Monthly Traffic Safety Analysis

129 CRASHES IN
CHICOPEE, MA
JUNE 2025

All metrics benchmarked againstJune 2024

In June 2025, Chicopee experienced 129 crashes, a 16.77% decrease compared to 155 crashes in June 2024. The most notable shift was the increase in fatalities from 0 in June 2024 to 1 in June 2025, alongside a 37.14% rise in total injuries from 35 to 48.

129

-16.8%was 155

Total Crash Events

1

Persons Killed

48

37.1%was 35

Persons Injured

21

-27.6%was 29

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. 5 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes in Chicopee decreased by 16.77%, from 155 in June 2024 to 129 in June 2025. Despite this reduction in crash volume, total fatalities increased from 0 to 1, and total injuries rose by 37.14% year-over-year.

21

Hit-and-Run Crashes — June 2025

-27.6% vs prior (29)

Hit-and-run crashes decreased from 29 in June 2024 to 21 in June 2025. Consequently, the hit-and-run rate also decreased from 18.7% to 16.3% year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

1

Pedestrians Injured

Prior: 0%

2

Cyclists Injured

Prior: 1100.0%

45

Motorists Injured

Prior: 3432.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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 Friday with 35 crashes in June 2024 to Monday with 33 crashes in June 2025. The peak hour also changed, moving from 4 PM with 20 crashes in June 2024 to 5 PM with 16 crashes in June 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities increased from 0 in June 2024 to 1 in June 2025, resulting in a fatal crash rate of 0.78% in June 2025 compared to 0% in the prior year. Total injuries rose by 37.14%, from 35 to 48. The proportion of serious injuries increased from 1.9% to 3.1%, while minor injuries increased from 8.4% to 16.3%, and possible injuries decreased from 7.7% to 4.7%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.8%
Serious Injury4serious injury crashes3.1%
33.3%prior 3
Minor Injury21minor injury crashes16.3%
61.5%prior 13
Possible Injury6possible injury crashes4.7%
-50.0%prior 12
No Injury92no injury crashes71.3%
-22.7%prior 119

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

The count of "No improper driving" crashes decreased from 40 in June 2024 to 24 in June 2025, a reduction of 16 crashes. "Inattention" saw an increase from 23 crashes to 27 crashes, while "Followed too closely" decreased from 20 crashes to 14 crashes. The top contributing factor shifted from "No improper driving" in June 2024 to "Inattention" in June 2025.

Officer-Reported Primary Contributing Cause

Inattention27 (20.9%)17.4%prior 23
No improper driving24 (18.6%)-40.0%prior 40
Followed too closely14 (10.9%)-30.0%prior 20
Failed to yield right of way9 (7%)-10.0%prior 10
Failure to keep in proper lane or running off road9 (7%)-30.8%prior 13
Disregarded traffic signs, signals, road markings7 (5.4%)16.7%prior 6
Other improper action7 (5.4%)16.7%prior 6
Made an improper turn5 (3.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (3.1%)-33.3%prior 6
Distracted3 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Clear" weather decreased from 119 in June 2024 to 74 in June 2025, while "Cloudy" conditions saw an increase from 7 to 15 crashes. The number of crashes during "Daylight" decreased from 131 to 104, whereas crashes in "Dark - lighted roadway" increased from 16 to 19. Crashes on "Dry" road surfaces decreased from 131 to 108, while those on "Wet" surfaces remained relatively stable, decreasing slightly from 22 to 21.

Weather

Clear74 (57.8%)
-37.8%prior 119
Cloudy15 (11.7%)
114.3%prior 7
Clear/Clear13 (10.2%)
Rain8 (6.3%)
-20.0%prior 10
Rain/Cloudy5 (3.9%)
Cloudy/Rain3 (2.3%)
Clear/Unknown3 (2.3%)
Cloudy/Cloudy2 (1.6%)
Clear/Other2 (1.6%)
Cloudy/Unknown1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Lighting

Daylight104 (81.3%)
-20.6%prior 131
Dark - lighted roadway19 (14.8%)
18.8%prior 16
Dark - roadway not lighted2 (1.6%)
Dusk2 (1.6%)
Dawn1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field

Road Surface

Dry108 (83.7%)
-17.6%prior 131
Wet21 (16.3%)
-4.5%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 293 in June 2024 to 253 in June 2025, and total persons involved decreased from 401 to 351. Honda became the top make involved in crashes with 42 vehicles in June 2025, surpassing Toyota which had 45 vehicles in June 2024 but decreased to 26 in June 2025. The 21-25 age group saw an increase from 30 to 43 persons involved, while the 26-34 and 35-44 age groups experienced decreases from 58 to 40 and 61 to 47 respectively.

Top Vehicle Makes (253 vehicles)

1
HONDA42 (16.6%)
5.0%prior 40
2
TOYOTA26 (10.3%)
-42.2%prior 45
3
CHEVROLET24 (9.5%)
4.3%prior 23
4
NISSAN20 (7.9%)
-9.1%prior 22
5
HYUNDAI20 (7.9%)
25.0%prior 16
6
FORD18 (7.1%)
-33.3%prior 27
7
JEEP10 (4%)
42.9%prior 7
8
ACURA6 (2.4%)
20.0%prior 5
9
VOLKSWAGEN6 (2.4%)
10
BMW6 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

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

Sex Distribution (306 persons with recorded sex)

Male170 (55.6%)
2.4%prior 166
Female136 (44.4%)
-19.5%prior 169

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed limit zone increased from 40 in June 2024 to 45 in June 2025, and this zone recorded the only fatality (1) in June 2025, compared to 0 in the prior year. Crashes in the 30 mph zone decreased from 39 to 26, while crashes in the 35 mph zone increased from 18 to 24.

Fatal crashes by zone: 25 mph: 1 of 45 (2.222%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: CHICOPEE, MA
  • Total crash records analyzed: 129
  • Total persons involved: 351
  • Total vehicles involved: 253

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). "CHICOPEE, MA Crash Intelligence Report: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/june-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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Chicopee, MA Crash Report — June 2025 | ThatCarHitMe.com