Monthly Traffic Safety Analysis

12 CRASHES IN
TOPSFIELD, MA
OCTOBER 2025

All metrics benchmarked againstOctober 2024

TOPSFIELD experienced an increase in total crashes from 7 in October 2024 to 12 in October 2025, marking a 71.4% rise year-over-year. The most notable shift was a 300% increase in crashes attributed to 'Failed to yield right of way,' rising from 1 crash in the prior period to 4 crashes in the current period.

12

71.4%was 7

Total Crash Events

0

Persons Killed

3

200.0%was 1

Persons Injured

0

-100.0%was 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 · 2025-10-01 to 2025-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the trend indicates a significant increase in crash activity in TOPSFIELD, with total crashes rising by 71.4% from 7 crashes in October 2024 to 12 crashes in October 2025. This represents an increase of 5 crashes 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 · 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 patterns of crashes shifted year-over-year. In October 2024, the peak day for crashes was Saturday with 2 incidents, and the peak hour was 10p with 2 incidents. However, in October 2025, the peak day shifted to Wednesday with 3 crashes, and the peak hour moved to 8a, also with 3 crashes.

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

Neither October 2024 nor October 2025 recorded any fatal crashes or fatalities. However, total injuries increased from 1 person in October 2024 to 3 persons in October 2025. The proportion of injury crashes changed, with October 2024 having 1 possible injury crash (14.3% of total crashes), while October 2025 saw 2 minor injury crashes (16.7%) and 1 possible injury crash (8.3%).

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes16.7%
Possible Injury1possible injury crashes8.3%
0.0%prior 1
No Injury9no injury crashes75%
50.0%prior 6

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

Comparing contributing factors, 'Failed to yield right of way' saw a substantial increase, rising from 1 crash in October 2024 to 4 crashes in October 2025. Conversely, crashes with 'No improper driving' decreased from 2 in the prior period to 1 in the current period. 'Inattention' remained constant with 1 crash in both periods, while factors like 'Followed too closely' and 'Driving too fast for conditions' appeared in October 2025 with 1 crash each, having not been present in October 2024.

Officer-Reported Primary Contributing Cause

Failed to yield right of way4 (33.3%)
Followed too closely1 (8.3%)
Disregarded traffic signs, signals, road markings1 (8.3%)
No improper driving1 (8.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (8.3%)
Inattention1 (8.3%)
Driving too fast for conditions1 (8.3%)

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 clear weather conditions increased from 6 in October 2024 to 8 in October 2025, while crashes in wet road surface conditions rose from 1 to 4. Daylight crashes significantly increased from 3 in the prior period to 9 in the current period, with crashes in dark, unlit conditions decreasing from 2 to 0, and dusk crashes appearing with 1 incident in October 2025.

Weather

Clear8 (66.7%)
33.3%prior 6
Rain2 (16.7%)
Rain/Cloudy2 (16.7%)

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

Lighting

Daylight9 (75.0%)
Dark - lighted roadway2 (16.7%)
Dusk1 (8.3%)

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

Road Surface

Dry8 (66.7%)
33.3%prior 6
Wet4 (33.3%)

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

Vehicles & Demographics

Top Vehicle Makes (20 vehicles)

1
TOYOTA4 (20%)
2
HONDA4 (20%)
3
FORD3 (15%)
4
NISSAN2 (10%)
5
SUBARU2 (10%)
6
WHITE GMC1 (5%)
7
LEXUS1 (5%)
8
MAZDA1 (5%)
9
VOLKSWAGEN1 (5%)
10
ACURA1 (5%)

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

Sex Distribution (24 persons with recorded sex)

Female12 (50.0%)
140.0%prior 5
Male12 (50.0%)
-7.7%prior 13

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

While no fatal crashes occurred in any speed zone during either period, there were shifts in crash distribution across speed limits. Crashes in 45 mph zones increased from 4 in October 2024 to 6 in October 2025, while crashes in 30 mph zones remained constant at 2. October 2025 also saw new crashes in 20 mph (1), 25 mph (1), and 65 mph (2) zones, which were not present in October 2024.

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: TOPSFIELD, MA
  • Total crash records analyzed: 12
  • Total persons involved: 24
  • Total vehicles involved: 20

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 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/topsfield/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

ThatCarHitMe.com · An Injuria.ai Company

Topsfield, MA Crash Report — October 2025 | ThatCarHitMe.com