ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NORTH ANDOVER, MA · JUNE 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/north-andover/june-2022-report
Monthly Traffic Safety Analysis
45 CRASHES IN
NORTH ANDOVER, MA
JUNE 2022
In June 2022, NORTH ANDOVER experienced 45 crashes, marking a 25% increase from the 36 crashes reported in June 2021. Total injuries decreased from 9 to 7 during this period, while fatalities remained at zero in both years. The most notable shift was the significant increase in Angle collisions, which rose from 7 to 18, and Rear-end collisions, which increased from 7 to 13.
45
▲ 25.0%was 36
Total Crash Events
0
Persons Killed
7
▼ -22.2%was 9
Persons Injured
1
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in NORTH ANDOVER showed an upward trend, with total crashes increasing by 25% from 36 in June 2021 to 45 in June 2022. Despite this rise in total crashes, the number of reported injuries decreased by 22.2%, from 9 in June 2021 to 7 in June 2022. Fatalities remained consistently at zero for both periods.
1
Hit-and-Run Crashes — June 2022
2.2% hit-and-run rate this period vs 0.0% prior. Prior period: 0.
Vulnerable Road User Casualties
0
Motorists Killed
7
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted year-over-year, with the peak day moving from Sunday (7 crashes) in June 2021 to Wednesday (10 crashes) in June 2022. Similarly, the peak hour changed from 1 PM (6 crashes) in June 2021 to 5 PM (5 crashes) in June 2022. Monday and Tuesday also saw notable increases, with crashes on Monday rising from 6 to 10 and on Tuesday from 5 to 9.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes increased, the overall severity distribution changed, with no fatal crashes reported in either June 2021 or June 2022. Crashes resulting in serious injuries (code A) decreased from 2 in June 2021 to 0 in June 2022. Conversely, crashes with possible injuries (code C) increased from 1 to 2, and crashes with no injuries (code O) rose from 28 to 39.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors saw shifts in their prevalence and ranking. 'No improper driving' became the top factor in June 2022 with 17 crashes, up from 12 crashes in June 2021, while 'Inattention' decreased from 13 crashes to 10 crashes. 'Failed to yield right of way' also saw a significant increase, rising from 1 crash in June 2021 to 5 crashes in June 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 34 in June 2021 to 40 in June 2022, while cloudy conditions saw a slight rise from 1 to 2 crashes. There was an increase in crashes occurring in dark conditions with lighted roadways, rising from 1 in June 2021 to 4 in June 2022, and 2 crashes occurred at dusk in June 2022 which were not recorded in June 2021. The road surface data for June 2021 was not available for comparison.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 64 in June 2021 to 87 in June 2022. FORD became the most frequently involved make with 12 vehicles, up from 9, surpassing HONDA which had 10 vehicles. NISSAN vehicles involved in crashes significantly increased from 4 to 10, moving it to the third most common make in June 2022.
Top Vehicle Makes (87 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records
7 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (93 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes saw a shift towards higher speed zones, with incidents in 40 mph zones increasing from 9 to 16, and 35 mph zones rising from 7 to 13. Conversely, crashes in 30 mph zones decreased from 6 to 4, and 45 mph zones saw a reduction from 4 to 1. No fatal crashes were reported across any speed zones in either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-06-01 through 2022-06-30 (30 days)
- Geographic scope: NORTH ANDOVER, MA
- Total crash records analyzed: 45
- Total persons involved: 104
- Total vehicles involved: 87
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). "NORTH ANDOVER, MA Crash Intelligence Report: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-andover/june-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: 2022-06-01 – 2022-06-30
Generated: June 21, 2026 · All rights reserved