Yearly Traffic Safety Analysis

583 CRASHES IN
WESTFIELD, MA
2024

All metrics benchmarked against2023

In 2024, Westfield recorded 583 total crashes, a 3.8% decrease from the 606 crashes reported in 2023. While overall crashes declined, the number of fatalities doubled from one to two. One of the most significant year-over-year changes was a 60% reduction in hit-and-run incidents, which fell from 20 in 2023 to 8 in 2024.

583

-3.8%was 606

Total Crash Events

2

100.0%was 1

Persons Killed

265

-0.7%was 267

Persons Injured

8

-60.0%was 20

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 6 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Westfield indicates a slight downward trend in overall incidents year-over-year. Total crashes decreased by 3.8%, from 606 in 2023 to 583 in 2024. The number of injuries remained relatively stable, with 265 in 2024 compared to 267 in the prior year, while fatalities increased from one to two.

8

Hit-and-Run Crashes — 2024

-60.0% vs prior (20)

There was a substantial year-over-year decrease in hit-and-run incidents in Westfield. The total number of hit-and-run crashes fell by 60%, from 20 in 2023 to 8 in 2024. This downward trend is also reflected in the hit-and-run rate, which dropped from 3.3 to 1.4 per 100 crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 10.0%

1

Other Killed

Prior: 0%

8

Pedestrians Injured

Prior: 633.3%

5

Cyclists Injured

Prior: 13-61.5%

251

Motorists Injured

Prior: 2471.6%

1

Other Injured

Prior: 10.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Westfield showed a shift between 2023 and 2024. The peak day for crashes moved from Thursday (100 incidents) in 2023 to Friday (106 incidents) in 2024. Similarly, the peak hour for collisions shifted from the 4 p.m. hour in the prior year (51 crashes) to the 1 p.m. hour in the current year (47 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

In 2024, the severity of crashes increased compared to the previous year. The number of fatal crashes doubled from one to two, and the fatal crash rate rose from 0.17 to 0.34 per 100 crashes. Crashes resulting in serious injuries also saw a significant increase, rising 69% from 13 incidents in 2023 to 22 in 2024, representing 3.8% of all crashes compared to 2.1% in the prior year.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.3%
100.0%prior 1
Serious Injury22serious injury crashes3.8%
69.2%prior 13
Minor Injury131minor injury crashes22.5%
-0.8%prior 132
Possible Injury50possible injury crashes8.6%
-12.3%prior 57
No Injury372no injury crashes63.8%
-6.1%prior 396

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

"Failed to yield right of way" remained the leading contributing factor in both periods, with its incident count slightly decreasing from 115 in 2023 to 111 in 2024. "Inattention" became a more prominent factor, as its count increased by 12.7% from 71 to 80 incidents, moving it from the fourth to the second-ranked cause. Other notable shifts include a 50% rise in the count of crashes attributed to "Driving too fast for conditions" (from 20 to 30 incidents) and a 100% increase in the count of crashes from "Disregarded traffic signs, signals, road markings" (from 14 to 28 incidents).

Officer-Reported Primary Contributing Cause

Failed to yield right of way111 (19%)-3.5%prior 115
Inattention80 (13.7%)12.7%prior 71
No improper driving73 (12.5%)-23.2%prior 95
Followed too closely66 (11.3%)-15.4%prior 78
Driving too fast for conditions30 (5.1%)50.0%prior 20
Failure to keep in proper lane or running off road28 (4.8%)-36.4%prior 44
Disregarded traffic signs, signals, road markings28 (4.8%)100.0%prior 14
Distracted24 (4.1%)4.3%prior 23
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner22 (3.8%)100.0%prior 11
Other improper action15 (2.6%)-34.8%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes by lighting conditions remained consistent year-over-year, with approximately 71% of incidents in both periods occurring in daylight. However, there was a shift in road surface conditions, with crashes on wet roads decreasing from 130 in 2023 to 91 in 2024. Conversely, incidents on snow-covered roads increased from 17 to 29, and crashes on icy roads rose from 2 to 11.

Weather

Clear405 (69.6%)
1.0%prior 401
Cloudy72 (12.4%)
4.3%prior 69
Rain40 (6.9%)
-31.0%prior 58
Snow13 (2.2%)
8.3%prior 12
Rain/Cloudy11 (1.9%)
57.1%prior 7
Clear/Clear8 (1.4%)
Cloudy/Rain7 (1.2%)
-73.1%prior 26
Snow/Sleet, hail (freezing rain or drizzle)4 (0.7%)
Snow/Blowing sand, snow4 (0.7%)
Sleet, hail (freezing rain or drizzle)3 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight417 (71.6%)
-3.0%prior 430
Dark - lighted roadway124 (21.3%)
-3.9%prior 129
Dark - roadway not lighted19 (3.3%)
-9.5%prior 21
Dusk16 (2.7%)
14.3%prior 14
Dawn6 (1.0%)
-45.5%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry448 (77.0%)
-1.5%prior 455
Wet91 (15.6%)
-30.0%prior 130
Snow29 (5.0%)
70.6%prior 17
Ice11 (1.9%)
Slush2 (0.3%)
Other1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent, with Toyota (153 vehicles), Honda (131), and Ford (119) leading in 2024, similar to the prior year's rankings. Analysis of persons involved shows a demographic shift, with a decrease in the representation of the 26-34 age group, which fell from 231 individuals in 2023 to 194 in 2024. Conversely, the number of individuals aged 65 and older involved in crashes increased from 151 to 166.

Top Vehicle Makes (1,085 vehicles)

1
TOYOTA153 (14.1%)
3.4%prior 148
2
HONDA131 (12.1%)
13.9%prior 115
3
FORD119 (11%)
3.5%prior 115
4
HYUNDAI76 (7%)
10.1%prior 69
5
CHEVROLET76 (7%)
-5.0%prior 80
6
NISSAN72 (6.6%)
-2.7%prior 74
7
SUBARU56 (5.2%)
-5.1%prior 59
8
JEEP56 (5.2%)
36.6%prior 41
9
GMC27 (2.5%)
17.4%prior 23
10
KIA25 (2.3%)
19.0%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (1,301 persons with recorded sex)

Male721 (55.4%)
-1.9%prior 735
Female580 (44.6%)
-7.1%prior 624

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

A significant redistribution of crashes across speed zones occurred between 2023 and 2024. The number of crashes in 25 mph zones more than doubled, increasing from 79 to 182 incidents. Concurrently, crashes in 30 mph zones decreased from 177 to 78, and those in 35 mph zones fell from 124 to 73. The location of fatal crashes also shifted, moving from a single fatality in a 65 mph zone in 2023 to two separate fatalities in 35 mph and 45 mph zones in 2024.

Fatal crashes by zone: 35 mph: 1 of 73 (1.37%) · 45 mph: 1 of 23 (4.348%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: WESTFIELD, MA
  • Total crash records analyzed: 583
  • Total persons involved: 1,375
  • Total vehicles involved: 1,085

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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/westfield/2024-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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Westfield, MA Crash Report — 2024 | ThatCarHitMe.com