Monthly Traffic Safety Analysis

144 CRASHES IN
CHICOPEE, MA
FEBRUARY 2025

All metrics benchmarked againstFebruary 2024

CHICOPEE experienced 144 crashes in February 2025, a 5.26% decrease from the 152 crashes recorded in February 2024. The most notable shift was the increase in total fatalities from 0 in the prior period to 1 in the current period, alongside an increase in fatal crashes from 0 to 1.

144

-5.3%was 152

Total Crash Events

1

Persons Killed

28

-48.1%was 54

Persons Injured

14

-30.0%was 20

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in CHICOPEE decreased year-over-year, with 144 crashes in February 2025 compared to 152 crashes in February 2024, representing a 5.26% reduction. Despite this decrease in total incidents, the city saw a fatal crash and one fatality in the current period, whereas none occurred in the prior period.

14

Hit-and-Run Crashes — February 2025

-30.0% vs prior (20)

The number of hit-and-run crashes decreased from 20 in February 2024 to 14 in February 2025. Correspondingly, the hit-and-run rate declined from 13.2% in the prior period to 9.7% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 3-66.7%

27

Motorists Injured

Prior: 51-47.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted year-over-year. In February 2025, Monday became the peak day for crashes with 25 incidents, replacing Thursday which had 36 crashes in February 2024. The peak hour also shifted, with 2 PM recording the highest number of crashes (15) in the current period, compared to 3 PM with 21 crashes in the prior period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total injuries decreased from 54 in February 2024 to 28 in February 2025, the most significant change in severity was the presence of 1 fatal crash and 1 fatality in the current period, compared to 0 in the prior period. The proportion of 'Serious Injury' crashes decreased from 2% (3 crashes) to 1.4% (2 crashes), and 'Minor Injury' crashes decreased from 13.8% (21 crashes) to 9.7% (14 crashes).

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.7%
Serious Injury2serious injury crashes1.4%
-33.3%prior 3
Minor Injury14minor injury crashes9.7%
-33.3%prior 21
Possible Injury7possible injury crashes4.9%
-36.4%prior 11
No Injury116no injury crashes80.6%
2.7%prior 113

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record

Top Contributing Factors

Analysis of contributing factors reveals several shifts. Crashes attributed to 'No improper driving' increased by 5 incidents, from 29 in February 2024 to 34 in February 2025. Conversely, crashes due to 'Failed to yield right of way' decreased by 11 incidents, from 21 to 10, and 'Inattention' crashes decreased by 6 incidents, from 25 to 19. 'Followed too closely' also saw a decrease of 5 incidents, from 17 in the prior period to 12 in the current period.

Officer-Reported Primary Contributing Cause

No improper driving34 (23.6%)17.2%prior 29
Inattention19 (13.2%)-24.0%prior 25
Driving too fast for conditions15 (10.4%)
Followed too closely12 (8.3%)-29.4%prior 17
Other improper action10 (6.9%)0.0%prior 10
Failed to yield right of way10 (6.9%)-52.4%prior 21
Failure to keep in proper lane or running off road6 (4.2%)-50.0%prior 12
Visibility obstructed5 (3.5%)
Disregarded traffic signs, signals, road markings4 (2.8%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There were notable changes in crash conditions year-over-year, particularly concerning weather and road surface. The number of crashes in 'Clear' weather decreased from 113 to 82, while crashes in 'Snow' conditions increased from 1 to 9. Similarly, crashes on 'Dry' road surfaces decreased from 137 to 68, whereas crashes on 'Snow' surfaces rose from 1 to 24. The current period also saw 18 crashes on 'Ice' surfaces and 10 crashes on 'Slush' surfaces, which were not reported in the prior period.

Weather

Clear82 (57.3%)
-27.4%prior 113
Cloudy13 (9.1%)
30.0%prior 10
Snow9 (6.3%)
Clear/Clear5 (3.5%)
Sleet, hail (freezing rain or drizzle)5 (3.5%)
Snow/Sleet, hail (freezing rain or drizzle)5 (3.5%)
Clear/Cloudy3 (2.1%)
Cloudy/Unknown3 (2.1%)
Rain2 (1.4%)
-80.0%prior 10
Snow/Snow2 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash

Lighting

Daylight100 (69.9%)
2.0%prior 98
Dark - lighted roadway29 (20.3%)
-32.6%prior 43
Dusk5 (3.5%)
-16.7%prior 6
Dawn4 (2.8%)
Dark - roadway not lighted3 (2.1%)
Dark - unknown roadway lighting2 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field

Road Surface

Dry68 (47.9%)
-50.4%prior 137
Snow24 (16.9%)
Wet22 (15.5%)
69.2%prior 13
Ice18 (12.7%)
Slush10 (7.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 298 in February 2024 to 256 in February 2025. While Toyota and Honda remained the top two most involved makes, their counts decreased from 50 to 38 and 47 to 35 respectively. Regarding persons involved, the age groups 0-15 and 16-20 saw increases in their representation, rising from 11 to 31 and 23 to 36 respectively, while the 65+ age group decreased from 40 to 19.

Top Vehicle Makes (256 vehicles)

1
TOYOTA38 (14.8%)
-24.0%prior 50
2
HONDA35 (13.7%)
-25.5%prior 47
3
FORD27 (10.5%)
-3.6%prior 28
4
HYUNDAI26 (10.2%)
8.3%prior 24
5
NISSAN19 (7.4%)
-13.6%prior 22
6
CHEVROLET13 (5.1%)
-23.5%prior 17
7
JEEP9 (3.5%)
28.6%prior 7
8
ACURA6 (2.3%)
-33.3%prior 9
9
KIA6 (2.3%)
-14.3%prior 7
10
DODGE6 (2.3%)
-33.3%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records

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

Sex Distribution (290 persons with recorded sex)

Male167 (57.6%)
-2.9%prior 172
Female123 (42.4%)
-8.2%prior 134

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes at 25 mph speed zones increased from 40 in the prior period to 54 in the current period, and notably, one fatal crash occurred in a 25 mph zone in February 2025, where there were none in February 2024. Conversely, crashes in 30 mph zones decreased from 62 to 43. There was also an increase in crashes in higher speed zones, with 55 mph zones rising from 5 to 13 crashes and 65 mph zones from 6 to 8 crashes.

Fatal crashes by zone: 25 mph: 1 of 54 (1.852%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-02-01 through 2025-02-28 (28 days)
  • Geographic scope: CHICOPEE, MA
  • Total crash records analyzed: 144
  • Total persons involved: 331
  • Total vehicles involved: 256

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: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/february-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 — February 2025 | ThatCarHitMe.com