Monthly Traffic Safety Analysis

9 CRASHES IN
HOPEDALE, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

Total crashes in HOPEDALE, MA increased by 28.6% year-over-year, rising from 7 crashes in October 2022 to 9 crashes in October 2023. The most notable shift was a 200% increase in total injuries, from 1 in the prior period to 3 in the current period. This indicates a significant rise in injury-involved crashes.

9

28.6%was 7

Total Crash Events

0

Persons Killed

3

200.0%was 1

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 · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Total crashes increased from 7 in October 2022 to 9 in October 2023, representing a 28.6% rise. Concurrently, total injuries saw a substantial increase of 200%, rising from 1 injury in October 2022 to 3 injuries in October 2023. This indicates an upward trend in both crash frequency and injury severity year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

3

Motorists Injured

Prior: 1200.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Monday in both periods, with 4 crashes in October 2022 and 5 crashes in October 2023. The peak crash hour shifted from 3 p.m. in October 2022 (2 crashes) to 9 a.m. in October 2023 (2 crashes). Overall, temporal patterns show a consistent peak day but a change in the peak hour for crash occurrences.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While no fatal crashes occurred in either October 2022 or October 2023, the total number of injuries increased from 1 to 3. The current period saw the emergence of 1 possible injury crash (11.1% of total crashes), which was not present in the prior period. Minor injury crashes remained at 1 in both periods, though their share of total crashes decreased from 14.3% to 11.1%.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes11.1%
0.0%prior 1
Possible Injury1possible injury crashes11.1%
No Injury7no injury crashes77.8%
16.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Inattention' decreased from 3 crashes in October 2022 to 1 crash in October 2023, a 66.7% reduction in count. Conversely, 'No improper driving' was identified in 3 crashes in October 2023, compared to none in the prior period. Factors such as 'Distracted' and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' remained consistent at 1 crash each across both periods.

Officer-Reported Primary Contributing Cause

No improper driving3 (33.3%)
Distracted1 (11.1%)
Failed to yield right of way1 (11.1%)
Disregarded traffic signs, signals, road markings1 (11.1%)
Inattention1 (11.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (11.1%)
Failure to keep in proper lane or running off road1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 6 in October 2022 to 8 in October 2023. Crashes on dry road surfaces also rose from 5 to 8 year-over-year, while crashes on wet surfaces decreased from 2 to 1. Daylight crashes increased from 5 to 7, with a shift in dark/dawn conditions; October 2022 had 1 crash in 'Dark - roadway not lighted,' replaced by 1 crash at 'Dawn' in October 2023.

Weather

Clear8 (88.9%)
Rain/Other1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight7 (77.8%)
40.0%prior 5
Dark - lighted roadway1 (11.1%)
Dawn1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry8 (88.9%)
60.0%prior 5
Wet1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (15 vehicles)

1
FORD3 (20%)
2
TOYOTA3 (20%)
-50.0%prior 6
3
GMC3 (20%)
4
JEEP2 (13.3%)
5
CHEVROLET2 (13.3%)
6
NISSAN1 (6.7%)
7
KIA1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

Sex Distribution (16 persons with recorded sex)

Female10 (62.5%)
100.0%prior 5
Male6 (37.5%)
-33.3%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones increased from 2 in October 2022 to 3 in October 2023. Additionally, 2 crashes occurred in 45 mph zones in October 2023, a speed zone not present in the prior period's data. Crashes in 35 mph zones, which accounted for 1 crash in October 2022, were not observed in October 2023. No fatal crashes were reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: HOPEDALE, MA
  • Total crash records analyzed: 9
  • Total persons involved: 17
  • 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: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hopedale/october-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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Hopedale, MA Crash Report — October 2023 | ThatCarHitMe.com