ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GARDNER, MA · OCTOBER 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/gardner/october-2023-report
Monthly Traffic Safety Analysis
49 CRASHES IN
GARDNER, MA
OCTOBER 2023
In October 2023, Gardner experienced 49 crashes, an increase from the 37 crashes recorded in October 2022. This represents a 32.43% rise in total crashes year-over-year. A notable shift was the 200% increase in total injuries, from 6 in October 2022 to 18 in October 2023.
49
▲ 32.4%was 37
Total Crash Events
1
Persons Killed
18
▲ 200.0%was 6
Persons Injured
3
▲ 50.0%was 2
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Gardner show an upward trend year-over-year, with total crashes increasing by 32.43% from 37 in October 2022 to 49 in October 2023. Concurrently, the number of injured persons saw a substantial rise of 200%, from 6 to 18.
3
Hit-and-Run Crashes — October 2023
▲ 50.0% vs prior (2)
The number of hit-and-run crashes increased from 2 in October 2022 to 3 in October 2023. The hit-and-run crash rate also saw a slight increase, rising from 5.4% in the prior period to 6.1% in the current period, indicating an upward trend.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
2
Cyclists Injured
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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 Wednesday in October 2022 (7 crashes) to Monday in October 2023 (11 crashes). While the peak hour remained 3p for both periods, the number of crashes at that hour decreased from 6 in October 2022 to 5 in October 2023. Notably, Monday crashes increased by 83.33% from 6 to 11 year-over-year, and Friday crashes doubled from 3 to 6.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes remained consistent at 1 in both October 2022 and October 2023, though the fatal crash rate decreased from 2.7% to 2.04% due to the overall increase in crashes. Minor injury crashes saw a significant increase, rising from 2 (5.4% share) in the prior period to 9 (18.4% share) in the current period. Conversely, possible injury crashes decreased from 3 (8.1% share) to 2 (4.1% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor shifted from 'Inattention' in October 2022 to 'No improper driving' in October 2023. Crashes attributed to 'No improper driving' increased from 2 to 13, representing a 550% rise in count. Conversely, 'Inattention' related crashes decreased by 43.75%, from 16 to 9. 'Failed to yield right of way' also saw a substantial increase in count, from 3 to 8.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The number of crashes occurring in clear weather remained stable at 26, while those in wet road conditions doubled from 6 in October 2022 to 12 in October 2023. Crashes occurring during rain-related conditions also increased, from 3 in the prior period to 10 in the current period. Incidents in daylight increased from 31 to 36, and crashes in dark-lighted roadway conditions increased from 5 to 8.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field
Vehicles & Demographics
Toyota vehicles were involved in 16 crashes in October 2023, up from 9 in October 2022, making it the top make in the current period. Ford vehicles remained stable with 11 involvements in both periods, while Honda involvements decreased from 10 to 5. The age group 0-15 saw a significant increase in persons involved, rising from 5 to 19, and persons aged 65+ saw a decrease from 16 to 10.
Top Vehicle Makes (84 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records
16 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (102 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph speed zones saw a substantial increase, rising from 14 in October 2022 to 34 in October 2023, a 142.86% increase. This speed zone accounted for the single fatal crash in both periods, though its fatal crash rate decreased from 7.143% to 2.941%. Conversely, crashes in 20 mph zones decreased from 6 to 5, and in 25 mph zones from 5 to 3.
Fatal crashes by zone: 30 mph: 1 of 34 (2.941%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-10-01 through 2023-10-31 (31 days)
- Geographic scope: GARDNER, MA
- Total crash records analyzed: 49
- Total persons involved: 120
- Total vehicles involved: 84
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: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gardner/october-2023-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: 2023-10-01 – 2023-10-31
Generated: June 21, 2026 · All rights reserved