ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · EVERETT, MA · 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/everett/2024-annual-report
Yearly Traffic Safety Analysis
320 CRASHES IN
EVERETT, MA
2024
In 2024, Everett recorded 320 total traffic crashes, a 7.3% decrease from the 345 crashes reported in 2023. The most notable year-over-year change was the reduction in fatalities, with zero deaths reported in 2024 compared to two in the prior year. Total injuries also declined by 9.0%, from 144 to 131.
320
▼ -7.2%was 345
Total Crash Events
0
▼ -100.0%was 2
Persons Killed
131
▼ -9.0%was 144
Persons Injured
24
▲ 14.3%was 21
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. 6 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in traffic crashes in Everett shows a year-over-year decrease. Total collisions fell by 7.3%, from 345 in 2023 to 320 in 2024. This downward trend was also reflected in crash outcomes, with total injuries declining by 9.0% and fatalities decreasing from two to zero.
24
Hit-and-Run Crashes — 2024
▲ 14.3% vs prior (21)
Hit-and-run incidents increased in both count and rate year-over-year. The number of hit-and-run crashes rose from 21 in 2023 to 24 in 2024. This corresponds to an increase in the hit-and-run rate, which climbed from 6.1% of all crashes in 2023 to 7.5% in 2024, indicating an upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
5
Pedestrians Injured
6
Cyclists Injured
114
Motorists Injured
6
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In 2024, the peak day for crashes was Saturday with 59 incidents, a change from 2023 when Monday was the peak day with 60 incidents. The peak hour also moved from 9 p.m. in 2023 (22 crashes) to the midday hour of 12 p.m. in 2024 (25 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity decreased notably in 2024, with zero fatal crashes recorded, compared to two fatal crashes in 2023. The number of crashes resulting in serious injuries also fell from five to three. While the overall proportion of crashes involving any injury remained relatively stable (32.5% in 2024 vs. 33.3% in 2023), the total number of injury-producing crashes decreased.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' was a leading factor in both periods, its count decreased from 61 in 2023 to 54 in 2024. A notable shift occurred with 'Followed too closely,' which saw its count increase by 33.3% from 30 to 40 incidents, moving it to the second-ranked factor in 2024. Conversely, crashes attributed to 'Disregarded traffic signs, signals, road markings' decreased in count by 26.3% (from 38 to 28).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In 2024, a higher proportion of crashes occurred in clear weather (80.6%) compared to 2023 (73.3%). Correspondingly, crashes on wet road surfaces decreased, accounting for 12.2% of incidents in 2024, down from 17.1% in the prior year. The distribution of crashes by lighting condition remained largely consistent, with daylight crashes making up 61.9% of the total in 2024, compared to 57.7% in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in crashes remained consistent year-over-year, with Toyota, Honda, Ford, Nissan, and Chevrolet leading in both periods. While the number of Toyotas involved decreased from 144 to 128, Hondas saw an increase from 114 to 123. Analysis of persons involved shows a shift in age demographics; the proportion of individuals in the 26-34 age group grew from 19.6% of all persons in 2023 to 23.1% in 2024.
Top Vehicle Makes (638 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
79 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (689 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes by speed zone showed some changes. While the number of crashes in 25 mph zones remained stable (183 in 2024 vs. 181 in 2023), there was a notable decrease in crashes within 35 mph zones, falling from 127 to 102. In 2023, both fatal crashes occurred in 25 mph zones; in 2024, there were no fatalities recorded in any speed zone.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: EVERETT, MA
- Total crash records analyzed: 320
- Total persons involved: 785
- Total vehicles involved: 638
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). "EVERETT, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/everett/2024-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved