Monthly Traffic Safety Analysis

136 CRASHES IN
FITCHBURG, MA
NOVEMBER 2024

All metrics benchmarked againstNovember 2023

Total crashes in November 2024 were 136, an increase from 116 crashes reported in November 2023. This represents a 17.24% rise in overall crashes year-over-year. The most notable shift was a 44.4% decrease in hit-and-run crashes, falling from 18 to 10.

136

17.2%was 116

Total Crash Events

0

Persons Killed

15

-34.8%was 23

Persons Injured

10

-44.4%was 18

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. 9 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in Fitchburg, MA, showed an upward trend year-over-year. Total crashes increased from 116 in November 2023 to 136 in November 2024, marking a 17.24% increase.

10

Hit-and-Run Crashes — November 2024

-44.4% vs prior (18)

Hit-and-run crashes decreased from 18 in November 2023 to 10 in November 2024, representing a 44.4% reduction. Correspondingly, the hit-and-run crash rate declined from 15.5% to 7.4% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

15

Motorists Injured

Prior: 20-25.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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 Thursday (23 crashes) in November 2023 to Saturday (24 crashes) in November 2024. The peak hour also changed, moving from 5 PM (10 crashes) in the prior period to 3 PM (15 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero for both November 2023 and November 2024. Serious injuries decreased from 3 in the prior period to 0 in the current period. Minor injuries increased from 8 to 10, while possible injuries decreased from 5 to 2.

Outcome by Severity (Crash Events)

Minor Injury10minor injury crashes7.4%
25.0%prior 8
Possible Injury2possible injury crashes1.5%
-60.0%prior 5
No Injury115no injury crashes84.6%
23.7%prior 93

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record

Top Contributing Factors

Inattention increased significantly from 17 crashes in the prior period to 29 crashes in the current period, a 70.6% increase, making it the leading contributing factor. No improper driving also increased from 21 to 24 crashes, a 14.3% rise. Conversely, Failed to yield right of way decreased from 14 to 13 crashes, a 7.1% reduction.

Officer-Reported Primary Contributing Cause

Inattention29 (21.3%)70.6%prior 17
No improper driving24 (17.6%)14.3%prior 21
Failed to yield right of way13 (9.6%)-7.1%prior 14
Failure to keep in proper lane or running off road10 (7.4%)
Followed too closely8 (5.9%)14.3%prior 7
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner7 (5.1%)
Other improper action5 (3.7%)-16.7%prior 6
Disregarded traffic signs, signals, road markings4 (2.9%)
Glare4 (2.9%)
Made an improper turn3 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather increased from 99 to 113, and those in rainy conditions increased from 3 to 10. Crashes during daylight hours increased from 60 to 85, while crashes in dark conditions with lighted roadways decreased from 40 to 32. Wet road surface crashes rose from 9 in the prior period to 19 in the current period.

Weather

Clear113 (83.7%)
14.1%prior 99
Rain10 (7.4%)
Cloudy7 (5.2%)
16.7%prior 6
Clear/Clear3 (2.2%)
Cloudy/Rain1 (0.7%)
Rain/Cloudy1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash

Lighting

Daylight85 (63.4%)
41.7%prior 60
Dark - lighted roadway32 (23.9%)
-20.0%prior 40
Dark - roadway not lighted9 (6.7%)
Dark - unknown roadway lighting4 (3.0%)
Dawn2 (1.5%)
Dusk2 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field

Road Surface

Dry115 (85.2%)
10.6%prior 104
Wet19 (14.1%)
111.1%prior 9
Ice1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes increased from 258 to 313 year-over-year. The 65+ age group saw an increase in involved persons from 33 to 45, and the 16-20 age group increased from 20 to 34. Among vehicle makes, Toyota remained the most frequently involved, increasing from 33 to 38, followed by Honda, which increased from 31 to 33.

Top Vehicle Makes (257 vehicles)

1
TOYOTA38 (14.8%)
15.2%prior 33
2
HONDA33 (12.8%)
6.5%prior 31
3
FORD26 (10.1%)
18.2%prior 22
4
CHEVROLET20 (7.8%)
-13.0%prior 23
5
NISSAN19 (7.4%)
35.7%prior 14
6
SUBARU17 (6.6%)
-15.0%prior 20
7
JEEP12 (4.7%)
20.0%prior 10
8
GMC8 (3.1%)
9
HYUNDAI7 (2.7%)
-30.0%prior 10
10
MAZDA6 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records

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

Sex Distribution (283 persons with recorded sex)

Male158 (55.8%)
25.4%prior 126
Female125 (44.2%)
25.0%prior 100

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 25 mph speed zones increased from 46 in November 2023 to 71 in November 2024. Conversely, crashes in 30 mph zones decreased from 32 to 28, and those in 35 mph zones decreased from 14 to 10. No fatalities were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-11-01 through 2024-11-30 (30 days)
  • Geographic scope: FITCHBURG, MA
  • Total crash records analyzed: 136
  • Total persons involved: 313
  • Total vehicles involved: 257

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: November 2024." Published June 21, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fitchburg/november-2024-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

Fitchburg, MA Crash Report — November 2024 | ThatCarHitMe.com