ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MARLBOROUGH, MA · 2022
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/marlborough/2022-annual-report
Yearly Traffic Safety Analysis
1,022 CRASHES IN
MARLBOROUGH, MA
2022
In 2022, Marlborough recorded 1,022 total crashes, a 3.7% increase from the 986 crashes reported in 2021. While overall collisions rose, the most significant year-over-year change was a substantial decrease in traffic fatalities. The number of persons killed in crashes fell from 6 in 2021 to 1 in 2022.
1,022
▲ 3.7%was 986
Total Crash Events
1
▼ -83.3%was 6
Persons Killed
278
▲ 15.4%was 241
Persons Injured
67
▲ 17.5%was 57
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 39 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crashes in Marlborough trended upward, increasing by 3.7% from 986 in 2021 to 1,022 in 2022. This rise was accompanied by a 15.4% increase in total injuries, which grew from 241 to 278. In contrast, fatalities saw a significant decline, dropping from 6 to 1 over the same period.
67
Hit-and-Run Crashes — 2022
▲ 17.5% vs prior (57)
The number of hit-and-run incidents increased from 57 in 2021 to 67 in 2022, representing a 17.5% rise in count. The hit-and-run rate, which measures the proportion of total crashes that were hit-and-runs, also trended upward. This rate increased from 5.8% of all crashes in 2021 to 6.6% in 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
7
Pedestrians Injured
7
Cyclists Injured
264
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between the two years. The peak day for crashes moved from Tuesday (163 crashes) in 2021 to Saturday (169 crashes) in 2022. The peak hour also shifted slightly later in the afternoon, from 4 p.m. (83 crashes) in 2021 to 5 p.m. (98 crashes) in 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity improved, with fatal crashes decreasing from 6 in 2021 to 1 in 2022, dropping the fatal crash rate from 0.6% to 0.1% of all collisions. While fatal incidents declined, the number of crashes involving serious injuries rose from 11 to 15, and those with possible injuries increased from 56 to 70. The share of crashes with minor injuries remained relatively stable at 11.6% in 2022 compared to 12.5% in 2021.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, though their counts shifted. Crashes attributed to 'Inattention' increased by 26.9% in count, rising from 130 incidents in 2021 to 165 in 2022, making it the second-most cited factor. Conversely, crashes involving 'Failed to yield right of way' decreased in count from 135 to 123. 'Followed too closely' also saw an increase in count, rising from 114 to 125 incidents.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both periods occurred in clear weather on dry roads. However, there was a notable shift in conditions, with the count of crashes on wet roads decreasing from 160 in 2021 to 113 in 2022. Correspondingly, crashes during rain fell from 75 to 46. The proportion of total crashes occurring in clear weather increased from a 68.5% share in 2021 to a 76.0% share in 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes were Toyota, Honda, and Ford in both years, though their rankings changed. While Toyota remained the most frequent make (340 vehicles in 2022 vs. 321 in 2021), Ford (225) surpassed Honda (211) for the second spot. Among persons involved, there was an increase in the 65+ age group, from 157 individuals in 2021 to 184 in 2022, while the 16-20 age group saw a decrease from 268 to 245.
Top Vehicle Makes (1,933 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
238 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,044 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes increased in several speed zones, including 25 mph zones (from 149 to 162 crashes) and 40 mph zones (from 107 to 130 crashes). The 30 mph zone had the highest number of crashes in both years, though the count was stable (304 in 2021 vs. 297 in 2022). The single fatal crash in 2022 occurred in a 30 mph zone, whereas 2021's 6 fatal crashes were distributed across 30, 40, 45, and 65 mph zones.
Fatal crashes by zone: 30 mph: 1 of 297 (0.337%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: MARLBOROUGH, MA
- Total crash records analyzed: 1,022
- Total persons involved: 2,319
- Total vehicles involved: 1,933
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). "MARLBOROUGH, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marlborough/2022-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved