ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BEVERLY, MA · NOVEMBER 2022
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/beverly/november-2022-report
Monthly Traffic Safety Analysis
43 CRASHES IN
BEVERLY, MA
NOVEMBER 2022
In November 2022, BEVERLY experienced 43 total crashes, a 17.3% decrease from the 52 crashes recorded in November 2021. Fatalities remained at 0 in both periods, while total injuries were stable at 13. A notable shift was the 100% increase in crashes attributed to 'No improper driving', rising from 7 in the prior period to 14 in the current period.
43
▼ -17.3%was 52
Total Crash Events
0
Persons Killed
13
Persons Injured
2
▼ -50.0%was 4
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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a decrease in total crashes, with a 17.3% reduction from 52 crashes in November 2021 to 43 crashes in November 2022. Total injuries remained consistent at 13 in both periods, and there were no reported fatalities in either November.
2
Hit-and-Run Crashes — November 2022
▼ -50.0% vs prior (4)
Hit-and-run crashes decreased from 4 in November 2021 to 2 in November 2022. The hit-and-run rate also decreased from 7.7% of total crashes in the prior period to 4.7% in the current period, indicating a downward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
11
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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 Tuesday in November 2021, which had 11 crashes, to Sunday in November 2022, which recorded 10 crashes. Similarly, the peak crash hour moved from 1 PM in November 2021 to 6 PM in November 2022, with both peak hours recording 6 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at 0 in both November 2021 and November 2022. Minor injury crashes decreased from 5 (9.6% share) in the prior period to 4 (9.3% share) in the current period, while possible injury crashes increased from 4 (7.7% share) to 8 (18.6% share). No injury crashes saw a decrease from 35 (67.3% share) to 27 (62.8% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor 'No improper driving' increased by 100% in count, rising from 7 crashes in November 2021 to 14 crashes in November 2022. Conversely, 'Failed to yield right of way' decreased by 62.5% in count, from 8 crashes to 3 crashes. 'Inattention' remained stable with 4 crashes in both periods, while 'Disregarded traffic signs, signals, road markings' decreased from 4 crashes to 0 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear/Clear' weather decreased from 42 in November 2021 to 33 in November 2022, while crashes in 'Rain/Rain' conditions increased from 1 to 5. Crashes on 'Dry' road surfaces decreased from 48 to 35, whereas crashes on 'Wet' road surfaces increased from 3 to 8. Crashes in 'Daylight' decreased from 31 to 21, but crashes in 'Dark - lighted roadway' increased from 16 to 18.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field
Vehicles & Demographics
The number of persons aged 0-15 involved in crashes increased from 10 in November 2021 to 18 in November 2022, and the 26-34 age group also saw an increase from 8 to 17 persons. Conversely, the 35-44 age group decreased from 15 to 5 persons, and the 55-64 age group decreased from 17 to 9 persons. Among vehicle makes, TOYOTA crashes decreased from 16 to 8, HONDA crashes decreased from 15 to 7, and JEEP crashes decreased from 11 to 4.
Top Vehicle Makes (73 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records
9 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (99 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed limit zone slightly decreased from 22 in November 2021 to 21 in November 2022, and crashes in the 30 mph zone decreased from 12 to 9. Conversely, crashes in the 35 mph zone increased from 5 to 7. All reported speed limit zones maintained 0 fatalities in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-11-01 through 2022-11-30 (30 days)
- Geographic scope: BEVERLY, MA
- Total crash records analyzed: 43
- Total persons involved: 108
- Total vehicles involved: 73
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). "BEVERLY, MA Crash Intelligence Report: November 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/beverly/november-2022-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: 2022-11-01 – 2022-11-30
Generated: June 21, 2026 · All rights reserved