ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NANTUCKET, MA · JANUARY 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/nantucket/january-2022-report
Monthly Traffic Safety Analysis
12 CRASHES IN
NANTUCKET, MA
JANUARY 2022
In January 2022, Nantucket experienced 12 total crashes, a decrease of 14.3% compared to the 14 crashes recorded in January 2021. Despite the overall reduction in crashes, the number of total injuries increased significantly by 200%, rising from 1 injury in the prior period to 3 injuries in the current period.
12
▼ -14.3%was 14
Total Crash Events
0
Persons Killed
3
▲ 200.0%was 1
Persons Injured
3
▲ 200.0%was 1
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. 3 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 2022-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes in Nantucket decreased year-over-year, falling by 2 crashes from 14 in January 2021 to 12 in January 2022, representing a 14.3% reduction. However, total injuries saw a substantial increase, rising from 1 to 3, marking a 200% increase during the same period.
3
Hit-and-Run Crashes — January 2022
▲ 200.0% vs prior (1)
Hit-and-run crashes increased substantially year-over-year, rising from 1 crash in January 2021 to 3 crashes in January 2022. This change represents a 200% increase in the number of hit-and-run incidents. Consequently, the hit-and-run rate more than tripled, from 7.1% of all crashes in January 2021 to 25% in January 2022.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
2
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · 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 year-over-year. The peak day for crashes moved from Friday in January 2021 (5 crashes) to Sunday in January 2022 (5 crashes), while crashes on Friday decreased to 1. The peak hour also shifted, with January 2021 seeing most crashes at 3 PM (3 crashes) and January 2022 at 4 PM (2 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either January 2021 or January 2022. However, total injuries increased by 200%, from 1 injury in January 2021 to 3 injuries in January 2022. The injury rate (total injuries per total crashes) also rose from 7.1% in January 2021 to 25% in January 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, 'No improper driving,' saw a significant decrease from 9 crashes (64.3% share) in January 2021 to 1 crash (8.3% share) in January 2022. 'Inattention' remained constant at 2 crashes in both periods, though its share increased from 14.3% to 16.7%. Several new factors, such as 'Failed to yield right of way' and 'Driving too fast for conditions,' each contributed to 1 crash in January 2022, but were not present in January 2021.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions remained stable at 8 crashes in both periods. January 2021 recorded 2 crashes in rainy conditions and 1 in snowy conditions, which were absent in January 2022. Crashes in 'Dark - roadway not lighted' decreased from 4 in January 2021 to 1 in January 2022, while those in 'Dark - lighted roadway' increased from 1 to 3.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Road surface condition field
Vehicles & Demographics
Top Vehicle Makes (18 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Vehicle unit records
4 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (19 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones changed, with crashes in the 30 mph zone increasing from 1 in January 2021 to 4 in January 2022. January 2022 also saw 2 crashes in 15 mph zones and 3 crashes in 25 mph zones, which were not present in the prior period. Conversely, crashes in 1 mph, 10 mph, 35 mph, and 40 mph zones, present in January 2021, were absent in January 2022, indicating a shift towards intermediate speed zones.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · 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: 2022-01-01 through 2022-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-01-31 (31 days)
- Geographic scope: NANTUCKET, MA
- Total crash records analyzed: 12
- Total persons involved: 23
- Total vehicles involved: 18
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). "NANTUCKET, MA Crash Intelligence Report: January 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/nantucket/january-2022-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 – 2022-01-31
Generated: June 21, 2026 · All rights reserved