ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GARDNER, MA · FEBRUARY 2025
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/february-2025-report
Monthly Traffic Safety Analysis
60 CRASHES IN
GARDNER, MA
FEBRUARY 2025
Total crashes in Gardner for February 2025 were 60, an increase from 47 crashes reported in February 2024, representing a 27.66% rise. A notable positive shift was the absence of fatalities in February 2025, down from 1 fatality in the prior year. Injuries, however, increased by 83.33%, from 6 to 11.
60
▲ 27.7%was 47
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
11
▲ 83.3%was 6
Persons Injured
5
▲ 150.0%was 2
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 · 2025-02-01 to 2025-02-28 · 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 27.66% from 47 to 60. While total injuries rose significantly from 6 to 11, representing an 83.33% increase, fatalities decreased from 1 in February 2024 to 0 in February 2025.
5
Hit-and-Run Crashes — February 2025
▲ 150.0% vs prior (2)
Hit-and-run crashes increased from 2 incidents in February 2024 to 5 incidents in February 2025. This resulted in the hit-and-run crash rate rising from 4.3% to 8.3% of all crashes, an increase of 4.0 percentage points.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
10
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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 Friday with 11 incidents in February 2024 to Wednesday with 13 incidents in February 2025. Monday saw a substantial increase in crashes, rising from 4 to 10. The peak crash hour remained consistent at 3 p.m. in both periods, with 8 crashes in February 2024 and 10 crashes in February 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes were eliminated in February 2025, dropping from 1 in the prior year to 0. Minor injury crashes increased from 4 to 7, and possible injury crashes rose from 1 to 2. Consequently, the share of crashes resulting in no injury decreased from 83% in February 2024 to 78.3% in February 2025.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record
Top Contributing Factors
Contributing factor 'No improper driving' saw a significant increase, rising from 6 incidents in February 2024 to 16 in February 2025, a 166.67% rise in count. Conversely, 'Inattention' decreased by 8 incidents, from 20 to 12. 'Followed too closely' crashes quadrupled, increasing from 1 to 4 incidents, a 300% rise in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 35 to 27, while those in cloudy conditions more than tripled, rising from 5 to 16 incidents. Crashes on snow-covered road surfaces increased from 1 to 10. The number of crashes occurring in daylight increased from 33 to 43, and those in unlit dark conditions increased from 1 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 89 to 104, a 16.85% rise. Toyota remained the top vehicle make involved in crashes, though its count decreased from 18 to 13. Honda vehicles involved in crashes doubled from 6 to 12, moving from the eighth most frequent make to the second. In terms of persons involved, the 16-20 age group saw a significant increase from 4 to 15 individuals, while the 0-15 age group decreased from 14 to 6.
Top Vehicle Makes (104 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records
19 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (105 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph speed zones saw the largest increase, rising from 16 incidents in February 2024 to 26 in February 2025. Crashes in 50 mph zones increased from 1 to 3, with the prior period recording 1 fatal crash in this zone, while the current period had none. Crashes in 5 mph zones decreased from 4 to 1.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-02-01 through 2025-02-28 (28 days)
- Geographic scope: GARDNER, MA
- Total crash records analyzed: 60
- Total persons involved: 124
- Total vehicles involved: 104
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: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gardner/february-2025-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: 2025-02-01 – 2025-02-28
Generated: June 21, 2026 · All rights reserved