Monthly Traffic Safety Analysis

114 CRASHES IN
FITCHBURG, MA
MARCH 2025

All metrics benchmarked againstMarch 2024

Total crashes in March 2025 were 114, an increase of 18.75% compared to 96 crashes in March 2024. The most notable year-over-year shift was in DUI-related crashes, which increased from 0 in March 2024 to 4 in March 2025. Total fatalities remained at 0 for both periods.

114

18.8%was 96

Total Crash Events

0

Persons Killed

16

-40.7%was 27

Persons Injured

18

80.0%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. 13 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes increased year-over-year, rising from 96 in March 2024 to 114 in March 2025. Conversely, total injuries decreased from 27 in March 2024 to 16 in March 2025. Fatalities remained stable at 0 for both periods.

18

Hit-and-Run Crashes — March 2025

80.0% vs prior (10)

Hit-and-run crashes increased from 10 in March 2024 to 18 in March 2025. The hit-and-run rate also increased, rising from 10.4% in March 2024 to 15.8% in March 2025, indicating an upward trend in such incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

16

Motorists Injured

Prior: 25-36.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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 Saturday with 20 crashes in March 2024 to Monday with 29 crashes in March 2025. The peak hour for crashes also shifted, with 11 crashes occurring at 2 PM in March 2024 and 11 crashes occurring at 11 AM in March 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either March 2024 or March 2025. The proportion of minor injury crashes decreased from 17.7% (17 crashes) in March 2024 to 8.8% (10 crashes) in March 2025. Possible injury crashes also decreased in count from 5 to 3, with their share dropping from 5.2% to 2.6%.

Outcome by Severity (Crash Events)

Minor Injury10minor injury crashes8.8%
-41.2%prior 17
Possible Injury3possible injury crashes2.6%
-40.0%prior 5
No Injury88no injury crashes77.2%
33.3%prior 66

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'No improper driving', increased by 2 crashes from 21 in March 2024 to 23 in March 2025. 'Inattention' crashes decreased by 8, from 24 to 16. 'Followed too closely' crashes increased by 6, from 4 to 10. 'Failed to yield right of way' crashes increased by 3, from 6 to 9. 'Driving too fast for conditions', which accounted for 5 crashes in March 2024, was not among the top factors in March 2025.

Officer-Reported Primary Contributing Cause

No improper driving23 (20.2%)9.5%prior 21
Inattention16 (14%)-33.3%prior 24
Followed too closely10 (8.8%)
Failed to yield right of way9 (7.9%)50.0%prior 6
Failure to keep in proper lane or running off road9 (7.9%)-10.0%prior 10
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner7 (6.1%)
Other improper action7 (6.1%)
Disregarded traffic signs, signals, road markings4 (3.5%)
Made an improper turn2 (1.8%)
Over-correcting/over-steering2 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 65 in March 2024 to 87 in March 2025. Crashes during rainy conditions decreased from 14 to 7 year-over-year. Crashes on dry road surfaces increased from 67 to 95, while crashes on wet surfaces decreased from 20 to 17. Crashes during daylight remained similar, with 73 in March 2024 and 75 in March 2025, but crashes in dark-lighted conditions increased from 15 to 22.

Weather

Clear87 (76.3%)
33.8%prior 65
Cloudy12 (10.5%)
Rain7 (6.1%)
-50.0%prior 14
Cloudy/Rain4 (3.5%)
Clear/Clear2 (1.8%)
Clear/Unknown1 (0.9%)
Rain/Fog, smog, smoke1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash

Lighting

Daylight75 (66.4%)
2.7%prior 73
Dark - lighted roadway22 (19.5%)
46.7%prior 15
Dark - roadway not lighted10 (8.8%)
66.7%prior 6
Dusk4 (3.5%)
Dawn1 (0.9%)
Dark - unknown roadway lighting1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field

Road Surface

Dry95 (84.1%)
41.8%prior 67
Wet17 (15.0%)
-15.0%prior 20
Ice1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 172 in March 2024 to 214 in March 2025. Toyota remained the top make involved, increasing from 22 to 33 vehicles. Honda vehicles increased from 21 to 31, and Ford vehicles increased from 17 to 22. The 26-34 age group continued to have the highest number of persons involved, increasing from 26 to 49 year-over-year.

Top Vehicle Makes (214 vehicles)

1
TOYOTA33 (15.4%)
50.0%prior 22
2
HONDA31 (14.5%)
47.6%prior 21
3
FORD22 (10.3%)
29.4%prior 17
4
CHEVROLET16 (7.5%)
23.1%prior 13
5
NISSAN12 (5.6%)
-14.3%prior 14
6
HYUNDAI11 (5.1%)
37.5%prior 8
7
JEEP10 (4.7%)
-23.1%prior 13
8
SUBARU8 (3.7%)
-20.0%prior 10
9
DODGE5 (2.3%)
-16.7%prior 6
10
MERCEDES-BENZ4 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records

44 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (211 persons with recorded sex)

Male118 (55.9%)
28.3%prior 92
Female92 (43.6%)
31.4%prior 70
X / Unspecified1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones increased from 37 in March 2024 to 50 in March 2025. Crashes in 30 mph zones increased from 22 to 25. There were no fatal crashes reported across any speed zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-03-01 through 2025-03-31 (31 days)
  • Geographic scope: FITCHBURG, MA
  • Total crash records analyzed: 114
  • Total persons involved: 256
  • Total vehicles involved: 214

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: March 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fitchburg/march-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

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Fitchburg, MA Crash Report — March 2025 | ThatCarHitMe.com