ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BARNSTABLE, 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/barnstable/january-2022-report
Monthly Traffic Safety Analysis
72 CRASHES IN
BARNSTABLE, MA
JANUARY 2022
In January 2022, BARNSTABLE, MA experienced 72 total crashes, a slight increase from the 71 crashes reported in January 2021, representing a 1.41% rise. Total injuries increased by 42.11% year-over-year, from 19 to 27. The most notable shift was a 200% increase in speeding-related crashes, rising from 3 in the prior period to 9 in the current period.
72
▲ 1.4%was 71
Total Crash Events
0
Persons Killed
27
▲ 42.1%was 19
Persons Injured
2
▼ -33.3%was 3
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. 5 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, crashes in BARNSTABLE remained relatively stable year-over-year, with a minor increase of 1 crash (1.41%) from 71 to 72. However, total injuries saw a significant increase, rising by 8 injuries or 42.11%, from 19 to 27. Fatalities remained at zero in both periods.
2
Hit-and-Run Crashes — January 2022
▼ -33.3% vs prior (3)
Hit-and-run crashes decreased from 3 in January 2021 to 2 in January 2022. The hit-and-run rate also decreased from 4.2% in the prior period to 2.8% in the current period, indicating a downward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
26
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 peak day for crashes shifted from Tuesday (13 crashes) in January 2021 to Wednesday (14 crashes) in January 2022. The peak hour also shifted, with the highest crash count moving from 5 PM (9 crashes) in the prior period to 3 PM (7 crashes) in the current period. Crashes occurring between 1 AM and 7 AM showed an increase from 5 crashes in the prior period to 16 crashes in the current period.
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 fatal crashes in either January 2021 or January 2022. Serious injury crashes increased by 200%, rising from 1 crash (1.4% of total) in the prior period to 3 crashes (4.2% of total) in the current period. Minor injury crashes also increased, from 8 (11.3% of total) to 11 (15.3% of total), while possible injury crashes decreased from 6 (8.5% of total) to 5 (6.9% of total).
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 number of crashes attributed to 'No improper driving' increased from 10 in January 2021 to 17 in January 2022, a 70% increase in count. Crashes involving 'Driving too fast for conditions' saw a 133.3% increase in count, rising from 3 to 7. Conversely, crashes due to 'Failed to yield right of way' decreased significantly from 7 to 1, an 85.7% decrease in count.
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 decreased from 46 in January 2021 to 42 in January 2022. Crashes during snowy conditions increased from 3 to 5, while wet road surface crashes decreased from 12 to 8. The current period also reported 8 crashes on icy road surfaces, a condition not explicitly listed in the prior period's top categories.
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
Toyota, which was the top vehicle make involved in crashes in January 2021 with 27 vehicles, saw its count decrease to 15 in January 2022. Ford vehicles involved in crashes increased slightly from 18 to 19, while Chevrolet saw a decrease from 21 to 9. The age group 0-15 saw a 150% increase in persons involved in crashes, rising from 2 to 5, while the 65+ age group decreased by 36%, from 25 to 16.
Top Vehicle Makes (123 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Vehicle unit records
10 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (126 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
Crashes in 30 mph zones decreased from 19 in January 2021 to 13 in January 2022, and 35 mph zones saw a slight decrease from 17 to 15 crashes. Notably, crashes in 55 mph zones experienced a 200% increase, rising from 4 in the prior period to 12 in the current period. No fatalities were reported in any speed zone during either period.
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: BARNSTABLE, MA
- Total crash records analyzed: 72
- Total persons involved: 136
- Total vehicles involved: 123
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). "BARNSTABLE, 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/barnstable/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