Monthly Traffic Safety Analysis

7 CRASHES IN
HOPEDALE, MA
JULY 2024

All metrics benchmarked againstJuly 2023

In July 2024, HOPEDALE experienced 7 total crashes, a substantial increase compared to the 3 crashes recorded in July 2023, representing a 133.3% rise. This period also saw 3 total injuries, whereas no injuries were reported in the same month last year. The most notable shift is the significant increase in both crash incidents and the appearance of injuries.

7

133.3%was 3

Total Crash Events

0

Persons Killed

3

Persons Injured

0

Fatal Crash Events

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.

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

The overall trend for crashes in HOPEDALE shows a significant increase year-over-year, with total crashes rising by 133.3% from 3 in July 2023 to 7 in July 2024. Additionally, total injuries increased from 0 in July 2023 to 3 in July 2024, further indicating a worsening trend in crash outcomes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

3

Motorists Injured

Prior: 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 temporal distribution of crashes shows some shifts year-over-year. While Thursday remained a peak day for crashes with 2 incidents in both July 2023 and July 2024, the peak hour changed from 4 PM in July 2023 to 8 PM in July 2024. Additionally, July 2024 saw crashes spread across more days of the week, including Monday, Wednesday, and Friday, which had no crashes in the prior period.

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

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes14.3%
Possible Injury1possible injury crashes14.3%
No Injury5no injury crashes71.4%

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

Comparing contributing factors, 'Inattention' increased from 1 crash in July 2023 to 2 crashes in July 2024, representing a 100% increase in count. Similarly, 'No improper driving' also rose from 1 crash to 2 crashes, a 100% increase in count. The factor 'Disregarded traffic signs, signals, road markings' remained constant at 1 crash in both periods, while 'Distracted' and 'Other improper action' emerged as new factors in July 2024, each contributing to 1 crash.

Officer-Reported Primary Contributing Cause

Inattention2 (28.6%)
No improper driving2 (28.6%)
Disregarded traffic signs, signals, road markings1 (14.3%)
Distracted1 (14.3%)
Other improper action1 (14.3%)

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

Weather conditions remained predominantly clear during crashes in both periods, with 5 crashes occurring in clear weather in July 2024 compared to 2 in July 2023. The number of crashes occurring in clear weather increased by 3. Lighting conditions data for July 2023 is not available for comparison, and road surface conditions were not reported for either period.

Weather

Clear5 (71.4%)
Clear/Unknown1 (14.3%)
Cloudy/Unknown1 (14.3%)

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

Lighting

Daylight4 (57.1%)
Dark - lighted roadway2 (28.6%)
Dusk1 (14.3%)

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

Vehicles & Demographics

Top Vehicle Makes (15 vehicles)

1
TOYOTA4 (26.7%)
2
HONDA2 (13.3%)
3
AUDI2 (13.3%)
4
GMC1 (6.7%)
5
HD1 (6.7%)
6
CHEVROLET1 (6.7%)
7
KIA1 (6.7%)
8
RAM1 (6.7%)
9
SUBARU1 (6.7%)
10
FORD1 (6.7%)

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

Sex Distribution (16 persons with recorded sex)

Male10 (62.5%)
400.0%prior 2
Female6 (37.5%)
20.0%prior 5

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

Crash distribution across speed zones shows some changes year-over-year. Crashes in the 40 mph speed zone increased from 2 in July 2023 to 4 in July 2024, a 100% increase in count. The 30 mph zone, which had no reported crashes in July 2023, recorded 3 crashes in July 2024. Conversely, the 35 mph zone, which had 1 crash in July 2023, reported no crashes in July 2024.

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: HOPEDALE, MA
  • Total crash records analyzed: 7
  • Total persons involved: 16
  • Total vehicles involved: 15

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). "HOPEDALE, 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/hopedale/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

ThatCarHitMe.com · An Injuria.ai Company

Hopedale, MA Crash Report — July 2024 | ThatCarHitMe.com