Yearly Traffic Safety Analysis

48 CRASHES IN
WHATELY, MA
2025

All metrics benchmarked against2024

In 2025, Whately recorded 48 total traffic crashes, a 34.3% decrease from the 73 crashes reported in 2024. Despite the overall drop in collisions, the most significant year-over-year change was the occurrence of one fatal crash in 2025, whereas no fatalities were recorded in the prior year.

48

-34.2%was 73

Total Crash Events

1

Persons Killed

22

-4.3%was 23

Persons Injured

0

-100.0%was 4

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Whately showed a notable downward trend, decreasing by 34.3% from 73 incidents in 2024 to 48 in 2025. While total collisions fell, the number of injuries remained nearly unchanged at 22, compared to 23 in the previous year. The period was marked by the introduction of one fatality in 2025, an increase from zero in 2024.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

22

Motorists Injured

Prior: 23-4.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Friday remained the most frequent day for crashes in both periods, though the count dropped from 18 in 2024 to 10 in 2025. A significant shift occurred in the peak crash hour, moving from the 9 p.m. hour (7 crashes) in 2024 to the 6 a.m. hour (5 crashes) in 2025, indicating a change in daily collision patterns.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased year-over-year, with one fatal crash recorded in 2025, accounting for 2.1% of all incidents, compared to zero fatal crashes in 2024. The proportion of crashes resulting in minor injuries rose from 12.3% in 2024 to 37.5% in 2025. Consequently, the share of non-injury crashes fell from 78.1% of the total in 2024 to 60.4% in 2025.

Outcome by Severity (Crash Events)

Fatal1fatal crashes2.1%
Minor Injury18minor injury crashes37.5%
100.0%prior 9
No Injury29no injury crashes60.4%
-49.1%prior 57

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors shifted between the two periods. Crashes attributed to "Failed to yield right of way" increased by 80% in count, from 5 incidents in 2024 to 9 in 2025, making it the second most common factor. In contrast, incidents involving "Inattention" saw a sharp decline, with the count falling by 87.5% from 8 crashes in 2024 to just 1 in 2025.

Officer-Reported Primary Contributing Cause

No improper driving11 (22.9%)-42.1%prior 19
Failed to yield right of way9 (18.8%)80.0%prior 5
Failure to keep in proper lane or running off road4 (8.3%)
Other improper action3 (6.3%)
Followed too closely3 (6.3%)
Over-correcting/over-steering2 (4.2%)
Exceeded authorized speed limit2 (4.2%)-60.0%prior 5
Inattention1 (2.1%)-87.5%prior 8
Driving too fast for conditions1 (2.1%)-80.0%prior 5
Fatigued/asleep1 (2.1%)-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both years occurred in daylight on dry roads, with conditions remaining largely consistent. In 2025, 62.5% of crashes happened during daylight, up from 57.5% in 2024. The proportion of incidents on wet roads was stable at about 21% in both years, while the share of crashes in rain or snow conditions increased from 13.7% in 2024 to 20.8% in 2025.

Weather

Clear23 (47.9%)
-46.5%prior 43
Clear/Clear8 (16.7%)
33.3%prior 6
Rain/Cloudy3 (6.3%)
Cloudy3 (6.3%)
Snow3 (6.3%)
Fog, smog, smoke2 (4.2%)
Cloudy/Cloudy1 (2.1%)
Rain/Rain1 (2.1%)
Rain1 (2.1%)
-85.7%prior 7
Snow/Cloudy1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight30 (62.5%)
-28.6%prior 42
Dark - roadway not lighted12 (25.0%)
-45.5%prior 22
Dark - lighted roadway4 (8.3%)
Dusk2 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry34 (70.8%)
-37.0%prior 54
Wet10 (20.8%)
-33.3%prior 15
Snow3 (6.3%)
Sand, mud, dirt, oil, gravel1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes saw a minor shuffle, with Honda (13 vehicles) becoming the most frequent make in 2025, surpassing Toyota (8 vehicles), which had led with 15 vehicles in 2024. Demographically, the representation of persons aged 65 and older among those involved in crashes increased, rising from a 14.8% share in 2024 to a 17.6% share in 2025.

Top Vehicle Makes (72 vehicles)

1
HONDA13 (18.1%)
0.0%prior 13
2
TOYOTA8 (11.1%)
-46.7%prior 15
3
FORD7 (9.7%)
-36.4%prior 11
4
CHEVROLET5 (6.9%)
-37.5%prior 8
5
HYUNDAI5 (6.9%)
6
JEEP5 (6.9%)
7
SUBARU5 (6.9%)
-61.5%prior 13
8
KIA3 (4.2%)
9
FREIGHTLINER2 (2.8%)
10
GMC2 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

Sex Distribution (85 persons with recorded sex)

Male49 (57.6%)
-26.9%prior 67
Female36 (42.4%)
-28.0%prior 50

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes became more concentrated in the highest speed zones year-over-year. In 2025, 45.8% of crashes (22 incidents) occurred in 65 mph zones, an increase from a 38.4% share (28 incidents) in 2024. The single fatal crash in 2025 also took place in a 65 mph zone. There was a corresponding drop in collisions in lower speed zones, with crashes in 35 mph zones falling from 17 to 8.

Fatal crashes by zone: 65 mph: 1 of 22 (4.545%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: WHATELY, MA
  • Total crash records analyzed: 48
  • Total persons involved: 85
  • Total vehicles involved: 72

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). "WHATELY, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/whately/2025-annual-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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Whately, MA Crash Report — 2025 | ThatCarHitMe.com