ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FITCHBURG, MA · SEPTEMBER 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/fitchburg/september-2023-report
Monthly Traffic Safety Analysis
126 CRASHES IN
FITCHBURG, MA
SEPTEMBER 2023
Total crashes in Fitchburg, MA increased by 44.83% from 87 in September 2022 to 126 in September 2023. This period saw a notable increase in hit-and-run crashes, which rose from 2 to 22 year-over-year. Fatalities remained at zero for both periods.
126
▲ 44.8%was 87
Total Crash Events
0
Persons Killed
29
▲ 11.5%was 26
Persons Injured
22
▲ 1000.0%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. 13 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates an increase in crash activity, with total crashes rising from 87 to 126, representing a 44.83% increase. Total injuries also saw a slight increase, from 26 to 29, over the same period.
22
Hit-and-Run Crashes — September 2023
▲ 1000.0% vs prior (2)
Hit-and-run crashes increased significantly from 2 in September 2022 to 22 in September 2023. This represents a substantial rise in the hit-and-run rate, from 2.3% of total crashes in the prior period to 17.5% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
4
Pedestrians Injured
25
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Wednesday with 17 crashes in September 2022 to Thursday with 28 crashes in September 2023. The peak hour also shifted from 5 PM with 10 crashes in the prior period to 4 PM with 21 crashes in the current period. Crashes on Saturdays doubled, increasing from 8 to 16.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either September 2022 or September 2023. Serious injury crashes (severity 'A') increased from 1 (1.1% of crashes) in the prior period to 4 (3.2% of crashes) in the current period. Minor injury crashes (severity 'B') slightly decreased from 12 (13.8% of crashes) to 11 (8.7% of crashes), despite an overall increase in total crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'No improper driving,' increased significantly from 5 crashes in September 2022 to 39 crashes in September 2023. 'Inattention' decreased slightly from 23 crashes to 21 crashes, while 'Followed too closely' increased from 10 to 12 crashes. Crashes involving 'Exceeded authorized speed limit' increased from 0 to 2.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 68 to 97, though their share of total crashes slightly decreased from 78.2% to 77%. Crashes during rain conditions increased from 9 to 18, raising their share from 10.3% to 14.3%. Similarly, crashes on wet road surfaces increased from 15 to 26, and their share of total crashes rose from 17.2% to 20.6%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 205 to 278 year-over-year. The 16-20 age group saw a decrease in involved persons from 35 to 22, while the 35-44 age group experienced a notable increase from 29 to 45 involved persons. Toyota remained the top vehicle make involved, increasing from 25 to 30, and Chevrolet saw a significant increase from 14 to 26 vehicles involved.
Top Vehicle Makes (238 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Vehicle unit records
46 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (230 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Person-level records linked to crash events
Speed Limit Zones
No fatal crashes were recorded in any speed zone for either period. Crashes occurring in 25 mph speed zones saw a substantial increase from 36 to 68. Crashes in 30 mph zones remained relatively stable, decreasing slightly from 24 to 23.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · 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: 2023-09-01 through 2023-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-09-01 through 2023-09-30 (30 days)
- Geographic scope: FITCHBURG, MA
- Total crash records analyzed: 126
- Total persons involved: 278
- Total vehicles involved: 238
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 2023." Published June 21, 2026. Reporting period: 2023-09-01 to 2023-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fitchburg/september-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: 2023-09-01 – 2023-09-30
Generated: June 21, 2026 · All rights reserved