Monthly Traffic Safety Analysis

50 CRASHES IN
RANDOLPH, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

Total crashes in Randolph, MA for September decreased by 39.76% year-over-year, falling from 83 crashes in September 2024 to 50 crashes in September 2025. This significant reduction in overall crash incidents is the most notable shift in the period.

50

▼ -39.8%was 83

Total Crash Events

0

Persons Killed

16

▼ -55.6%was 36

Persons Injured

3

▼ -25.0%was 4

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 · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Randolph, MA saw a substantial decline year-over-year. Total crashes decreased from 83 in September 2024 to 50 in September 2025, marking a 39.76% reduction in crash frequency.

3

Hit-and-Run Crashes — September 2025

▼ -25.0% vs prior (4)

Hit-and-run crashes decreased in count from 4 in September 2024 to 3 in September 2025. However, the hit-and-run rate relative to total crashes increased from 4.8% to 6% year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 0→%

15

Motorists Injured

Prior: 36↓-58.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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 Sunday, with 18 crashes in September 2024, to Wednesday, with 12 crashes in September 2025. The peak hour also changed, moving from 4 p.m. (10 crashes) in the prior period to 3 p.m. (7 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities in either period. Serious injury crashes (severity A) increased from 1 in September 2024 to 2 in September 2025. Conversely, minor injury crashes (severity B) decreased from 10 to 6, and possible injury crashes (severity C) decreased from 11 to 6, contributing to a total injury reduction from 36 to 16.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes4%
↑100.0%prior 1
Minor Injury6minor injury crashes12%
↓-40.0%prior 10
Possible Injury6possible injury crashes12%
↓-45.5%prior 11
No Injury36no injury crashes72%
↓-40.0%prior 60

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Followed too closely' decreased from 19 to 15, a reduction of 4 crashes. 'Failed to yield right of way' saw a decrease of 8 crashes, from 12 to 4. Conversely, 'Disregarded traffic signs, signals, road markings' increased from 2 crashes to 3 crashes, and 'Made an improper turn' also increased from 2 to 3 crashes.

Officer-Reported Primary Contributing Cause

Followed too closely15 (30%)↓-21.1%prior 19
No improper driving9 (18%)↑12.5%prior 8
Failed to yield right of way4 (8%)↓-66.7%prior 12
Disregarded traffic signs, signals, road markings3 (6%)
Inattention3 (6%)↓-40.0%prior 5
Made an improper turn3 (6%)
Failure to keep in proper lane or running off road3 (6%)
Exceeded authorized speed limit2 (4%)
Fatigued/asleep1 (2%)
Operating defective equipment1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 33 to 24, while those in 'Clear/Clear' conditions decreased from 23 to 14. Crashes on 'Dry' road surfaces decreased from 59 to 41, and on 'Wet' surfaces from 12 to 6. The number of crashes during 'Daylight' conditions also decreased from 57 to 31.

Weather

Clear24 (50.0%)
↓-27.3%prior 33
Clear/Clear14 (29.2%)
↓-39.1%prior 23
Cloudy3 (6.3%)
Rain3 (6.3%)
↓-40.0%prior 5
Rain/Rain2 (4.2%)
Unknown/Unknown1 (2.1%)
Cloudy/Cloudy1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash

Lighting

Daylight31 (62.0%)
↓-45.6%prior 57
Dark - lighted roadway11 (22.0%)
→0.0%prior 11
Dark - roadway not lighted3 (6.0%)
↓-62.5%prior 8
Dusk3 (6.0%)
Dawn1 (2.0%)
Other1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field

Road Surface

Dry41 (87.2%)
↓-30.5%prior 59
Wet6 (12.8%)
↓-50.0%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 167 to 106. Toyota remained the top make involved, though its count decreased from 41 to 24. Notably, Jeep-involved crashes increased from 4 to 10, while Honda-involved crashes decreased from 21 to 14. The age group 26-34 saw a significant decrease in persons involved, from 42 to 20.

Top Vehicle Makes (106 vehicles)

1
TOYOTA24 (22.6%)
↓-41.5%prior 41
2
HONDA14 (13.2%)
↓-33.3%prior 21
3
JEEP10 (9.4%)
4
FORD9 (8.5%)
↓-35.7%prior 14
5
NISSAN9 (8.5%)
↓-10.0%prior 10
6
SUBARU5 (4.7%)
↓-16.7%prior 6
7
CHEVROLET5 (4.7%)
↓-44.4%prior 9
8
ACURA5 (4.7%)
9
LEXUS4 (3.8%)
10
MAZDA2 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records

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

Sex Distribution (113 persons with recorded sex)

Male70 (61.9%)
↓-41.2%prior 119
Female42 (37.2%)
↓-48.8%prior 82
X / Unspecified1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone decreased from 21 to 12, and those in the 55 mph zone decreased from 21 to 5. Conversely, crashes in the 65 mph zone increased from 8 to 11, and the 40 mph zone increased from 1 to 4. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-09-01 through 2025-09-30 (30 days)
  • Geographic scope: RANDOLPH, MA
  • Total crash records analyzed: 50
  • Total persons involved: 120
  • Total vehicles involved: 106

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). "RANDOLPH, MA Crash Intelligence Report: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/randolph/september-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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Randolph, MA Crash Report — September 2025 | ThatCarHitMe.com