ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FITCHBURG, MA · JANUARY 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/january-2023-report
Monthly Traffic Safety Analysis
82 CRASHES IN
FITCHBURG, MA
JANUARY 2023
In January 2023, Fitchburg experienced 82 total crashes, a 34.4% increase compared to the 61 crashes recorded in January 2022. Total injuries rose significantly by 128.6%, from 7 to 16, marking the most notable year-over-year shift. There were no fatalities reported in either period.
82
▲ 34.4%was 61
Total Crash Events
0
Persons Killed
16
▲ 128.6%was 7
Persons Injured
1
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for January indicates an upward trend year-over-year in Fitchburg. Total crashes increased by 21, from 61 in January 2022 to 82 in January 2023, representing a 34.4% rise. Concurrently, total injuries saw a substantial increase of 9, from 7 to 16, which is a 128.6% change.
1
Hit-and-Run Crashes — January 2023
▼ 0.0% vs prior (1)
The number of hit-and-run crashes remained constant at 1 in both January 2022 and January 2023. However, due to an overall increase in total crashes, the hit-and-run crash rate decreased from 1.6% in the prior period to 1.2% in the current period.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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 Monday (14 crashes) in January 2022 to Friday (18 crashes) in January 2023. Similarly, the peak crash hour moved from 8 AM (8 crashes) in the prior period to 2 PM (8 crashes) in the current period. Crashes on Tuesdays, Thursdays, and Fridays saw notable increases, with Friday crashes rising by 10 (from 8 to 18) and Tuesday crashes by 8 (from 8 to 16).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero in both January 2022 and January 2023. While serious injuries (severity A) decreased from 1 to 0, minor injuries (severity B) increased by 5 crashes (from 2 to 7), and possible injuries (severity C) increased by 1 crash (from 4 to 5). The proportion of crashes resulting in no injury also increased from 78.7% to 82.9% of all crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Inattention' saw the largest increase, rising by 10 crashes (from 2 to 12), a 500% change. 'Failed to yield right of way' increased by 6 crashes (from 3 to 9), a 200% change, and 'Followed too closely' increased by 3 crashes (from 6 to 9), a 50% change. Conversely, 'Driving too fast for conditions' decreased by 1 crash (from 4 to 3), a 25% reduction.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring during snowy weather conditions saw a significant increase of 12 (from 2 to 14), a 600% change. Crashes on snowy road surfaces also increased substantially by 12 (from 6 to 18), a 200% change, and on slushy surfaces by 3 (from 1 to 4), a 300% change. Meanwhile, crashes on wet road surfaces decreased by 3 (from 16 to 13), an 18.8% reduction.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 44, from 100 in January 2022 to 144 in January 2023. Honda vehicles involved in crashes increased by 13 (from 9 to 22), a 144.4% change, making it the top make in the current period, while Toyota vehicles decreased by 5 (from 24 to 19). The 45-54 age group experienced a substantial increase in persons involved in crashes, rising by 24 (from 5 to 29), a 480% change.
Top Vehicle Makes (144 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Vehicle unit records
11 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (164 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 20 mph speed zones increased by 9 (from 1 to 10), a 900% change, and crashes in 30 mph zones increased by 11 (from 11 to 22), a 100% change. Conversely, crashes in 15 mph zones decreased by 3 (from 3 to 0), a 100% reduction, and in 55 mph zones by 3 (from 4 to 1), a 75% reduction. No fatalities were recorded across any speed limit zone in either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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: 2023-01-01 through 2023-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-01-31 (31 days)
- Geographic scope: FITCHBURG, MA
- Total crash records analyzed: 82
- Total persons involved: 177
- Total vehicles involved: 144
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: January 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fitchburg/january-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: 2023-01-01 – 2023-01-31
Generated: June 21, 2026 · All rights reserved