Monthly Traffic Safety Analysis

151 CRASHES IN
CHICOPEE, MA
JULY 2023

All metrics benchmarked againstJuly 2022

In July 2023, CHICOPEE experienced 151 crashes, a decrease of 4.43% compared to the 158 crashes in July 2022. The most significant year-over-year shift was the absence of fatalities in July 2023, down from 3 fatalities in the prior year.

151

-4.4%was 158

Total Crash Events

0

-100.0%was 3

Persons Killed

50

-13.8%was 58

Persons Injured

27

3.8%was 26

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in CHICOPEE showed a slight downward trend year-over-year, with total crashes decreasing by 4.43% from 158 to 151. Fatalities saw a substantial reduction, falling from 3 in July 2022 to 0 in July 2023, while total injuries also decreased by 13.79%, from 58 to 50.

27

Hit-and-Run Crashes — July 2023

3.8% vs prior (26)

Hit-and-run crashes increased slightly from 26 in July 2022 to 27 in July 2023. This resulted in an increase in the hit-and-run rate from 16.5% to 17.9% year-over-year.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 3-100.0%

0

Other Killed

Prior: 00.0%

2

Cyclists Injured

Prior: 1100.0%

47

Motorists Injured

Prior: 55-14.5%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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 Friday with 29 crashes in July 2022 to Monday with 26 crashes in July 2023. The peak crash hour also changed, moving from 1 PM with 16 crashes in July 2022 to 3 PM with 11 crashes in July 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 2 in July 2022 to 0 in July 2023, resulting in no fatalities for the current period, down from 3. Serious injuries decreased from 5 to 3, while minor injuries saw a slight reduction from 25 to 24. Conversely, crashes with no reported injuries increased from 99 to 109.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes2%
-40.0%prior 5
Minor Injury24minor injury crashes15.9%
-4.0%prior 25
Possible Injury11possible injury crashes7.3%
-26.7%prior 15
No Injury109no injury crashes72.2%
10.1%prior 99

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Most severe injury per crash record

Top Contributing Factors

The count of crashes attributed to "No improper driving" remained stable at 33 in both periods. Crashes involving drivers who "Followed too closely" increased by 2 (11.76%) from 17 to 19, while those where drivers "Failed to yield right of way" decreased by 5 (31.25%) from 16 to 11. Crashes due to "Failure to keep in proper lane or running off road" increased by 2 (40%) from 5 to 7.

Officer-Reported Primary Contributing Cause

No improper driving33 (21.9%)0.0%prior 33
Inattention24 (15.9%)0.0%prior 24
Followed too closely19 (12.6%)11.8%prior 17
Failed to yield right of way11 (7.3%)-31.3%prior 16
Disregarded traffic signs, signals, road markings7 (4.6%)16.7%prior 6
Failure to keep in proper lane or running off road7 (4.6%)40.0%prior 5
Other improper action7 (4.6%)16.7%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner6 (4%)-25.0%prior 8
Exceeded authorized speed limit4 (2.6%)
Driving too fast for conditions4 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Clear" weather conditions decreased by 15 (12.3%) from 122 to 107, while crashes during "Rain" increased by 4 (66.7%) from 6 to 10. Similarly, crashes on "Dry" road surfaces decreased by 18 (12.8%) from 141 to 123, whereas those on "Wet" surfaces increased by 10 (66.7%) from 15 to 25.

Weather

Clear107 (72.8%)
-12.3%prior 122
Cloudy13 (8.8%)
18.2%prior 11
Rain10 (6.8%)
66.7%prior 6
Clear/Cloudy5 (3.4%)
Cloudy/Rain4 (2.7%)
Unknown/Other2 (1.4%)
Cloudy/Unknown2 (1.4%)
Rain/Cloudy1 (0.7%)
Rain/Unknown1 (0.7%)
Clear/Unknown1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Weather condition at time of crash

Lighting

Daylight107 (72.3%)
-13.7%prior 124
Dark - lighted roadway29 (19.6%)
16.0%prior 25
Dusk5 (3.4%)
Dark - roadway not lighted3 (2.0%)
Dawn2 (1.4%)
Dark - unknown roadway lighting1 (0.7%)
Other1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Lighting condition field

Road Surface

Dry123 (83.1%)
-12.8%prior 141
Wet25 (16.9%)
66.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased slightly from 294 to 285 year-over-year. Among top makes, Hyundai saw a notable increase of 10 vehicles involved, from 18 to 28, while Ford saw a decrease of 7 vehicles, from 26 to 19. The 16-20 age group experienced an increase of 11 persons involved, from 38 to 49, and the 35-44 age group saw a significant increase of 24 persons involved, from 36 to 60.

Top Vehicle Makes (285 vehicles)

1
HONDA42 (14.7%)
7.7%prior 39
2
TOYOTA31 (10.9%)
-8.8%prior 34
3
HYUNDAI28 (9.8%)
55.6%prior 18
4
NISSAN25 (8.8%)
4.2%prior 24
5
FORD19 (6.7%)
-26.9%prior 26
6
CHEVROLET17 (6%)
-19.0%prior 21
7
ACURA9 (3.2%)
8
DODGE8 (2.8%)
60.0%prior 5
9
VOLVO7 (2.5%)
10
INFI7 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Vehicle unit records

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

Sex Distribution (320 persons with recorded sex)

Male178 (55.6%)
-4.3%prior 186
Female142 (44.4%)
14.5%prior 124

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Person-level records linked to crash events

Speed Limit Zones

No fatalities were recorded in any speed zone in July 2023, compared to 1 fatality at 20 mph and 1 fatality at 30 mph in July 2022. The count of crashes in the 30 mph zone increased by 6, from 34 to 40, while crashes in the 35 mph zone decreased by 4, from 18 to 14.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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: 2023-07-01 through 2023-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-07-01 through 2023-07-31 (31 days)
  • Geographic scope: CHICOPEE, MA
  • Total crash records analyzed: 151
  • Total persons involved: 382
  • Total vehicles involved: 285

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: July 2023." Published June 21, 2026. Reporting period: 2023-07-01 to 2023-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/july-2023-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 — July 2023 | ThatCarHitMe.com