ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FITCHBURG, MA · 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/2025-annual-report
Yearly Traffic Safety Analysis
1,461 CRASHES IN
FITCHBURG, MA
2025
In Fitchburg, total vehicle crashes increased by 5.6% from 1,384 in the prior year to 1,461 in the current year. This increase was accompanied by a rise in both injuries, from 255 to 304, and a notable shift in crash severity, with the number of fatalities rising from zero to three. The most significant change year-over-year was the emergence of these fatal crashes where none had occurred in the previous period.
1,461
▲ 5.6%was 1,384
Total Crash Events
3
Persons Killed
304
▲ 19.2%was 255
Persons Injured
177
▲ 12.0%was 158
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 101 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for Fitchburg indicates a rising trend in both the frequency and severity of incidents year-over-year. Total crashes rose from 1,384 to 1,461, an increase of 5.6%. Concurrently, the number of people injured grew by 19.2% from 255 to 304, and the year saw three fatalities, compared to zero in the prior year.
177
Hit-and-Run Crashes — 2025
▲ 12.0% vs prior (158)
Hit-and-run incidents trended upward year-over-year. The total count of hit-and-run crashes increased from 158 in the prior year to 177 in the current year. The hit-and-run rate, as a percentage of all crashes, also saw a slight increase, rising from 11.4% to 12.1%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
10
Pedestrians Injured
9
Cyclists Injured
281
Motorists Injured
4
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed minor shifts between the two periods. The peak day for crashes moved from Friday (229 incidents) in the prior year to Tuesday (239 incidents) in the current year. The peak hour also shifted slightly earlier, from the 3 PM hour (129 crashes) to the 2 PM hour (131 crashes), with weekday afternoons remaining the most frequent time for collisions in both years.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity worsened in the current year compared to the prior year. Three fatal crashes occurred, representing 0.2% of all incidents, whereas there were no fatal crashes in the previous period. The count of serious injury crashes also more than doubled, increasing from 8 to 21, raising their share of total crashes from 0.6% to 1.4%. The proportion of crashes with no injuries remained largely stable, at 77.1% in the current year versus 76.5% in the prior year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors remained consistent across both years: 'No improper driving', 'Inattention', and 'Failed to yield right of way'. The count of crashes attributed to 'Inattention' decreased slightly from 275 to 266, while those attributed to 'Failed to yield right of way' also fell from 128 to 112. Conversely, crashes where 'No improper driving' was cited increased from 303 to 424, and incidents involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased from 43 to 51.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both periods occurred under similar conditions: during daylight, on dry roads, and in clear weather. Crashes on dry roads increased from 1,056 to 1,147, in line with the overall increase in incidents. Incidents during rainy conditions decreased from 91 to 69, and crashes on icy surfaces dropped from 63 to 43. Overall, there was no significant shift in the proportion of crashes occurring in adverse conditions versus clear conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained the same across both years, with each showing an increase in crash counts. Toyota involvement rose from 403 to 425 vehicles, Honda from 294 to 345, and Ford from 243 to 290. Analysis of persons involved shows increases across several age groups, most notably for those aged 16-20 (from 308 to 362), 35-44 (from 433 to 490), and 55-64 (from 268 to 326).
Top Vehicle Makes (2,722 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
481 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,869 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes remained concentrated in lower speed zones, with increases seen in 25 mph zones (from 575 to 610 crashes) and 30 mph zones (from 313 to 346 crashes). A significant change was the appearance of fatal crashes in the current year, which were absent in the prior year. Two of the three fatal crashes occurred in 35 mph zones, and one occurred in a 45 mph zone.
Fatal crashes by zone: 35 mph: 2 of 142 (1.408%) · 45 mph: 1 of 24 (4.167%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: FITCHBURG, MA
- Total crash records analyzed: 1,461
- Total persons involved: 3,368
- Total vehicles involved: 2,722
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fitchburg/2025-annual-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved