Monthly Traffic Safety Analysis

11 CRASHES IN
PAXTON, MA
JULY 2025

All metrics benchmarked againstJuly 2024

In July 2025, PAXTON experienced 11 crashes, a 57.1% increase compared to the 7 crashes reported in July 2024. Despite the rise in total crashes, the number of injuries decreased from 6 in the prior period to 4 in the current period, representing a 33.3% reduction.

11

57.1%was 7

Total Crash Events

0

Persons Killed

4

-33.3%was 6

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 · 2025-07-01 to 2025-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in PAXTON increased by 57.1% year-over-year, rising from 7 crashes in July 2024 to 11 crashes in July 2025. This indicates a notable upward trend in crash frequency for the month.

1

Hit-and-Run Crashes — July 2025

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 incident in both July 2024 and July 2025. However, the hit-and-run crash rate decreased from 14.3% of all crashes in the prior period to 9.1% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 6-33.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · 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 significantly year-over-year. In July 2024, the peak day for crashes was Monday with 2 incidents, while in July 2025, Thursday became the peak day with 3 crashes. Similarly, the peak crash hour shifted from 8 AM in July 2024 to 6 PM in July 2025, with both hours recording 2 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero for both July 2024 and July 2025. The proportion of crashes resulting in any injury (Minor or Possible) decreased substantially, moving from 3 crashes (42.9% of total crashes) in the prior period to 1 crash (9.1% of total crashes) in the current period.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes9.1%
0.0%prior 1
No Injury9no injury crashes81.8%
125.0%prior 4

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Most severe injury per crash record

Top Contributing Factors

The most significant change in contributing factors was a three-crash increase in incidents attributed to 'No improper driving,' rising from 1 in July 2024 to 4 in July 2025. Crashes involving 'Failed to yield right of way' also increased from 1 to 2. Factors such as 'Driving too fast for conditions' and 'Inattention' remained constant at 1 crash each across both periods.

Officer-Reported Primary Contributing Cause

No improper driving4 (36.4%)
Failed to yield right of way2 (18.2%)
Driving too fast for conditions1 (9.1%)
Over-correcting/over-steering1 (9.1%)
Inattention1 (9.1%)
Fatigued/asleep1 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In terms of lighting conditions, crashes occurring during daylight hours increased from 6 in July 2024 to 8 in July 2025. Incidents in 'Dark - lighted roadway' conditions also saw an increase, from 1 crash in the prior period to 2 crashes in the current period. A crash occurring at 'Dusk' was reported in July 2025, where none were reported in July 2024.

Weather

Clear9 (81.8%)
Cloudy/Rain1 (9.1%)
Rain/Fog, smog, smoke1 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Weather condition at time of crash

Lighting

Daylight8 (72.7%)
33.3%prior 6
Dark - lighted roadway2 (18.2%)
Dusk1 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Lighting condition field

Road Surface

Dry9 (81.8%)
Wet2 (18.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (17 vehicles)

1
VOLKSWAGEN3 (17.6%)
2
TOYOTA3 (17.6%)
3
BUIC2 (11.8%)
4
FORD2 (11.8%)
5
JEEP1 (5.9%)
6
KIA1 (5.9%)
7
RAM1 (5.9%)
8
SUBARU1 (5.9%)
9
GMC1 (5.9%)
10
CHEVROLET1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Vehicle unit records

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

Sex Distribution (23 persons with recorded sex)

Male15 (65.2%)
87.5%prior 8
Female8 (34.8%)
14.3%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased from 3 incidents in July 2024 to 5 incidents in July 2025. Similarly, crashes in 40 mph zones rose from 4 to 5 over the same period. A new crash occurred in a 5 mph zone in July 2025, where no crashes were recorded in that zone in July 2024, and no fatal crashes were reported in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · 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: 2025-07-01 through 2025-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-07-01 through 2025-07-31 (31 days)
  • Geographic scope: PAXTON, MA
  • Total crash records analyzed: 11
  • Total persons involved: 25
  • 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). "PAXTON, MA Crash Intelligence Report: July 2025." Published June 21, 2026. Reporting period: 2025-07-01 to 2025-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/paxton/july-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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Paxton, MA Crash Report — July 2025 | ThatCarHitMe.com