Monthly Traffic Safety Analysis

30 CRASHES IN
HANOVER, MA
SEPTEMBER 2023

All metrics benchmarked againstSeptember 2022

Total crashes in Hanover, MA increased by 15.38% from 26 in September 2022 to 30 in September 2023. This period also saw a substantial 166.67% increase in total injuries, rising from 6 to 16. DUI-related crashes, which were absent in the prior period, accounted for 3 crashes in the current period.

30

15.4%was 26

Total Crash Events

0

Persons Killed

16

166.7%was 6

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 · 2023-09-01 to 2023-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash activity in Hanover, MA showed an upward trend year-over-year, with total crashes increasing by 4, from 26 to 30. This 15.38% rise in crashes was accompanied by a significant 166.67% increase in total injuries, from 6 to 16. Fatalities remained at zero for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

16

Motorists Injured

Prior: 6166.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · 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 crashes in the prior period, to Saturday, with 7 crashes in the current period. The peak crash hour also changed, moving from 3 PM (5 crashes) in September 2022 to 9 PM (4 crashes) in September 2023. Additionally, Tuesday crashes significantly decreased from 5 in the prior period to 1 in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While both periods reported zero fatalities, the total number of injured persons increased substantially from 6 in September 2022 to 16 in September 2023. Serious injury crashes remained consistent at 1 in both periods, but minor injury crashes doubled from 2 to 4, and possible injury crashes tripled from 2 to 6. Consequently, the proportion of crashes resulting in no injury decreased from 80.8% in the prior period to 63.3% in the current period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.3%
0.0%prior 1
Minor Injury4minor injury crashes13.3%
100.0%prior 2
Possible Injury6possible injury crashes20%
200.0%prior 2
No Injury19no injury crashes63.3%
-9.5%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Most severe injury per crash record

Top Contributing Factors

The factor 'Failed to yield right of way' remained the top contributing factor, increasing from 7 crashes in the prior period to 9 crashes in the current period. 'Followed too closely' saw a notable increase in count, rising from 1 crash to 7 crashes, making it the second most frequent factor in the current period. Conversely, 'Failure to keep in proper lane or running off road' decreased from 4 crashes to 1 crash year-over-year.

Officer-Reported Primary Contributing Cause

Failed to yield right of way9 (30%)28.6%prior 7
Followed too closely7 (23.3%)
Inattention5 (16.7%)0.0%prior 5
No improper driving3 (10%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (10%)
Over-correcting/over-steering1 (3.3%)
Failure to keep in proper lane or running off road1 (3.3%)
Distracted1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring during 'Rain' conditions increased significantly from 1 in the prior period to 9 in the current period. Correspondingly, crashes on a 'Wet' road surface more than doubled, rising from 6 to 13. While 'Daylight' crashes slightly decreased from 23 to 20, crashes in 'Dark - lighted roadway' increased from 2 to 6.

Weather

Clear14 (50.0%)
7.7%prior 13
Rain9 (32.1%)
Cloudy3 (10.7%)
-66.7%prior 9
Rain/Cloudy2 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Weather condition at time of crash

Lighting

Daylight20 (66.7%)
-13.0%prior 23
Dark - lighted roadway6 (20.0%)
Dark - roadway not lighted2 (6.7%)
Dawn1 (3.3%)
Dusk1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Lighting condition field

Road Surface

Dry17 (56.7%)
-15.0%prior 20
Wet13 (43.3%)
116.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (58 vehicles)

1
CHEVROLET8 (13.8%)
2
TOYOTA8 (13.8%)
-11.1%prior 9
3
HONDA7 (12.1%)
0.0%prior 7
4
FORD6 (10.3%)
5
NISSAN5 (8.6%)
0.0%prior 5
6
MERCEDES-BENZ3 (5.2%)
7
SUBARU3 (5.2%)
8
JEEP2 (3.4%)
9
HYUNDAI2 (3.4%)
10
MAZDA2 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Vehicle unit records

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

Sex Distribution (78 persons with recorded sex)

Female40 (51.3%)
90.5%prior 21
Male38 (48.7%)
2.7%prior 37

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Person-level records linked to crash events

Speed Limit Zones

No fatal crashes were recorded across any speed zone in either period. Crashes in the 25 mph zone increased from 2 in the prior period to 8 in the current period, and crashes in the 35 mph zone increased from 4 to 9. The 40 mph zone experienced a decrease in crashes, from 10 in the prior period to 8 in the current period. Speed limits of 5 mph and 30 mph, which accounted for 1 and 6 crashes respectively in the prior period, were not present in the current period's data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · 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: 2023-09-01 through 2023-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-09-01 through 2023-09-30 (30 days)
  • Geographic scope: HANOVER, MA
  • Total crash records analyzed: 30
  • Total persons involved: 84
  • Total vehicles involved: 58

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: September 2023." Published June 21, 2026. Reporting period: 2023-09-01 to 2023-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hanover/september-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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Hanover, MA Crash Report — September 2023 | ThatCarHitMe.com