Monthly Traffic Safety Analysis

58 CRASHES IN
HANOVER, MA
MAY 2025

All metrics benchmarked againstMay 2024

Total crashes in Hanover increased significantly from 30 in May 2024 to 58 in May 2025, representing a 93.3% year-over-year rise. The most notable shift was this substantial increase in overall crash incidents.

58

93.3%was 30

Total Crash Events

0

Persons Killed

15

50.0%was 10

Persons Injured

1

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 · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Hanover are trending upwards, with a 93.3% increase in total incidents from 30 in May 2024 to 58 in May 2025. This indicates a considerable rise in crash frequency year-over-year.

1

Hit-and-Run Crashes — May 2025

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 in both May 2024 and May 2025. However, the hit-and-run rate decreased from 3.3% of total crashes in the prior period to 1.7% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

15

Motorists Injured

Prior: 966.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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 6 incidents in May 2024 to Thursday with 12 incidents in May 2025. The peak hour remained 2 PM in both periods, though the number of crashes at this hour increased from 5 to 9.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either period. The proportion of crashes resulting in any injury decreased from 30% (9 of 30 crashes) in May 2024 to 17.2% (10 of 58 crashes) in May 2025, despite the total number of injured persons increasing from 10 to 15. Serious injury crashes increased from 0 to 1.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.7%
Minor Injury7minor injury crashes12.1%
133.3%prior 3
Possible Injury2possible injury crashes3.4%
-66.7%prior 6
No Injury48no injury crashes82.8%
128.6%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Failed to yield right of way' saw a significant increase, rising from 10 crashes in May 2024 to 22 crashes in May 2025, a 120% increase in count. 'Followed too closely' also increased substantially, from 2 crashes to 7 crashes, representing a 250% increase in count.

Officer-Reported Primary Contributing Cause

Failed to yield right of way22 (37.9%)120.0%prior 10
Followed too closely7 (12.1%)
No improper driving7 (12.1%)40.0%prior 5
Failure to keep in proper lane or running off road5 (8.6%)
Inattention2 (3.4%)
Over-correcting/over-steering2 (3.4%)
Made an improper turn1 (1.7%)
Fatigued/asleep1 (1.7%)
Disregarded traffic signs, signals, road markings1 (1.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Rain' conditions increased from 3 incidents in May 2024 to 15 incidents in May 2025, a 400% rise. Similarly, crashes on 'Wet' road surfaces increased from 5 to 19, a 280% increase. The number of crashes during 'Daylight' conditions more than doubled, from 24 to 51 incidents.

Weather

Clear29 (50.0%)
70.6%prior 17
Rain15 (25.9%)
Cloudy13 (22.4%)
85.7%prior 7
Cloudy/Rain1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight51 (87.9%)
112.5%prior 24
Dark - lighted roadway3 (5.2%)
Dusk2 (3.4%)
Dark - roadway not lighted1 (1.7%)
Dawn1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry39 (67.2%)
56.0%prior 25
Wet19 (32.8%)
280.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes increased from 67 to 130. The 16-20 age group experienced a notable increase in involvement, rising from 8 persons in May 2024 to 20 persons in May 2025. CHEVROLET became the most frequently involved vehicle make in May 2025 with 14 instances, up from 4, while TOYOTA, previously the top make with 10 instances, dropped to 7.

Top Vehicle Makes (104 vehicles)

1
CHEVROLET14 (13.5%)
2
JEEP9 (8.7%)
50.0%prior 6
3
FORD9 (8.7%)
80.0%prior 5
4
HONDA8 (7.7%)
5
SUBARU8 (7.7%)
6
NISSAN8 (7.7%)
7
TOYOTA7 (6.7%)
-30.0%prior 10
8
HYUNDAI6 (5.8%)
9
GMC3 (2.9%)
10
MERCEDES-BENZ3 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

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

Sex Distribution (127 persons with recorded sex)

Male66 (52.0%)
120.0%prior 30
Female61 (48.0%)
79.4%prior 34

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 40 mph speed zone increased from 15 in May 2024 to 23 in May 2025. Crashes in the 35 mph speed zone also rose from 5 to 19 incidents, indicating a trend of more crashes occurring in higher speed limit zones.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: HANOVER, MA
  • Total crash records analyzed: 58
  • Total persons involved: 130
  • Total vehicles involved: 104

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: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hanover/may-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

ThatCarHitMe.com · An Injuria.ai Company

Hanover, MA Crash Report — May 2025 | ThatCarHitMe.com