Total vehicles involved: 2,114
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelsea/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved