ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FITCHBURG, MA · SEPTEMBER 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/september-2025-report
Monthly Traffic Safety Analysis
107 CRASHES IN
FITCHBURG, MA
SEPTEMBER 2025
In September 2025, Fitchburg experienced 107 crashes, a 4.5% decrease compared to the 112 crashes recorded in September 2024. Despite the overall decrease in crashes, total injuries rose by 70.6% from 17 to 29. The most notable shift was the significant increase in reported injuries.
107
▼ -4.5%was 112
Total Crash Events
0
Persons Killed
29
▲ 70.6%was 17
Persons Injured
8
▼ -20.0%was 10
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 · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Total crashes in Fitchburg decreased by 4.5% year-over-year, from 112 crashes in September 2024 to 107 crashes in September 2025. This indicates a slight downward trend in overall crash frequency. However, injuries increased by 70.6%, suggesting a rise in the severity of incidents.
8
Hit-and-Run Crashes — September 2025
▼ -20.0% vs prior (10)
Hit-and-run crashes decreased from 10 incidents in September 2024 to 8 incidents in September 2025. The hit-and-run rate also decreased from 8.9% to 7.5% of all crashes. This indicates a downward trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Motorists Killed
0
Other Killed
28
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Monday in both periods, with 23 crashes in September 2025 and 22 in September 2024. However, the peak hour shifted from 7 AM in September 2024 to 2 PM in September 2025, with both periods recording 13 crashes during their respective peak hours.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero in both September 2024 and September 2025. Total injuries increased significantly by 70.6%, from 17 to 29. While serious injuries remained constant at 2, minor injuries rose from 12 (10.7% of crashes) to 15 (14% of crashes), and crashes with no injuries decreased from 94 to 83.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors remained consistent, with 'No improper driving' increasing by 3 crashes to 31, and 'Inattention' increasing by 2 crashes to 27. 'Failed to yield right of way' also saw a slight increase of 1 crash, reaching 11 incidents. Conversely, 'Followed too closely' decreased by 2 crashes, and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased by 2 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions remained largely stable, with 96 incidents in September 2025 compared to 95 in September 2024. However, crashes during rainy conditions decreased from 7 to 3, and crashes on wet road surfaces decreased from 11 to 6. Crashes during daylight hours also saw a slight reduction from 91 to 87.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field
Vehicles & Demographics
Toyota remained the most frequently involved vehicle make, increasing from 35 to 37 vehicles, while Ford also saw a slight increase from 24 to 26. Honda involvement increased from 19 to 26 vehicles, moving it higher in the rankings. Among persons involved, the 21-25 age group saw a decrease from 37 to 24, while the 26-34 age group increased from 34 to 37.
Top Vehicle Makes (206 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records
24 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (240 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 mph zones decreased by 7, from 46 in September 2024 to 39 in September 2025. Similarly, 30 mph zones saw a minor decrease of 1 crash, from 35 to 34. Conversely, crashes in 35 mph zones increased by 5, from 6 to 11, indicating a shift in crash distribution towards higher speed limit areas.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-09-01 through 2025-09-30 (30 days)
- Geographic scope: FITCHBURG, MA
- Total crash records analyzed: 107
- Total persons involved: 266
- Total vehicles involved: 206
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: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fitchburg/september-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: 2025-09-01 – 2025-09-30
Generated: June 21, 2026 · All rights reserved