Monthly Traffic Safety Analysis

2 CRASHES IN
CHESHIRE, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

Total crashes in CHESHIRE decreased by 75%, from 8 crashes in September 2024 to 2 crashes in September 2025. This significant reduction in overall incidents is the most notable year-over-year shift. Additionally, total injuries decreased by 100%, from 3 injuries in the prior period to 0 injuries in the current period.

2

-75.0%was 8

Total Crash Events

0

Persons Killed

0

-100.0%was 3

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. 2 crashes with unreported severity are 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

The overall trend indicates a substantial decrease in crash activity in CHESHIRE. Total crashes fell by 75%, from 8 crashes in September 2024 to 2 crashes in September 2025. Concurrently, total injuries decreased by 100%, with 0 injuries reported in September 2025 compared to 3 injuries in September 2024.

When Crashes Happen

The temporal distribution of crashes shifted year-over-year. In September 2024, the peak day for crashes was Saturday and Wednesday with 2 crashes each, while in September 2025, crashes were evenly split between Sunday and Wednesday, with 1 crash each. The peak crash hour in September 2024 was 12 p.m. with 2 crashes, whereas in September 2025, crashes occurred at 12 p.m. and 10 p.m., with 1 crash at each hour.

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

Top Contributing Factors

The dominant contributing factors observed in crashes changed significantly between the two periods. In September 2024, "Inattention" was the most frequent factor, linked to 3 crashes, while other factors like "Distracted" and "Followed too closely" each contributed to 1 crash. In September 2025, "Failed to yield right of way" and "No improper driving" were each associated with 1 crash. No common contributing factors were present in both periods to allow for direct count-based delta comparison.

Officer-Reported Primary Contributing Cause

Failed to yield right of way1 (50%)
No improper driving1 (50%)

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

The distribution of crash conditions changed between the periods. The proportion of crashes occurring in clear weather conditions decreased from 87.5% (7 out of 8 crashes) in September 2024 to 50% (1 out of 2 crashes) in September 2025, with crashes in rainy conditions appearing in the current period. Similarly, crashes in daylight conditions decreased from 87.5% (7 out of 8 crashes) in the prior period to 50% (1 out of 2 crashes) in the current period, while crashes in dark conditions maintained 1 incident in both periods. Road surface condition data was not available for comparison in the prior period.

Weather

Clear1 (50.0%)
-80.0%prior 5
Rain1 (50.0%)

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

Lighting

Dark - roadway not lighted1 (50.0%)
Daylight1 (50.0%)
-85.7%prior 7

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

Road Surface

Dry1 (50.0%)
Wet1 (50.0%)

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 (3 vehicles)

1
JEEP1 (33.3%)
2
MAZDA1 (33.3%)
3
SUBARU1 (33.3%)

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

Sex Distribution (4 persons with recorded sex)

Female2 (50.0%)
-60.0%prior 5
Male2 (50.0%)
-75.0%prior 8

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

The distribution of crashes across speed zones changed year-over-year. Crashes in 30 mph zones remained consistent with 1 crash in both September 2024 and September 2025. However, crashes in 35 mph zones decreased from 3 crashes in the prior period to 1 crash in the current period. Speed zones of 40 mph and 50 mph, which accounted for 1 and 2 crashes respectively in September 2024, had no reported crashes in September 2025. No fatalities were recorded in any speed zone during either period.

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: CHESHIRE, MA
  • Total crash records analyzed: 2
  • Total persons involved: 4
  • Total vehicles involved: 3

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). "CHESHIRE, 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/cheshire/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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Cheshire, MA Crash Report — September 2025 | ThatCarHitMe.com