Monthly Traffic Safety Analysis

127 CRASHES IN
WEST SPRINGFIELD, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

In September 2025, West Springfield experienced 127 crashes, a 6.72% increase from the 119 crashes recorded in September 2024. Total fatalities rose from 0 in the prior period to 1 in the current period, representing a significant year-over-year shift. Additionally, hit-and-run crashes increased by 78.6% year-over-year.

127

6.7%was 119

Total Crash Events

1

Persons Killed

44

7.3%was 41

Persons Injured

25

78.6%was 14

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 · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in West Springfield show an increase year-over-year, with total crashes rising by 6.72% from 119 to 127. Fatalities increased from 0 in September 2024 to 1 in September 2025, while total injuries also saw an increase of 7.32%, from 41 to 44.

25

Hit-and-Run Crashes — September 2025

78.6% vs prior (14)

Hit-and-run crashes increased by 11, from 14 in September 2024 to 25 in September 2025, representing a 78.6% rise in count. Concurrently, the hit-and-run crash rate increased from 11.8% to 19.7%, indicating an upward trend in these incidents.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

2

Cyclists Injured

Prior: 1100.0%

40

Motorists Injured

Prior: 378.1%

2

Other Injured

Prior: 1100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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 September 2024 (19 crashes) to Saturday in September 2025 (23 crashes). While the peak hour remained 4 p.m. in both periods, the number of crashes at this hour decreased from 16 to 13. Notable shifts in daily patterns include a 7-crash increase on Saturdays and a 7-crash decrease at 11 a.m. year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate increased from 0% in September 2024 to 0.79% in September 2025, with 1 fatal crash occurring in the current period compared to none previously. The proportion of crashes resulting in any injury (Serious, Minor, or Possible) slightly increased from 24.37% (29 crashes) to 25.98% (33 crashes) year-over-year. Serious injuries decreased from 2 crashes in the prior period to 1 crash in the current period.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.8%
Serious Injury1serious injury crashes0.8%
-50.0%prior 2
Minor Injury18minor injury crashes14.2%
-10.0%prior 20
Possible Injury14possible injury crashes11%
100.0%prior 7
No Injury93no injury crashes73.2%
5.7%prior 88

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record

Top Contributing Factors

Crashes involving "Failed to yield right of way" increased by 9, from 13 to 22, representing a 69.2% rise in count. "Followed too closely" crashes saw a substantial increase of 5, from 3 to 8, a 166.7% change in count. "No improper driving" remained constant at 52 crashes in both periods, maintaining its position as the most frequent contributing factor.

Officer-Reported Primary Contributing Cause

No improper driving52 (40.9%)0.0%prior 52
Failed to yield right of way22 (17.3%)69.2%prior 13
Inattention13 (10.2%)18.2%prior 11
Followed too closely8 (6.3%)
Failure to keep in proper lane or running off road7 (5.5%)40.0%prior 5
Disregarded traffic signs, signals, road markings4 (3.1%)
Distracted4 (3.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (3.1%)
Driving too fast for conditions3 (2.4%)
Physical impairment2 (1.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in rainy conditions increased significantly from 2 in September 2024 to 10 in September 2025, a 400% rise in count. Similarly, crashes on wet road surfaces increased by 8, from 7 to 15, marking a 114.3% increase. Crashes during daylight hours increased by 6, from 93 to 99, while crashes in dark, lighted roadway conditions decreased by 6, from 22 to 16.

Weather

Clear101 (80.8%)
4.1%prior 97
Rain10 (8.0%)
Clear/Clear6 (4.8%)
Rain/Cloudy3 (2.4%)
Cloudy3 (2.4%)
-75.0%prior 12
Cloudy/Cloudy1 (0.8%)
Clear/Cloudy1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash

Lighting

Daylight99 (78.6%)
6.5%prior 93
Dark - lighted roadway16 (12.7%)
-27.3%prior 22
Dawn4 (3.2%)
Dusk4 (3.2%)
Dark - roadway not lighted2 (1.6%)
Dark - unknown roadway lighting1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field

Road Surface

Dry110 (88.0%)
-0.9%prior 111
Wet15 (12.0%)
114.3%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 13.1%, from 229 to 259. The 0-15 age group saw a substantial increase in persons involved, rising by 25 from 23 to 48, a 108.7% change. Among top vehicle makes, Honda saw a 7-vehicle increase, from 21 to 28, while Toyota decreased by 1, from 31 to 30.

Top Vehicle Makes (259 vehicles)

1
TOYOTA30 (11.6%)
-3.2%prior 31
2
HONDA28 (10.8%)
33.3%prior 21
3
FORD27 (10.4%)
-10.0%prior 30
4
CHEVROLET20 (7.7%)
150.0%prior 8
5
JEEP15 (5.8%)
15.4%prior 13
6
HYUNDAI15 (5.8%)
-6.3%prior 16
7
NISSAN11 (4.2%)
-26.7%prior 15
8
SUBARU9 (3.5%)
0.0%prior 9
9
ACURA7 (2.7%)
10
BMW7 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records

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

Sex Distribution (336 persons with recorded sex)

Male184 (54.8%)
21.1%prior 152
Female152 (45.2%)
15.2%prior 132

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased by 5, from 68 to 63, but this zone recorded 1 fatal crash in the current period compared to none prior. Crashes in 40 mph zones increased by 10, from 11 to 21, and 65 mph zones saw an increase of 4 crashes, from 1 to 5. No fatalities were recorded in 40 mph or 65 mph zones in either period.

Fatal crashes by zone: 30 mph: 1 of 63 (1.587%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-09-01 through 2025-09-30 (30 days)
  • Geographic scope: WEST SPRINGFIELD, MA
  • Total crash records analyzed: 127
  • Total persons involved: 371
  • Total vehicles involved: 259

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: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-springfield/september-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 — September 2025 | ThatCarHitMe.com