ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · RANDOLPH, MA · 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/randolph/2025-annual-report
Yearly Traffic Safety Analysis
738 CRASHES IN
RANDOLPH, MA
2025
In 2025, Randolph recorded 738 total vehicle crashes, an 18.3% decrease from the 903 crashes reported in 2024. Despite the overall reduction in collisions, the number of fatalities rose from one in 2024 to three in 2025. The total number of people injured also increased by 7.9%, from 266 to 287.
738
▼ -18.3%was 903
Total Crash Events
3
▲ 200.0%was 1
Persons Killed
287
▲ 7.9%was 266
Persons Injured
72
▼ -23.4%was 94
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 16 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 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in crash volume shows a significant year-over-year decline, with total crashes falling by 18.3% from 903 in 2024 to 738 in 2025. However, this decrease in total incidents did not correspond to a reduction in crash severity. The number of people injured increased by 7.9%, and the number of fatalities tripled from one to three.
72
Hit-and-Run Crashes — 2025
▼ -23.4% vs prior (94)
Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. The number of hit-and-run crashes fell from 94 in 2024 to 72 in 2025. Correspondingly, the hit-and-run rate saw a slight decline, moving from 10.4% of all crashes in the prior year to 9.8% in the current year.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
6
Pedestrians Injured
1
Cyclists Injured
278
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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 between the two periods. The day with the most crashes changed from Wednesday (147 crashes) in 2024 to Sunday (122 crashes) in 2025. The peak hour for collisions moved slightly earlier, from 4 p.m. in the prior year to 3 p.m. in the current year. While afternoon hours remained the most frequent time for crashes in both years, the weekly distribution of crashes became more uniform in 2025 compared to the pronounced midweek peak observed in 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes decreased, their severity increased year-over-year. The fatal crash rate rose from 0.11% in 2024 to 0.41% in 2025, with fatal crashes tripling from one to three. The proportion of crashes resulting in any type of injury (Serious, Minor, or Possible) grew from 19.0% of crashes in 2024 to 29.3% in 2025. Notably, the count of crashes involving serious injuries tripled from 7 to 21.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes saw a shift in ranking and volume year-over-year. While 'Followed too closely' was the top factor in 2024 with 211 incidents, its count decreased by 23.2% to 162 in 2025, making it the second-leading factor. 'No improper driving' became the most cited factor in 2025, with its count increasing by 20.4% from 137 to 165. Crashes attributed to 'Failed to yield right of way' also decreased in count by 12.5%, from 152 to 133.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained broadly similar year-over-year, with the majority of incidents in both periods occurring in daylight on dry roads. However, there was an increase in the proportion of crashes happening in darkness, which rose from 29.9% of all crashes in 2024 to 32.4% in 2025. Specifically, collisions on dark but lighted roadways increased in count from 166 to 192. The share of crashes on wet road surfaces remained stable at approximately 15% in both years.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in crashes remained unchanged between 2024 and 2025: Toyota, Honda, Ford, Nissan, and Chevrolet, in that order. The number of vehicles from each of these top makes involved in collisions decreased, in line with the overall drop in total crashes. The age distribution of persons involved in crashes also remained largely consistent, with no significant shifts in the proportional representation of any specific age group year-over-year.
Top Vehicle Makes (1,516 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
208 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,681 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
There was a shift in the distribution of crashes across different speed zones. The proportion of crashes occurring in zones with posted speed limits of 40 mph or higher decreased from 45.8% in 2024 to 38.7% in 2025, indicating a relative increase in incidents in lower-speed areas. In 2025, fatal crashes were recorded in a 25 mph zone and a 55 mph zone. This contrasts with 2024, where the single fatal crash occurred in a 30 mph zone.
Fatal crashes by zone: 25 mph: 1 of 180 (0.556%) · 55 mph: 1 of 119 (0.84%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: RANDOLPH, MA
- Total crash records analyzed: 738
- Total persons involved: 1,865
- Total vehicles involved: 1,516
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/randolph/2025-annual-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
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved