Monthly Traffic Safety Analysis

21 CRASHES IN
PALMER, MA
JUNE 2025

All metrics benchmarked againstJune 2024

In June 2025, Palmer, MA experienced 21 crashes, a decrease from the 31 crashes reported in June 2024. This represents a 32.3% reduction in total crashes year-over-year. The most significant shift observed is the substantial decline in overall crash incidents.

21

-32.3%was 31

Total Crash Events

0

Persons Killed

6

-33.3%was 9

Persons Injured

1

-66.7%was 3

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in Palmer, MA decreased significantly by 32.3% from 31 crashes in June 2024 to 21 crashes in June 2025. Fatalities remained at zero in both periods, while total injuries saw a 33.3% reduction, falling from 9 to 6.

1

Hit-and-Run Crashes — June 2025

-66.7% vs prior (3)

Hit-and-run crashes decreased from 3 incidents in June 2024 to 1 incident in June 2025. This reduction also led to a decrease in the hit-and-run rate, which fell from 9.7% of total crashes to 4.8% year-over-year, indicating a positive trend in this area.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 8-25.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Monday in both June 2024 and June 2025, though the number of crashes on Monday decreased from 8 to 6. The peak crash hour shifted from 3p with 6 crashes in June 2024 to 2p with 3 crashes in June 2025. This indicates a shift in the precise timing of peak activity, but Monday remains the day with the highest crash frequency.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate remained at 0% in both June 2024 and June 2025. Crashes resulting in serious injuries decreased from 2 in June 2024 to 1 in June 2025, while minor injury crashes also fell from 4 to 1. Conversely, crashes with possible injuries increased from 1 in June 2024 to 3 in June 2025, shifting the distribution of injury severities.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.8%
-50.0%prior 2
Minor Injury1minor injury crashes4.8%
-75.0%prior 4
Possible Injury3possible injury crashes14.3%
200.0%prior 1
No Injury16no injury crashes76.2%
-33.3%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving', decreased from 11 crashes in June 2024 to 8 crashes in June 2025. 'Inattention' crashes saw a significant reduction, dropping from 8 to 2 incidents year-over-year. 'Failed to yield right of way' crashes also decreased from 4 to 1, while 'Failure to keep in proper lane or running off road' emerged as a factor in 3 crashes in June 2025, not being a top factor in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving8 (38.1%)-27.3%prior 11
Failure to keep in proper lane or running off road3 (14.3%)
Inattention2 (9.5%)-75.0%prior 8
Disregarded traffic signs, signals, road markings2 (9.5%)
Followed too closely2 (9.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (9.5%)
Failed to yield right of way1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 24 in June 2024 to 10 in June 2025. Similarly, crashes on 'Dry' road surfaces decreased from 27 to 17, and 'Daylight' crashes fell from 23 to 16. The number of crashes in 'Wet' road conditions also saw a slight decrease from 4 to 3, indicating a general reduction across various conditions.

Weather

Clear10 (47.6%)
-58.3%prior 24
Clear/Clear7 (33.3%)
Cloudy/Rain3 (14.3%)
Rain1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Lighting

Daylight16 (76.2%)
-30.4%prior 23
Dawn3 (14.3%)
Dark - lighted roadway1 (4.8%)
Dark - roadway not lighted1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field

Road Surface

Dry17 (81.0%)
-37.0%prior 27
Wet3 (14.3%)
Water (standing, moving)1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (35 vehicles)

1
TOYOTA8 (22.9%)
-20.0%prior 10
2
HONDA5 (14.3%)
3
CHEVROLET3 (8.6%)
4
VOLVO2 (5.7%)
5
FORD2 (5.7%)
-71.4%prior 7
6
JEEP2 (5.7%)
7
DODGE1 (2.9%)
8
HYUNDAI1 (2.9%)
9
AUDI1 (2.9%)
10
LEXUS1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

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

Sex Distribution (37 persons with recorded sex)

Male23 (62.2%)
-41.0%prior 39
Female14 (37.8%)
-56.3%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone significantly decreased from 10 incidents in June 2024 to 5 in June 2025. Conversely, crashes in the 25 mph zone increased from 2 to 4 year-over-year. Crashes in the 65 mph zone also decreased from 6 to 4, indicating a shift in crash distribution across different speed limit categories.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: PALMER, MA
  • Total crash records analyzed: 21
  • Total persons involved: 41
  • Total vehicles involved: 35

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). "PALMER, MA Crash Intelligence Report: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/palmer/june-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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Palmer, MA Crash Report — June 2025 | ThatCarHitMe.com