Monthly Traffic Safety Analysis

10 CRASHES IN
HAMPDEN, MA
MARCH 2026

All metrics benchmarked againstMarch 2025

In March 2026, HAMPDEN experienced 10 total crashes, an 11.11% increase compared to the 9 crashes recorded in March 2025. Total injuries increased by 100%, rising from 1 to 2, while fatalities remained at zero in both periods. A notable shift includes the emergence of 1 DUI-related crash and 1 speeding-related crash in the current period, neither of which were present in the prior year.

10

11.1%was 9

Total Crash Events

0

Persons Killed

2

100.0%was 1

Persons Injured

0

Fatal Crash Events

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in HAMPDEN saw an increase year-over-year, with total crashes rising from 9 in March 2025 to 10 in March 2026, representing an 11.11% increase. Total injuries also doubled, from 1 in the prior period to 2 in the current period. Fatalities remained consistent at zero for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 1100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year. In March 2026, the peak day for crashes was Saturday with 3 incidents, whereas in March 2025, the peak day was Friday with 2 incidents. The peak hour also changed, with 3 PM recording 2 crashes in the current period, compared to 8 PM with 2 crashes in the prior period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution remained largely consistent with no fatalities reported in either period. Total injuries, however, increased from 1 in March 2025 to 2 in March 2026. The number of crashes resulting in a possible injury remained at 1 in both periods, representing 10% of crashes in the current period and 11.1% in the prior period.

Outcome by Severity (Crash Events)

Possible Injury1possible injury crashes10%
0.0%prior 1
No Injury9no injury crashes90%
12.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record

Top Contributing Factors

Contributing factors showed shifts in prevalence year-over-year. 'No improper driving' decreased by 50% in count, from 4 crashes in March 2025 to 2 crashes in March 2026. 'Failure to keep in proper lane or running off road' emerged as a factor in the current period with 3 crashes, while 'Failed to yield right of way,' which accounted for 2 crashes in the prior period, was not present in the current data. 'Inattention' remained consistent with 2 crashes in both periods.

Officer-Reported Primary Contributing Cause

Failure to keep in proper lane or running off road3 (30%)
Inattention2 (20%)
No improper driving2 (20%)
Followed too closely1 (10%)
Other improper action1 (10%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Weather conditions showed some changes, with 'Cloudy' conditions increasing by 1 crash from 1 in March 2025 to 2 in March 2026. Crashes occurring in 'Daylight' conditions increased significantly by 6 incidents, from 2 in the prior period to 8 in the current period. Conversely, crashes in 'Dark - lighted roadway' conditions decreased by 3 incidents, from 5 in the prior period to 2 in the current period. Road surface condition data was not available for comparison in the prior period.

Weather

Clear4 (40.0%)
Cloudy2 (20.0%)
Clear/Unknown1 (10.0%)
Cloudy/Clear1 (10.0%)
Cloudy/Rain1 (10.0%)
Snow/Rain1 (10.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash

Lighting

Daylight8 (80.0%)
Dark - lighted roadway2 (20.0%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field

Road Surface

Dry8 (80.0%)
Snow1 (10.0%)
Wet1 (10.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (17 vehicles)

1
HONDA3 (17.6%)
2
NISSAN3 (17.6%)
3
RAM2 (11.8%)
4
CADI1 (5.9%)
5
FORD1 (5.9%)
6
GMC1 (5.9%)
7
JEEP1 (5.9%)
8
SUBARU1 (5.9%)
9
ACURA1 (5.9%)
10
TOYOTA1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records

Sex Distribution (20 persons with recorded sex)

Male12 (60.0%)
71.4%prior 7
Female8 (40.0%)
33.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crash distribution by speed zone showed a notable shift year-over-year. Crashes in 30 mph zones increased by 4 incidents, from 3 in March 2025 to 7 in March 2026. Conversely, crashes in 40 mph zones decreased by 4 incidents, from 5 in the prior period to 1 in the current period. A crash in a 25 mph zone was observed in the current period (1 crash) but not in the prior period, and fatal rates remained at zero across all speed zones in both periods.

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

Data Coverage

  • Reporting period: 2026-03-01 through 2026-03-31 (31 days)
  • Geographic scope: HAMPDEN, MA
  • Total crash records analyzed: 10
  • Total persons involved: 21
  • Total vehicles involved: 17

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). "HAMPDEN, MA Crash Intelligence Report: March 2026." Published June 21, 2026. Reporting period: 2026-03-01 to 2026-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hampden/march-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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Hampden, MA Crash Report — March 2026 | ThatCarHitMe.com