Monthly Traffic Safety Analysis

47 CRASHES IN
HANOVER, MA
OCTOBER 2025

All metrics benchmarked againstOctober 2024

In October 2025, HANOVER, MA experienced 47 crashes, an increase from 34 crashes in October 2024. This represents a 38.2% rise in total crashes year-over-year. A notable shift was the emergence of 2 hit-and-run crashes in the current period, compared to none in the prior year.

47

38.2%was 34

Total Crash Events

0

Persons Killed

11

37.5%was 8

Persons Injured

2

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash activity in HANOVER, MA for October 2025 shows an upward trend compared to October 2024. Total crashes increased by 38.2%, rising from 34 to 47 incidents. Concurrently, the number of total injuries also increased by 37.5%, from 8 to 11.

2

Hit-and-Run Crashes — October 2025

4.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

11

Motorists Injured

Prior: 837.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with Friday becoming the peak day in October 2025 with 10 crashes, up from 2 crashes on Fridays in October 2024. Saturdays saw a decrease from 8 crashes in the prior period to 5 in the current period. The peak crash hour moved from 5 PM (4 crashes) in October 2024 to 3 PM (10 crashes) in October 2025, indicating a shift in peak activity to an earlier afternoon period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero for both October 2024 and October 2025. However, the number of injury-involved crashes increased from 5 in the prior period to 9 in the current period. This led to a rise in the proportion of injury crashes from 14.7% of total crashes in October 2024 to 19.1% in October 2025, with the current period also reporting 1 serious injury crash that was not present in the prior year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.1%
Minor Injury4minor injury crashes8.5%
33.3%prior 3
Possible Injury4possible injury crashes8.5%
100.0%prior 2
No Injury38no injury crashes80.9%
31.0%prior 29

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors shifted significantly year-over-year. 'No improper driving' saw the largest increase, rising from 6 crashes in October 2024 to 14 crashes in October 2025. Conversely, 'Failed to yield right of way' decreased slightly from 11 to 10 crashes, while 'Followed too closely' dropped from 8 to 3 crashes. 'Inattention' emerged as a notable factor in October 2025 with 6 crashes, not being a top factor in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving14 (29.8%)133.3%prior 6
Failed to yield right of way10 (21.3%)-9.1%prior 11
Inattention6 (12.8%)
Failure to keep in proper lane or running off road3 (6.4%)
Followed too closely3 (6.4%)-62.5%prior 8
Other improper action2 (4.3%)
Driving too fast for conditions2 (4.3%)
Visibility obstructed2 (4.3%)
Made an improper turn1 (2.1%)
Disregarded traffic signs, signals, road markings1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in adverse conditions saw a notable increase in October 2025. Crashes on wet road surfaces surged from 2 in October 2024 to 14 in October 2025, representing a significant increase in the proportion of wet-road crashes from 5.9% to 29.8%. Similarly, crashes during rainy weather increased from a negligible number in the prior year to 9 incidents in the current period, while crashes under clear weather conditions decreased proportionally from 82.3% to 61.7%.

Weather

Clear29 (61.7%)
3.6%prior 28
Rain9 (19.1%)
Clear/Clear3 (6.4%)
Rain/Cloudy2 (4.3%)
Cloudy2 (4.3%)
Cloudy/Rain1 (2.1%)
Rain/Rain1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Weather condition at time of crash

Lighting

Daylight34 (72.3%)
41.7%prior 24
Dark - lighted roadway9 (19.1%)
50.0%prior 6
Dark - roadway not lighted3 (6.4%)
Dusk1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Lighting condition field

Road Surface

Dry33 (70.2%)
3.1%prior 32
Wet14 (29.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Road surface condition field

Vehicles & Demographics

The ranking of top vehicle makes involved in crashes shifted, with Toyota becoming the most frequently involved make in October 2025 with 17 vehicles, up from 11 in the prior period. Ford, previously the top make with 15 vehicles, saw a decrease to 12. In terms of persons involved, the 65+ age group experienced the largest increase, rising from 13 persons in October 2024 to 21 persons in October 2025, and remained the largest age group involved in crashes.

Top Vehicle Makes (89 vehicles)

1
TOYOTA17 (19.1%)
54.5%prior 11
2
FORD12 (13.5%)
-20.0%prior 15
3
CHEVROLET10 (11.2%)
100.0%prior 5
4
HONDA10 (11.2%)
5
SUBARU6 (6.7%)
0.0%prior 6
6
LEXUS5 (5.6%)
7
NISSAN3 (3.4%)
8
VOLVO2 (2.2%)
9
AUDI2 (2.2%)
10
GMC2 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Vehicle unit records

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

Sex Distribution (109 persons with recorded sex)

Female65 (59.6%)
41.3%prior 46
Male44 (40.4%)
12.8%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 35 mph speed zone increased from 8 incidents in October 2024 to 13 in October 2025. There was also an increase in crashes in the 60 mph zone, rising from 1 to 4 incidents. Crashes in the 40 mph zone saw a slight decrease from 18 to 17, while no fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · 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: 2025-10-01 through 2025-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-10-01 through 2025-10-31 (31 days)
  • Geographic scope: HANOVER, MA
  • Total crash records analyzed: 47
  • Total persons involved: 116
  • Total vehicles involved: 89

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). "HANOVER, MA Crash Intelligence Report: October 2025." Published June 21, 2026. Reporting period: 2025-10-01 to 2025-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hanover/october-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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Hanover, MA Crash Report — October 2025 | ThatCarHitMe.com