Monthly Traffic Safety Analysis

50 CRASHES IN
WESTFIELD, MA
NOVEMBER 2023

All metrics benchmarked againstNovember 2022

In November 2023, WESTFIELD experienced 50 crashes, a decrease of 22% compared to the 64 crashes reported in November 2022. Concurrently, total injuries fell by 34%, from 38 to 25. This period saw a notable reduction in both overall crash incidents and associated injuries.

50

-21.9%was 64

Total Crash Events

0

Persons Killed

25

-34.2%was 38

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash activity in WESTFIELD showed a significant downward trend year-over-year. Total crashes decreased by 14 incidents, from 64 in November 2022 to 50 in November 2023, representing a 22% reduction.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

24

Motorists Injured

Prior: 37-35.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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 year-over-year; the peak day for crashes moved from Tuesday with 17 incidents in November 2022 to Wednesday with 11 incidents in November 2023. Similarly, the peak hour for crashes changed from 2 p.m. with 9 incidents in the prior period to 1 p.m. with 5 incidents in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Neither November 2023 nor November 2022 recorded any fatal crashes or fatalities. Total injuries decreased by 34%, from 38 to 25. The proportion of crashes resulting in 'No Injury' increased from 57.8% in November 2022 to 64% in November 2023, and serious injuries, which accounted for 2 crashes in the prior period, were absent in the current period.

Outcome by Severity (Crash Events)

Minor Injury11minor injury crashes22%
-21.4%prior 14
Possible Injury7possible injury crashes14%
-30.0%prior 10
No Injury32no injury crashes64%
-13.5%prior 37

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record

Top Contributing Factors

Several top contributing factors saw decreases in crash counts year-over-year; 'Inattention' and 'Failed to yield right of way' each decreased by 5 crashes, representing a 38.5% reduction for both. Conversely, 'Failure to keep in proper lane or running off road' increased by 3 crashes, rising from 2 to 5, a 150% increase. Additionally, 'Exceeded authorized speed limit' appeared as a factor in 2 crashes in November 2023, after not being reported in the prior period's top factors.

Officer-Reported Primary Contributing Cause

Inattention8 (16%)-38.5%prior 13
Failed to yield right of way8 (16%)-38.5%prior 13
No improper driving7 (14%)-46.2%prior 13
Failure to keep in proper lane or running off road5 (10%)
Followed too closely4 (8%)-33.3%prior 6
Other improper action3 (6%)
Exceeded authorized speed limit2 (4%)
Distracted2 (4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (4%)
Driving too fast for conditions2 (4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 45 to 37, while those on 'Dry' road surfaces also saw a reduction from 54 to 45. Crashes in 'Dark - lighted roadway' conditions decreased from 18 to 12. Notably, 'Snow' as a road surface condition was reported in 1 crash in November 2023, whereas it was not present in November 2022.

Weather

Clear37 (77.1%)
-17.8%prior 45
Cloudy7 (14.6%)
-22.2%prior 9
Rain3 (6.3%)
Rain/Snow1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash

Lighting

Daylight32 (64.0%)
-3.0%prior 33
Dark - lighted roadway12 (24.0%)
-33.3%prior 18
Dark - roadway not lighted2 (4.0%)
-71.4%prior 7
Dusk2 (4.0%)
Dark - unknown roadway lighting1 (2.0%)
Dawn1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field

Road Surface

Dry45 (90.0%)
-16.7%prior 54
Wet4 (8.0%)
-55.6%prior 9
Snow1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased by 29.3%, from 123 to 87 year-over-year. Toyota became the most frequently involved make with 15 vehicles in November 2023, surpassing Honda, which saw its involvement decrease from 17 to 10 vehicles. Significant shifts were observed in the age distribution of persons involved, with the 16-20 age group decreasing from 28 to 6 persons, while the 65+ age group increased from 8 to 14 persons.

Top Vehicle Makes (87 vehicles)

1
TOYOTA15 (17.2%)
7.1%prior 14
2
HONDA10 (11.5%)
-41.2%prior 17
3
FORD9 (10.3%)
0.0%prior 9
4
SUBARU7 (8%)
-12.5%prior 8
5
JEEP5 (5.7%)
6
NISSAN5 (5.7%)
-54.5%prior 11
7
CHEVROLET5 (5.7%)
-44.4%prior 9
8
HYUNDAI5 (5.7%)
-16.7%prior 6
9
MAZDA3 (3.4%)
10
GMC2 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records

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

Sex Distribution (99 persons with recorded sex)

Female56 (56.6%)
-26.3%prior 76
Male43 (43.4%)
-44.2%prior 77

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones changed year-over-year, with crashes in the 30 mph zone decreasing by 8 incidents, from 20 to 12. Conversely, crashes in the 25 mph zone increased by 5 incidents, from 2 to 7. Crashes in the 65 mph zone saw a significant reduction from 10 to 3 incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-11-01 through 2023-11-30 (30 days)
  • Geographic scope: WESTFIELD, MA
  • Total crash records analyzed: 50
  • Total persons involved: 104
  • Total vehicles involved: 87

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 2023." Published June 21, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/westfield/november-2023-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 2023 | ThatCarHitMe.com