Monthly Traffic Safety Analysis

40 CRASHES IN
WESTFIELD, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, WESTFIELD experienced 40 crashes, a decrease of 16.67% compared to the 48 crashes recorded in November 2024. Total injuries also saw a reduction from 22 to 19 over the same period. Despite the overall decrease in crashes, DUI-related incidents notably rose from 1 crash in the prior period to 3 crashes in the current period.

40

-16.7%was 48

Total Crash Events

0

Persons Killed

19

-13.6%was 22

Persons Injured

0

-100.0%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 · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for WESTFIELD in November 2025 indicates a downward trend, with total crashes decreasing by 8 incidents from 48 in the prior year to 40. This represents a 16.67% reduction year-over-year. Similarly, total injuries decreased by 3, from 22 to 19, suggesting an improvement in safety outcomes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 10.0%

1

Cyclists Injured

Prior: 3-66.7%

17

Motorists Injured

Prior: 170.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted year-over-year, with the peak day for crashes moving from Friday in November 2024 (10 crashes) to Wednesday in November 2025 (12 crashes). The peak hour also changed, with the highest number of crashes occurring at 1p (6 crashes) in the prior period, shifting to 10p (5 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either November 2024 or November 2025. The proportion of crashes resulting in minor injuries (code B) increased from 25% of total crashes in the prior period to 27.5% in the current period. Conversely, crashes with possible injuries (code C) decreased from 12.5% to 10% of total crashes, while crashes with no injuries remained stable at 62.5%.

Outcome by Severity (Crash Events)

Minor Injury11minor injury crashes27.5%
-8.3%prior 12
Possible Injury4possible injury crashes10%
-33.3%prior 6
No Injury25no injury crashes62.5%
-16.7%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'Failed to yield right of way,' decreased from 13 crashes in the prior period to 10 crashes in the current period. Crashes attributed to 'No improper driving' increased from 7 to 9, while 'Inattention' decreased from 6 crashes to 5. 'Followed too closely' also saw a slight increase from 3 to 4 crashes year-over-year.

Officer-Reported Primary Contributing Cause

Failed to yield right of way10 (25%)-23.1%prior 13
No improper driving9 (22.5%)28.6%prior 7
Inattention5 (12.5%)-16.7%prior 6
Followed too closely4 (10%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (5%)
Driving too fast for conditions2 (5%)
Visibility obstructed1 (2.5%)
Disregarded traffic signs, signals, road markings1 (2.5%)
Wrong side or wrong way1 (2.5%)
Distracted1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in daylight conditions decreased from 31 in November 2024 to 15 in November 2025, while crashes in dark conditions significantly increased from 15 to 24. The number of crashes occurring in adverse weather conditions (rain, snow, ice) remained stable at 7 incidents in both periods. However, the proportion of these adverse weather crashes relative to total crashes increased from 14.6% to 17.5%.

Weather

Clear24 (60.0%)
-29.4%prior 34
Cloudy5 (12.5%)
-16.7%prior 6
Clear/Clear4 (10.0%)
Rain3 (7.5%)
-40.0%prior 5
Rain/Rain2 (5.0%)
Rain/Snow1 (2.5%)
Snow/Sleet, hail (freezing rain or drizzle)1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash

Lighting

Dark - lighted roadway19 (47.5%)
35.7%prior 14
Daylight15 (37.5%)
-51.6%prior 31
Dark - roadway not lighted4 (10.0%)
Dark - unknown roadway lighting1 (2.5%)
Dusk1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field

Road Surface

Dry29 (72.5%)
-21.6%prior 37
Wet10 (25.0%)
-9.1%prior 11
Ice1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field

Vehicles & Demographics

The top two vehicle makes involved in crashes, Toyota and Honda, saw decreases in counts, from 18 to 14 and 13 to 9 respectively. Hyundai crashes increased slightly from 6 to 7, while Jeep crashes decreased from 6 to 3 and Ford crashes decreased from 6 to 1. Volkswagen also saw an increase in crash involvement from 1 to 3.

Top Vehicle Makes (72 vehicles)

1
TOYOTA14 (19.4%)
-22.2%prior 18
2
HONDA9 (12.5%)
-30.8%prior 13
3
HYUNDAI7 (9.7%)
16.7%prior 6
4
CHEVROLET4 (5.6%)
5
VOLKSWAGEN3 (4.2%)
6
GMC3 (4.2%)
7
JEEP3 (4.2%)
-50.0%prior 6
8
KIA3 (4.2%)
9
MERCEDES-BENZ3 (4.2%)
10
NISSAN2 (2.8%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records

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

Sex Distribution (94 persons with recorded sex)

Male59 (62.8%)
31.1%prior 45
Female35 (37.2%)
-36.4%prior 55

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones saw a slight increase from 16 to 17 incidents year-over-year. A notable shift occurred in 40 mph zones, where crashes decreased from 13 to 6, while crashes in 65 mph zones increased significantly from 2 to 8. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-11-01 through 2025-11-30 (30 days)
  • Geographic scope: WESTFIELD, MA
  • Total crash records analyzed: 40
  • Total persons involved: 100
  • 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). "WESTFIELD, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/westfield/november-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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Westfield, MA Crash Report — November 2025 | ThatCarHitMe.com