Monthly Traffic Safety Analysis

116 CRASHES IN
WEST SPRINGFIELD, MA
NOVEMBER 2024

All metrics benchmarked againstNovember 2023

In November 2024, West Springfield experienced 116 total crashes, an increase from 90 crashes in November 2023. This represents a 28.89% rise in overall crash incidents year-over-year. The most notable shift was the emergence of 1 fatality in November 2024, compared to 0 fatalities in the prior year.

116

28.9%was 90

Total Crash Events

1

Persons Killed

49

276.9%was 13

Persons Injured

10

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 · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in West Springfield showed an upward trend, increasing by 28.89% from 90 crashes in November 2023 to 116 crashes in November 2024. Fatalities rose from 0 to 1, and total injuries saw a substantial increase of 276.9%, from 13 to 49.

10

Hit-and-Run Crashes — November 2024

0.0% vs prior (10)

The number of hit-and-run crashes remained constant at 10 incidents in both November 2023 and November 2024. However, due to the overall increase in total crashes, the hit-and-run rate decreased from 11.1% in the prior year to 8.6% in the current year.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

1

Cyclists Injured

Prior: 0%

48

Motorists Injured

Prior: 13269.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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 Tuesday in November 2023, with 18 incidents, to Friday in November 2024, with 24 incidents. Similarly, the peak crash hour moved from 3 PM (11 crashes) in the prior year to 5 PM (16 crashes) in the current year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The current period saw a significant increase in crash severity compared to the prior year, with 1 fatal crash and 1 serious injury crash in November 2024, whereas there were 0 fatal and 0 serious injury crashes in November 2023. Minor injury crashes more than doubled, rising from 8 to 22, and possible injury crashes increased from 2 to 9.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.9%
Serious Injury1serious injury crashes0.9%
Minor Injury22minor injury crashes19%
175.0%prior 8
Possible Injury9possible injury crashes7.8%
350.0%prior 2
No Injury82no injury crashes70.7%
6.5%prior 77

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw notable increases in crash counts year-over-year. 'Followed too closely' crashes surged by 11 incidents, from 3 to 14, representing a 366.7% increase. Crashes attributed to 'Failed to yield right of way' increased by 7 incidents (70% rise), from 10 to 17, and 'Driving too fast for conditions' rose from 0 to 6 incidents. Conversely, 'No improper driving' crashes decreased from 36 to 32 incidents.

Officer-Reported Primary Contributing Cause

No improper driving32 (27.6%)-11.1%prior 36
Failed to yield right of way17 (14.7%)70.0%prior 10
Followed too closely14 (12.1%)
Inattention13 (11.2%)44.4%prior 9
Driving too fast for conditions6 (5.2%)
Failure to keep in proper lane or running off road5 (4.3%)
Disregarded traffic signs, signals, road markings3 (2.6%)
Distracted2 (1.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (0.9%)
Other improper action1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 81 in November 2023 to 90 in November 2024. Incidents on wet road surfaces also rose, from 7 in the prior period to 21 in the current period. Crashes occurring in daylight increased from 56 to 65, while those in dark but lighted conditions saw a smaller increase from 27 to 30.

Weather

Clear79 (69.9%)
2.6%prior 77
Cloudy13 (11.5%)
Clear/Clear11 (9.7%)
Rain7 (6.2%)
Rain/Clear1 (0.9%)
Rain/Cloudy1 (0.9%)
Rain/Rain1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash

Lighting

Daylight65 (58.0%)
16.1%prior 56
Dark - lighted roadway30 (26.8%)
11.1%prior 27
Dark - roadway not lighted6 (5.4%)
Dawn5 (4.5%)
Dusk5 (4.5%)
Dark - unknown roadway lighting1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field

Road Surface

Dry95 (81.9%)
17.3%prior 81
Wet21 (18.1%)
200.0%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 169 in November 2023 to 226 in November 2024. The top vehicle make involved shifted, with Toyota moving from the second position (21 vehicles) to the first (41 vehicles), while Honda moved from first (22 vehicles) to second (27 vehicles).

Top Vehicle Makes (226 vehicles)

1
TOYOTA41 (18.1%)
95.2%prior 21
2
HONDA27 (11.9%)
22.7%prior 22
3
FORD17 (7.5%)
13.3%prior 15
4
HYUNDAI15 (6.6%)
7.1%prior 14
5
CHEVROLET15 (6.6%)
15.4%prior 13
6
NISSAN14 (6.2%)
-6.7%prior 15
7
JEEP9 (4%)
80.0%prior 5
8
KIA7 (3.1%)
9
SUBARU6 (2.7%)
10
MERCEDES-BENZ5 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records

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

Sex Distribution (263 persons with recorded sex)

Female134 (51.0%)
52.3%prior 88
Male129 (49.0%)
44.9%prior 89

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones increased from 38 in November 2023 to 54 in November 2024, with one of these crashes being fatal in the current period. Incidents in 40 mph zones rose from 14 to 23, and those in 25 mph zones increased from 5 to 8. The 65 mph zones also saw a slight increase from 6 to 7 crashes.

Fatal crashes by zone: 30 mph: 1 of 54 (1.852%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-11-01 through 2024-11-30 (30 days)
  • Geographic scope: WEST SPRINGFIELD, MA
  • Total crash records analyzed: 116
  • Total persons involved: 288
  • Total vehicles involved: 226

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: November 2024." Published June 21, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-springfield/november-2024-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 — November 2024 | ThatCarHitMe.com