Monthly Traffic Safety Analysis

17 CRASHES IN
EAST LONGMEADOW, MA
JULY 2024

All metrics benchmarked againstJuly 2023

In July 2024, East Longmeadow experienced 17 crashes, a 32% decrease compared to the 25 crashes reported in July 2023. Despite the reduction in overall crashes, total injuries increased by 100%, rising from 6 in July 2023 to 12 in July 2024, representing the most notable year-over-year shift.

17

▼ -32.0%was 25

Total Crash Events

0

Persons Killed

12

▲ 100.0%was 6

Persons Injured

2

▲ 100.0%was 1

Hit-and-Run Crashes

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes decreased by 32% year-over-year, from 25 crashes in July 2023 to 17 crashes in July 2024. However, the total number of injuries saw a substantial increase of 100%, rising from 6 to 12 over the same period.

2

Hit-and-Run Crashes — July 2024

▲ 100.0% vs prior (1)

Hit-and-run crashes increased from 1 in July 2023 to 2 in July 2024. The hit-and-run rate also rose, from 4% of total crashes in July 2023 to 11.8% in July 2024, indicating an upward trend in both count and rate.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

2

Cyclists Injured

Prior: 1↑100.0%

10

Motorists Injured

Prior: 5↑100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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 Saturday, with 7 crashes in July 2023, to Wednesday, with 5 crashes in July 2024. Similarly, the peak hour for crashes moved from 4 PM, with 4 crashes in July 2023, to 10 PM, with 2 crashes in July 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both July 2023 and July 2024. The proportion of serious injury (A) crashes increased from 8% (2 crashes) in July 2023 to 17.6% (3 crashes) in July 2024. The overall proportion of crashes resulting in any injury (A, B, or C) rose from 24% (6 of 25 crashes) to 41.2% (7 of 17 crashes) year-over-year.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes17.6%
↑50.0%prior 2
Minor Injury1minor injury crashes5.9%
↓-75.0%prior 4
Possible Injury3possible injury crashes17.6%
No Injury9no injury crashes52.9%
↓-52.6%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'Failed to yield right of way,' decreased significantly from 7 crashes in July 2023 to 1 crash in July 2024. Conversely, 'Followed too closely' increased from 1 crash (4% share) to 4 crashes (23.5% share), and 'No improper driving' increased from 3 crashes (12% share) to 4 crashes (23.5% share), becoming the joint top factors in July 2024.

Officer-Reported Primary Contributing Cause

Followed too closely4 (23.5%)
No improper driving4 (23.5%)
Inattention2 (11.8%)↓-60.0%prior 5
Failed to yield right of way1 (5.9%)↓-85.7%prior 7
Distracted1 (5.9%)
Exceeded authorized speed limit1 (5.9%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (5.9%)
Failure to keep in proper lane or running off road1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 20 in July 2023 to 14 in July 2024. Crashes on wet road surfaces also decreased, from 4 in July 2023 to 1 in July 2024. However, crashes occurring in dark conditions increased from 1 in July 2023 to 5 in July 2024.

Weather

Clear14 (82.4%)
↓-30.0%prior 20
Cloudy2 (11.8%)
Rain1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Weather condition at time of crash

Lighting

Daylight12 (70.6%)
↓-50.0%prior 24
Dark - lighted roadway2 (11.8%)
Dark - roadway not lighted2 (11.8%)
Dark - unknown roadway lighting1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Lighting condition field

Road Surface

Dry16 (94.1%)
↓-23.8%prior 21
Wet1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (27 vehicles)

1
HONDA5 (18.5%)
→0.0%prior 5
2
TOYOTA3 (11.1%)
↓-57.1%prior 7
3
CHEVROLET3 (11.1%)
4
HYUNDAI2 (7.4%)
5
KIA2 (7.4%)
6
SUBARU1 (3.7%)
7
TESL1 (3.7%)
8
VOLKSWAGEN1 (3.7%)
9
ACURA1 (3.7%)
10
VOLVO1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Vehicle unit records

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

Sex Distribution (29 persons with recorded sex)

Male17 (58.6%)
↓-46.9%prior 32
Female12 (41.4%)
↓-50.0%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones decreased from 9 in July 2023 to 5 in July 2024, and crashes in 35 mph zones decreased from 10 to 7. Conversely, crashes in 30 mph zones increased from 1 to 3, and those in 45 mph zones increased from 1 to 2. There were no fatal crashes in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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: 2024-07-01 through 2024-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-07-01 through 2024-07-31 (31 days)
  • Geographic scope: EAST LONGMEADOW, MA
  • Total crash records analyzed: 17
  • Total persons involved: 33
  • Total vehicles involved: 27

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). "EAST LONGMEADOW, MA Crash Intelligence Report: July 2024." Published June 21, 2026. Reporting period: 2024-07-01 to 2024-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/east-longmeadow/july-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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East Longmeadow, MA Crash Report — July 2024 | ThatCarHitMe.com