ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · RANDOLPH, MA · 2023
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/2023-annual-report
Yearly Traffic Safety Analysis
962 CRASHES IN
RANDOLPH, MA
2023
In 2023, Randolph recorded 962 total crashes, a 30% increase from the 740 crashes reported in 2022. This year-over-year rise was accompanied by an increase in total fatalities from one to three and a 32.7% increase in total injuries from 110 to 146. The most notable shift was the 71.1% increase in hit-and-run crashes, which grew from 45 incidents in 2022 to 77 in 2023.
962
▲ 30.0%was 740
Total Crash Events
3
▲ 200.0%was 1
Persons Killed
146
▲ 32.7%was 110
Persons Injured
77
▲ 71.1%was 45
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 491 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for Randolph indicates a rising trend in traffic incidents year-over-year. Total crashes increased by 30%, from 740 in 2022 to 962 in 2023. This upward trend is also reflected in crash outcomes, with total injuries rising by 32.7% (from 110 to 146) and fatalities increasing from one to three.
77
Hit-and-Run Crashes — 2023
▲ 71.1% vs prior (45)
Hit-and-run incidents in Randolph showed a significant upward trend from 2022 to 2023. The total number of hit-and-run crashes increased by 71.1%, from 45 to 77. This rise outpaced the overall growth in crashes, causing the hit-and-run rate to climb from 6.1% of all crashes in 2022 to 8.0% in 2023.
Vulnerable Road User Casualties
3
Motorists Killed
146
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes in Randolph shifted between 2022 and 2023. The peak day for crashes moved from Saturday (131 crashes) in 2022 to Thursday (148 crashes) in 2023. Similarly, the peak hour for incidents shifted earlier in the day, from the 5 p.m. hour in 2022 (65 crashes) to the 2 p.m. hour in 2023 (73 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes increased from one in 2022 to two in 2023, raising the fatal crash rate from 0.14% to 0.21%. The count of minor injury crashes increased from 48 to 68, while serious injury crashes rose from 3 to 4. Despite the absolute increase in injury-related incidents, the overall proportion of crashes involving any level of injury (from possible to fatal) remained relatively stable, moving from 11.2% in 2022 to 11.6% in 2023.
Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent year-over-year, though their counts increased. 'Followed too closely' remained the top factor, with its incident count rising by 54.5% from 134 in 2022 to 207 in 2023. 'Failed to yield right of way' moved up to the second-ranked factor, with its count also increasing by 54.5% from 121 to 187. Crashes attributed to 'Failure to keep in proper lane or running off road' saw a 79.5% increase in count from 39 to 70 incidents.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both periods occurred in clear weather and on dry roads. In 2023, 78.6% of crashes were on dry surfaces, nearly identical to 78.9% in 2022; however, the proportion of crashes on wet roads increased from 16.5% in 2022 to 19.4% in 2023. Regarding lighting, crashes during daylight hours made up a slightly larger share of the total in 2023 (64.3%) compared to 2022 (61.2%), while the proportion of crashes on dark but lighted roadways decreased from 22.2% to 19.0%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained unchanged between 2022 and 2023: Toyota, Honda, and Ford. The number of vehicles from each of these makes involved in crashes increased, with Toyota up from 272 to 383 and Honda up from 172 to 278. The age distribution of persons involved in crashes was also largely consistent, with the 26-34 age group representing the largest cohort in both years, accounting for 21.1% of persons in 2022 and 20.3% in 2023.
Top Vehicle Makes (1,957 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
71 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,264 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
In 2023, the highest number of crashes occurred in 25 mph zones (218 incidents), followed by 55 mph zones (186 incidents), a pattern similar to 2022 which also saw the most crashes in 25 mph zones (202). The two fatal crashes in 2023 both occurred in a 35 mph zone, a shift from 2022, where the single fatal crash took place in a 55 mph zone. Crashes in higher speed zones of 55 mph and 65 mph saw increases in count from 156 to 186 and 112 to 139, respectively.
Fatal crashes by zone: 35 mph: 2 of 98 (2.041%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: RANDOLPH, MA
- Total crash records analyzed: 962
- Total persons involved: 2,395
- Total vehicles involved: 1,957
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/randolph/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved