Monthly Traffic Safety Analysis

112 CRASHES IN
WEST SPRINGFIELD, MA
MAY 2025

All metrics benchmarked againstMay 2024

In May 2025, West Springfield experienced 112 total crashes, a decrease from the 121 crashes reported in May 2024, representing a 7.4% reduction. The most notable year-over-year shift was the occurrence of one fatality in May 2025, compared to zero fatalities in May 2024.

112

-7.4%was 121

Total Crash Events

1

Persons Killed

29

-3.3%was 30

Persons Injured

14

-22.2%was 18

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a slight decrease in total crashes, with 112 crashes in May 2025 compared to 121 crashes in May 2024. This represents a 7.4% reduction in the total number of crash events year-over-year. However, the period saw an increase in fatalities from 0 to 1.

14

Hit-and-Run Crashes — May 2025

-22.2% vs prior (18)

The number of hit-and-run crashes decreased from 18 in May 2024 to 14 in May 2025. Consequently, the hit-and-run rate also trended downward, from 14.9% in the prior period to 12.5% in the current period. This indicates a reduction in both the count and proportion of hit-and-run incidents.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

1

Cyclists Injured

Prior: 10.0%

28

Motorists Injured

Prior: 29-3.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Thursday in May 2024 (26 crashes) to Wednesday in May 2025 (23 crashes). The peak hour for crashes remained 3 PM for both periods, with 15 crashes in May 2025 and 16 crashes in May 2024. This indicates a consistent afternoon peak in crash activity.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

May 2025 recorded one fatal crash, resulting in one fatality, compared to zero fatal crashes and zero fatalities in May 2024. Minor injury crashes decreased from 20 in May 2024 to 10 in May 2025, while possible injury crashes increased from 4 to 8 over the same period. The prior period also reported 2 serious injury crashes, a category not present in the current period's data.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.9%
Minor Injury10minor injury crashes8.9%
-50.0%prior 20
Possible Injury8possible injury crashes7.1%
100.0%prior 4
No Injury92no injury crashes82.1%
-2.1%prior 94

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' decreased from 53 in May 2024 to 44 in May 2025, a reduction of 9 crashes. Conversely, 'Failed to yield right of way' crashes increased from 8 to 11, and 'Followed too closely' crashes rose from 7 to 11. 'Inattention' crashes saw a significant decrease, from 16 in May 2024 to 8 in May 2025.

Officer-Reported Primary Contributing Cause

No improper driving44 (39.3%)-17.0%prior 53
Failed to yield right of way11 (9.8%)37.5%prior 8
Followed too closely11 (9.8%)57.1%prior 7
Inattention8 (7.1%)-50.0%prior 16
Failure to keep in proper lane or running off road8 (7.1%)
Visibility obstructed4 (3.6%)
Other improper action3 (2.7%)-40.0%prior 5
Disregarded traffic signs, signals, road markings3 (2.7%)
Exceeded authorized speed limit2 (1.8%)
Made an improper turn2 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 82 in May 2024 to 64 in May 2025, while 'Cloudy' conditions saw a slight increase from 17 to 20 crashes. Crashes on 'Dry' road surfaces decreased from 95 to 90, and those on 'Wet' surfaces decreased from 24 to 21. Daylight crashes decreased from 101 to 86, but crashes in 'Dark - lighted roadway' conditions increased from 10 to 17.

Weather

Clear64 (58.2%)
-22.0%prior 82
Cloudy20 (18.2%)
17.6%prior 17
Rain11 (10.0%)
10.0%prior 10
Clear/Clear9 (8.2%)
Rain/Cloudy3 (2.7%)
Cloudy/Rain2 (1.8%)
-71.4%prior 7
Rain/Rain1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight86 (78.2%)
-14.9%prior 101
Dark - lighted roadway17 (15.5%)
70.0%prior 10
Dawn3 (2.7%)
Dusk2 (1.8%)
-60.0%prior 5
Dark - unknown roadway lighting1 (0.9%)
Dark - roadway not lighted1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry90 (81.1%)
-5.3%prior 95
Wet21 (18.9%)
-12.5%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 220 in May 2024 to 230 in May 2025. Toyota remained the top vehicle make involved, though its count decreased from 35 to 31. The most represented age group among persons involved shifted from 26-34 (42 persons) in May 2024 to 35-44 (59 persons) in May 2025.

Top Vehicle Makes (230 vehicles)

1
TOYOTA31 (13.5%)
-11.4%prior 35
2
HONDA23 (10%)
-17.9%prior 28
3
HYUNDAI20 (8.7%)
66.7%prior 12
4
CHEVROLET20 (8.7%)
42.9%prior 14
5
FORD13 (5.7%)
-43.5%prior 23
6
JEEP12 (5.2%)
50.0%prior 8
7
MAZDA9 (3.9%)
80.0%prior 5
8
NISSAN9 (3.9%)
-52.6%prior 19
9
LEXUS8 (3.5%)
33.3%prior 6
10
SUBARU6 (2.6%)
0.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

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

Sex Distribution (285 persons with recorded sex)

Male159 (55.8%)
26.2%prior 126
Female126 (44.2%)
38.5%prior 91

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 47 in May 2024 to 43 in May 2025, while crashes in the 40 mph zone increased from 14 to 27. Notably, the single fatality in May 2025 occurred in a 40 mph speed zone, which had no fatalities in the prior period. Crashes in the 65 mph zone decreased from 8 to 6.

Fatal crashes by zone: 40 mph: 1 of 27 (3.704%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: WEST SPRINGFIELD, MA
  • Total crash records analyzed: 112
  • Total persons involved: 304
  • Total vehicles involved: 230

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). "WEST SPRINGFIELD, MA Crash Intelligence Report: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-springfield/may-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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West Springfield, MA Crash Report — May 2025 | ThatCarHitMe.com