ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GARDNER, 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/gardner/november-2022-report
Monthly Traffic Safety Analysis
54 CRASHES IN
GARDNER, MA
NOVEMBER 2022
In November 2022, there were 54 crashes, a slight decrease of 1 crash (1.82%) compared to the 55 crashes recorded in November 2021. The most significant year-over-year shift was the increase in total fatalities, rising from 0 in the prior period to 2 in the current period.
54
▼ -1.8%was 55
Total Crash Events
2
Persons Killed
9
▲ 28.6%was 7
Persons Injured
1
▼ -50.0%was 2
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.
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
Overall, the number of crashes in November 2022 remained relatively stable, with a minor decrease of 1 crash (1.82%) compared to November 2021. However, the period saw an concerning increase in severity, with total fatalities rising from 0 to 2 and total injuries increasing by 2 (28.57%) from 7 to 9.
1
Hit-and-Run Crashes — November 2022
▼ -50.0% vs prior (2)
The number of hit-and-run crashes decreased from 2 in November 2021 to 1 in November 2022. Consequently, the hit-and-run rate trended downward, falling from 3.6% in the prior period to 1.9% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
2
Motorists Killed
1
Pedestrians Injured
8
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 (14 crashes) to Monday in November 2022 (11 crashes). The peak crash hour also changed, moving from 11 AM with 6 crashes in the prior period to 1 PM with 7 crashes in the current period. Notably, crashes on Tuesdays decreased significantly from 14 to 9, while crashes on Mondays increased from 8 to 11.
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
The fatal crash rate increased from 0% in November 2021 to 3.7% in November 2022, with 2 fatal crashes occurring in the current period compared to none in the prior period. The proportion of crashes resulting in any injury also rose from 12.73% in the prior period to 16.67% in the current period. While there were 3 serious injuries in the prior period, the current period recorded 1 serious injury, 7 minor injuries, and 1 possible injury, totaling 9 injured persons compared to 7 previously.
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
Inattention became the leading contributing factor in November 2022, with 16 crashes, a 100% increase in count from 8 crashes in the prior period. Crashes attributed to 'No improper driving' decreased by 5, from 11 to 6. 'Failed to yield right of way' crashes increased by 3 (75% increase in count), from 4 to 7, and 'Followed too closely' crashes also doubled from 3 to 6.
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 weather conditions slightly increased from 37 in November 2021 to 39 in November 2022, while crashes on dry road surfaces remained stable, increasing by only 1 from 45 to 46. There was a notable decrease in crashes occurring in dark conditions, with 'Dark - lighted roadway' incidents falling from 12 to 7 and 'Dark - roadway not lighted' incidents decreasing from 8 to 6. The current period also saw no crashes on snowy road surfaces, compared to 3 in the prior period.
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 top vehicle makes involved in crashes saw some shifts, with Toyota remaining the most frequent (19 vs 15) and Subaru experiencing a significant increase from 7 to 15 vehicles. Chevrolet involvement decreased from 15 to 11, while Ford increased from 9 to 14, and Nissan increased from 6 to 11. All reported age groups showed an increase in persons involved in crashes, with the 0-15 age group seeing a rise from 2 to 8 individuals, and the 45-54 age group increasing from 9 to 17 individuals.
Top Vehicle Makes (102 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records
10 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (119 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 occurring in 30 mph speed zones increased from 19 in November 2021 to 22 in November 2022, while crashes in 20 mph zones decreased from 16 to 8. Notably, the 50 mph speed zone recorded 1 fatal crash in the current period, whereas no fatal crashes were reported in any speed zone in the prior period. Overall, there was a shift away from lower speed zones like 5 mph and 20 mph, with an increase in crashes in the 30 mph zone.
Fatal crashes by zone: 50 mph: 1 of 3 (33.333%)
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: GARDNER, MA
- Total crash records analyzed: 54
- Total persons involved: 130
- Total vehicles involved: 102
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). "GARDNER, 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/gardner/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