Monthly Traffic Safety Analysis

73 CRASHES IN
RANDOLPH, MA
JANUARY 2025

All metrics benchmarked againstJanuary 2024

In January 2025, Randolph experienced 73 total crashes, a slight increase from the 72 crashes reported in January 2024, representing a 1.39% rise. A notable year-over-year shift was observed in hit-and-run incidents, which more than doubled from 4 crashes in the prior period to 11 crashes in the current period. Additionally, DUI-related crashes increased from 0 in January 2024 to 2 in January 2025.

73

1.4%was 72

Total Crash Events

0

Persons Killed

16

23.1%was 13

Persons Injured

11

175.0%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. 4 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a slight increase in total crashes, rising from 72 in January 2024 to 73 in January 2025. While fatalities remained at 0 in both periods, total injuries saw an increase from 13 in the prior year to 16 in the current year. This suggests a stable but slightly more injurious crash environment year-over-year.

11

Hit-and-Run Crashes — January 2025

175.0% vs prior (4)

Hit-and-run crashes increased significantly from 4 in January 2024 to 11 in January 2025. This represents a substantial rise in the hit-and-run rate, which climbed from 5.6% in the prior period to 15.1% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

16

Motorists Injured

Prior: 1323.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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 Tuesday with 18 crashes in January 2024 to Sunday with 14 crashes in January 2025. Similarly, the peak hour for crashes changed from 6 PM with 9 crashes in the prior period to 5 PM with 7 crashes in the current period. These shifts indicate a change in the temporal patterns of crash occurrences.

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

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

Crash Severity Breakdown

There were no fatal crashes in either January 2024 or January 2025. Crashes resulting in minor injuries increased from 4 (5.6% share) in the prior period to 5 (6.8% share) in the current period. Crashes with possible injuries also rose from 4 (5.6% share) to 9 (12.3% share) year-over-year.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes6.8%
25.0%prior 4
Possible Injury9possible injury crashes12.3%
125.0%prior 4
No Injury55no injury crashes75.3%
103.7%prior 27

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

Crashes attributed to 'No improper driving' saw a significant increase, rising from 10 in January 2024 to 21 in January 2025, an increase of 11 crashes. Conversely, 'Followed too closely' decreased from 13 crashes to 9 crashes, a reduction of 4. 'Inattention' also saw a substantial decrease, dropping from 8 crashes to 1 crash year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving21 (28.8%)110.0%prior 10
Failed to yield right of way11 (15.1%)0.0%prior 11
Followed too closely9 (12.3%)-30.8%prior 13
Driving too fast for conditions6 (8.2%)0.0%prior 6
Disregarded traffic signs, signals, road markings4 (5.5%)
Distracted3 (4.1%)
Failure to keep in proper lane or running off road3 (4.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (2.7%)
Fatigued/asleep2 (2.7%)
Other improper action2 (2.7%)-60.0%prior 5

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

Road & Environmental Conditions

Crashes occurring in 'Clear/Clear' weather conditions increased from 15 in January 2024 to 34 in January 2025, while 'Snow/Snow' conditions saw a decrease from 8 to 3 crashes. The number of crashes on 'Dry' road surfaces increased from 34 to 43, whereas crashes on 'Wet' surfaces decreased from 17 to 6. Crashes during 'Daylight' conditions slightly increased from 32 to 36, while 'Dark - lighted roadway' conditions remained stable with 25 and 26 crashes, respectively.

Weather

Clear/Clear34 (49.3%)
126.7%prior 15
Clear13 (18.8%)
-35.0%prior 20
Snow/Snow3 (4.3%)
-62.5%prior 8
Cloudy3 (4.3%)
Snow3 (4.3%)
Snow/Blowing sand, snow2 (2.9%)
Rain2 (2.9%)
Rain/Cloudy2 (2.9%)
Rain/Rain1 (1.4%)
-80.0%prior 5
Clear/Cloudy1 (1.4%)

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

Lighting

Daylight36 (49.3%)
12.5%prior 32
Dark - lighted roadway26 (35.6%)
4.0%prior 25
Dawn4 (5.5%)
Dark - roadway not lighted3 (4.1%)
-62.5%prior 8
Dark - unknown roadway lighting2 (2.7%)
Dusk2 (2.7%)
-60.0%prior 5

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

Road Surface

Dry43 (68.3%)
26.5%prior 34
Ice7 (11.1%)
40.0%prior 5
Snow7 (11.1%)
-46.2%prior 13
Wet6 (9.5%)
-64.7%prior 17

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

Vehicles & Demographics

The total number of vehicles involved in crashes slightly increased from 141 in January 2024 to 144 in January 2025. Toyota vehicles involved in crashes decreased from 30 to 25, and Honda vehicles decreased from 28 to 17. Nissan vehicles, however, saw an increase from 8 to 16 involved in crashes.

Top Vehicle Makes (144 vehicles)

1
TOYOTA25 (17.4%)
-16.7%prior 30
2
HONDA17 (11.8%)
-39.3%prior 28
3
NISSAN16 (11.1%)
100.0%prior 8
4
FORD11 (7.6%)
-26.7%prior 15
5
CHEVROLET9 (6.3%)
50.0%prior 6
6
HYUNDAI7 (4.9%)
7
JEEP6 (4.2%)
8
GMC4 (2.8%)
9
MERCEDES-BENZ4 (2.8%)
10
LEXUS4 (2.8%)
-20.0%prior 5

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

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

Sex Distribution (152 persons with recorded sex)

Male90 (59.2%)
-6.3%prior 96
Female61 (40.1%)
-1.6%prior 62
X / Unspecified1 (0.7%)

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

Speed Limit Zones

Crashes in 25 mph speed zones slightly decreased from 21 in January 2024 to 20 in January 2025. Conversely, crashes in 30 mph zones increased from 14 to 16 year-over-year. The number of crashes in 55 mph speed zones remained constant at 12 for both periods, and no fatalities were recorded in any speed zone during either period.

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

Data Coverage

  • Reporting period: 2025-01-01 through 2025-01-31 (31 days)
  • Geographic scope: RANDOLPH, MA
  • Total crash records analyzed: 73
  • Total persons involved: 172
  • Total vehicles involved: 144

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: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/randolph/january-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 — January 2025 | ThatCarHitMe.com