ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FITCHBURG, MA · JUNE 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/fitchburg/june-2025-report
Monthly Traffic Safety Analysis
121 CRASHES IN
FITCHBURG, MA
JUNE 2025
In June 2025, Fitchburg experienced 121 total crashes, marking a 30.1% increase from the 93 crashes reported in June 2024. Total injuries rose significantly by 110.5%, from 19 to 40, making this the most notable year-over-year shift. Fatalities remained at zero for both periods.
121
▲ 30.1%was 93
Total Crash Events
0
Persons Killed
40
▲ 110.5%was 19
Persons Injured
13
▲ 18.2%was 11
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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a rise in crash incidents, with total crashes increasing by 30.1% from 93 in June 2024 to 121 in June 2025. Concurrently, the number of injured persons saw a substantial increase of 110.5%, from 19 to 40. There were no fatal crashes in either period.
13
Hit-and-Run Crashes — June 2025
▲ 18.2% vs prior (11)
The number of hit-and-run crashes increased by 18.2%, from 11 in June 2024 to 13 in June 2025. Despite this increase in count, the hit-and-run rate decreased slightly from 11.8% of total crashes to 10.7%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
2
Pedestrians Injured
2
Cyclists Injured
35
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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 Monday with 17 crashes in June 2024 to Friday with 20 crashes in June 2025. The peak crash hour also moved from 11 AM with 9 crashes in June 2024 to 5 PM with 12 crashes in June 2025. Notably, crashes on Sundays more than doubled, rising from 9 to 19 year-over-year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While no fatal crashes occurred in either period, total injuries increased from 19 in June 2024 to 40 in June 2025. Minor injury crashes rose from 11 to 23, and possible injury crashes increased from 4 to 5. Serious injury crashes, which accounted for 1.1% of total crashes in June 2024, were not reported in June 2025.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'No improper driving' increased by 100% in count, from 15 to 30, and its share of crashes rose from 16.1% to 24.8%. 'Inattention' crashes increased by 23.5% in count, from 17 to 21, though its share slightly decreased from 18.3% to 17.4%. 'Followed too closely' crashes saw a 300% increase in count, from 3 to 12, and its share of crashes nearly tripled from 3.2% to 9.9%.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased by 20.9%, from 81 to 98, while those in 'Rain' increased by 60%, from 5 to 8. Crashes on 'Dry' road surfaces rose by 25.9% from 85 to 107, and those on 'Wet' surfaces increased by 62.5% from 8 to 13. The number of crashes during 'Daylight' conditions increased by 31.1% from 74 to 97.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased by 37.6% from 226 to 311, and total vehicles increased by 32.4% from 170 to 225. The 16-20 age group saw a 121.7% increase in persons involved, rising from 23 to 51, and the 55-64 age group increased by 115.4% from 13 to 28. Subaru vehicles involved in crashes saw a significant increase of 316.7%, moving from 6 to 25 and rising from the 8th to the 3rd most common make.
Top Vehicle Makes (225 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records
39 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (274 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones increased by 41.7%, from 36 to 51, and those in 55 mph zones doubled from 4 to 8. Crashes in 5 mph zones increased by 166.7%, from 3 to 8, while crashes in 10 mph zones decreased by 50% from 8 to 4. There were no fatal crashes reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-06-01 through 2025-06-30 (30 days)
- Geographic scope: FITCHBURG, MA
- Total crash records analyzed: 121
- Total persons involved: 311
- Total vehicles involved: 225
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). "FITCHBURG, MA Crash Intelligence Report: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fitchburg/june-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: 2025-06-01 – 2025-06-30
Generated: June 21, 2026 · All rights reserved