Monthly Traffic Safety Analysis

7 CRASHES IN
TOPSFIELD, MA
OCTOBER 2024

All metrics benchmarked againstOctober 2023

In October 2024, Topsfield experienced 7 total crashes, marking a 30% decrease compared to the 10 crashes recorded in October 2023. The most notable year-over-year shift was the reduction in total crashes and a significant change in the distribution of contributing factors. Fatalities remained at zero for both periods.

7

-30.0%was 10

Total Crash Events

0

Persons Killed

1

-50.0%was 2

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 · 2024-10-01 to 2024-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crashes, with total incidents falling by 30% from 10 crashes in October 2023 to 7 crashes in October 2024. This reduction suggests a positive shift in crash frequency year-over-year.

1

Hit-and-Run Crashes — October 2024

14.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 2-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes showed shifts year-over-year. In the prior period, Saturday was the peak day with 3 crashes, whereas in the current period, Saturday, Tuesday, and Wednesday each recorded 2 crashes. The peak hour for crashes also shifted from 2 PM (2 crashes) in the prior period to 10 PM (2 crashes) in the current period, with 10 AM also seeing 2 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Both periods reported zero total fatalities. Total injuries decreased by 50%, from 2 in October 2023 to 1 in October 2024. The proportion of crashes resulting in possible injuries also decreased, from 20% (2 crashes) in the prior period to 14.3% (1 crash) in the current period.

Outcome by Severity (Crash Events)

Possible Injury1possible injury crashes14.3%
-50.0%prior 2
No Injury6no injury crashes85.7%
-25.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Inattention' saw a 75% decrease in count, falling from 4 in the prior period to 1 in the current period. Conversely, 'No improper driving' crashes increased by 100%, from 1 in the prior period to 2 in the current period. 'Failed to yield right of way' emerged as a factor in the current period with 1 crash (14.3% share), while factors like 'Exceeded authorized speed limit' and 'Distracted' from the prior period were not present in the current data.

Officer-Reported Primary Contributing Cause

No improper driving2 (28.6%)
Failed to yield right of way1 (14.3%)
Failure to keep in proper lane or running off road1 (14.3%)
Inattention1 (14.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (14.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 9 in the prior period to 6 in the current period, while those in cloudy/rain conditions remained stable at 1 crash. Similarly, crashes on dry road surfaces decreased from 9 to 6, with wet surface crashes remaining at 1. Crashes in daylight decreased from 6 to 3, while crashes in dark-lighted roadway conditions increased from 1 to 2.

Weather

Clear6 (85.7%)
-33.3%prior 9
Cloudy/Rain1 (14.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Weather condition at time of crash

Lighting

Daylight3 (42.9%)
-50.0%prior 6
Dark - lighted roadway2 (28.6%)
Dark - roadway not lighted2 (28.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Lighting condition field

Road Surface

Dry6 (85.7%)
-33.3%prior 9
Wet1 (14.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (14 vehicles)

1
FORD3 (21.4%)
2
HYUNDAI1 (7.1%)
3
INTR1 (7.1%)
4
LNDR1 (7.1%)
5
MAZDA1 (7.1%)
6
MERCEDES-BENZ1 (7.1%)
7
RAM1 (7.1%)
8
SUBARU1 (7.1%)
9
TOYOTA1 (7.1%)
10
CHEVROLET1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Vehicle unit records

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

Sex Distribution (18 persons with recorded sex)

Male13 (72.2%)
8.3%prior 12
Female5 (27.8%)
-28.6%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones shifted year-over-year. Crashes in the 45 mph zone increased from 2 in the prior period to 4 in the current period, representing a 100% increase in count. Crashes in the 30 mph zone remained constant at 2 for both periods. Notably, crashes occurred in the 50 mph zone (1 crash) in the current period, a zone not present in the prior period, while crashes in the 20 mph, 40 mph, and 65 mph zones from the prior period were not observed in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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: 2024-10-01 through 2024-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-10-01 through 2024-10-31 (31 days)
  • Geographic scope: TOPSFIELD, MA
  • Total crash records analyzed: 7
  • Total persons involved: 20
  • Total vehicles involved: 14

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). "TOPSFIELD, MA Crash Intelligence Report: October 2024." Published June 21, 2026. Reporting period: 2024-10-01 to 2024-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/topsfield/october-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

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Topsfield, MA Crash Report — October 2024 | ThatCarHitMe.com