Monthly Traffic Safety Analysis

25 CRASHES IN
PALMER, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

Total crashes in PALMER for September 2025 were 25, a decrease of 10.71% compared to the 28 crashes reported in September 2024. The most significant year-over-year shift was the absence of fatal crashes and fatalities in the current period, down from one fatal crash and one fatality in the prior year. Total injuries also saw a notable reduction, decreasing from 15 to 10.

25

-10.7%was 28

Total Crash Events

0

-100.0%was 1

Persons Killed

10

-33.3%was 15

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for PALMER in September 2025 shows a downward trend compared to September 2024. Total crashes decreased by 10.71%, from 28 to 25. This reduction was accompanied by a 33.33% decrease in total injuries, falling from 15 to 10.

1

Hit-and-Run Crashes — September 2025

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 in both September 2025 and September 2024. The hit-and-run crash rate was 4% in the current period, a slight increase from 3.6% in the prior period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

10

Motorists Injured

Prior: 15-33.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts year-over-year. In September 2025, Friday was the peak day for crashes with 7 incidents, whereas Monday was the peak day in September 2024, also with 7 incidents. The peak hour for crashes remained consistent at 4 p.m. in both periods, with 5 crashes recorded at that time.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes saw a significant positive change year-over-year. September 2025 recorded no fatal crashes and no fatalities, a decrease from one fatal crash and one fatality in September 2024. Total injuries decreased from 15 to 10, while serious injuries remained constant at 1 in both periods.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4%
0.0%prior 1
Possible Injury5possible injury crashes20%
66.7%prior 3
No Injury18no injury crashes72%
20.0%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving', decreased by 4 crashes, from 7 in September 2024 to 3 in September 2025. Similarly, 'Inattention' decreased by 3 crashes, from 6 to 3, and 'Failed to yield right of way' decreased by 2 crashes, from 4 to 2. Conversely, 'Failure to keep in proper lane or running off road' and 'Visibility obstructed' each increased from 0 to 4 crashes year-over-year.

Officer-Reported Primary Contributing Cause

Failure to keep in proper lane or running off road4 (16%)
Visibility obstructed4 (16%)
No improper driving3 (12%)-57.1%prior 7
Inattention3 (12%)-50.0%prior 6
Followed too closely2 (8%)
Disregarded traffic signs, signals, road markings2 (8%)
Failed to yield right of way2 (8%)
Operating defective equipment1 (4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4%)
Other improper action1 (4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained largely similar between the two periods. The majority of crashes in both September 2025 and September 2024 occurred during clear weather (21 vs 23 crashes) and daylight hours (19 vs 20 crashes). Dry road surfaces were also predominant, accounting for 22 crashes in the current period and 25 in the prior period, with wet road surface crashes remaining at 2 in both periods.

Weather

Clear14 (58.3%)
-30.0%prior 20
Clear/Clear7 (29.2%)
Clear/Cloudy1 (4.2%)
Cloudy1 (4.2%)
Rain/Rain1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash

Lighting

Daylight19 (79.2%)
-5.0%prior 20
Dark - roadway not lighted4 (16.7%)
-20.0%prior 5
Dark - lighted roadway1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field

Road Surface

Dry22 (91.7%)
-12.0%prior 25
Wet2 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (44 vehicles)

1
FORD8 (18.2%)
2
TOYOTA7 (15.9%)
3
HONDA4 (9.1%)
4
FREIGHTLINER CO3 (6.8%)
5
CHEVROLET3 (6.8%)
-50.0%prior 6
6
MAZDA2 (4.5%)
7
GMC2 (4.5%)
8
VOLKSWAGEN2 (4.5%)
9
RAM1 (2.3%)
10
SUBARU1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records

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

Sex Distribution (56 persons with recorded sex)

Male33 (58.9%)
-15.4%prior 39
Female23 (41.1%)
15.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph speed zones decreased from 12 in September 2024 to 11 in September 2025, and notably, the single fatal crash from the prior year occurred in a 30 mph zone, with no fatalities in this zone in the current period. Crashes in 65 mph speed zones saw a slight increase from 6 to 7.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-09-01 through 2025-09-30 (30 days)
  • Geographic scope: PALMER, MA
  • Total crash records analyzed: 25
  • Total persons involved: 60
  • Total vehicles involved: 44

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: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/palmer/september-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 — September 2025 | ThatCarHitMe.com