Monthly Traffic Safety Analysis

15 CRASHES IN
PEPPERELL, MA
FEBRUARY 2026

All metrics benchmarked againstFebruary 2025

In February 2026, PEPPERELL, MA experienced 15 crashes, a decrease of 6.25% from the 16 crashes recorded in February 2025. The most notable shift was the absence of fatalities and injuries in the current period, compared to 1 fatality and 1 injury in the prior period.

15

-6.3%was 16

Total Crash Events

0

-100.0%was 1

Persons Killed

0

-100.0%was 1

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in PEPPERELL, MA saw a slight decrease year-over-year, with total crashes falling by 1, from 16 to 15, representing a 6.25% reduction. Critically, fatalities decreased from 1 to 0, and total injuries also decreased from 1 to 0.

1

Hit-and-Run Crashes — February 2026

6.7% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

When Crashes Happen

The temporal distribution of crashes shifted year-over-year. The peak day for crashes moved from Saturday in February 2025 (4 crashes) to Monday in February 2026 (4 crashes), while Sunday crashes decreased from 2 to 0. The peak crash hour also shifted from 10 p.m. in February 2025 (3 crashes) to 5 p.m. in February 2026 (2 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash time field aggregated by hour (0-23)

Top Contributing Factors

Among contributing factors, 'No improper driving' remained consistent with 5 crashes in both periods. Crashes attributed to 'Driving too fast for conditions' decreased significantly from 3 crashes in February 2025 to 1 crash in February 2026, a 66.7% decrease in count. 'Failed to yield right of way' accounted for 2 crashes in both periods, showing no change in count. Factors like 'Followed too closely' (2 crashes in prior period) were not present in the current period, while 'Inattention' and 'Distracted' each contributed to 1 crash in the current period but were not listed in the prior period's top factors.

Officer-Reported Primary Contributing Cause

No improper driving5 (33.3%)0.0%prior 5
Failed to yield right of way2 (13.3%)
Driving too fast for conditions1 (6.7%)
Inattention1 (6.7%)
Made an improper turn1 (6.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (6.7%)
Wrong side or wrong way1 (6.7%)
Disregarded traffic signs, signals, road markings1 (6.7%)
Distracted1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There were notable shifts in crash conditions year-over-year. Crashes occurring in 'Clear' weather increased from 6 in February 2025 to 9 in February 2026, while those in 'Snow' conditions (including 'Snow/Sleet' and 'Snow/Blowing sand, snow') decreased from 7 to 2 crashes. Under 'Daylight' conditions, crashes increased from 6 to 10, whereas crashes in 'Dark - lighted roadway' decreased from 7 to 2. Regarding road surface, 'Dry' road crashes increased from 4 to 10, while 'Snow' road crashes decreased from 6 to 2.

Weather

Clear9 (60.0%)
50.0%prior 6
Cloudy4 (26.7%)
Snow1 (6.7%)
-80.0%prior 5
Snow/Blowing sand, snow1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Weather condition at time of crash

Lighting

Daylight10 (66.7%)
66.7%prior 6
Dark - lighted roadway2 (13.3%)
-71.4%prior 7
Dusk2 (13.3%)
Dark - roadway not lighted1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Lighting condition field

Road Surface

Dry10 (66.7%)
Snow2 (13.3%)
-66.7%prior 6
Wet2 (13.3%)
Slush1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (24 vehicles)

1
FORD4 (16.7%)
-20.0%prior 5
2
HONDA4 (16.7%)
3
NISSAN2 (8.3%)
4
HYUNDAI2 (8.3%)
5
JEEP2 (8.3%)
6
TOYOTA2 (8.3%)
7
THMS1 (4.2%)
8
AUDI1 (4.2%)
9
CHEVROLET1 (4.2%)
10
MACK1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Vehicle unit records

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

Sex Distribution (28 persons with recorded sex)

Male20 (71.4%)
25.0%prior 16
Female8 (28.6%)
-20.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones shifted, with crashes in 30 mph zones decreasing from 9 in February 2025 to 5 in February 2026. Conversely, crashes in 40 mph zones increased from 2 to 6, and crashes in 45 mph zones increased from 2 to 3. No fatalities were recorded within the listed speed zones for either February 2025 or February 2026.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · 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: 2026-02-01 through 2026-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2026-02-01 through 2026-02-28 (28 days)
  • Geographic scope: PEPPERELL, MA
  • Total crash records analyzed: 15
  • Total persons involved: 29
  • Total vehicles involved: 24

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). "PEPPERELL, MA Crash Intelligence Report: February 2026." Published June 21, 2026. Reporting period: 2026-02-01 to 2026-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/pepperell/february-2026-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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Pepperell, MA Crash Report — February 2026 | ThatCarHitMe.com