ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BARNSTABLE, MA · NOVEMBER 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/november-2022-report
Monthly Traffic Safety Analysis
105 CRASHES IN
BARNSTABLE, MA
NOVEMBER 2022
Total crashes in BARNSTABLE, MA increased by 7.1% from 98 in November 2021 to 105 in November 2022. The most notable year-over-year shift was a 300% increase in speeding-related crashes, rising from 1 to 4 incidents. This indicates a slight overall increase in crash volume with a significant rise in certain high-risk behaviors.
105
▲ 7.1%was 98
Total Crash Events
0
Persons Killed
29
▼ -12.1%was 33
Persons Injured
7
▲ 133.3%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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in BARNSTABLE, MA increased year-over-year, rising by 7.1% from 98 crashes in November 2021 to 105 crashes in November 2022. While total crashes saw an increase, total injuries decreased by 12.1%, from 33 to 29. Fatalities remained stable at 0 in both periods.
7
Hit-and-Run Crashes — November 2022
▲ 133.3% vs prior (3)
Hit-and-run crashes saw a significant increase, rising from 3 incidents in November 2021 to 7 incidents in November 2022. This represents a 133.3% increase in the count of hit-and-run crashes. The hit-and-run rate also trended upward, increasing from 3.1% to 6.7% of total crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
3
Pedestrians Injured
26
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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 Friday with 20 incidents in November 2021 to Tuesday with 21 incidents in November 2022. The peak hour also shifted, moving from 2 PM with 12 crashes in the prior period to 5 PM with 14 crashes in the current period. This indicates a change in the temporal patterns of crash occurrences.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of serious injury crashes remained constant at 2 in both periods, while minor injury crashes also stayed at 16. However, possible injury crashes saw a significant decrease, falling from 10 (10.2% of total crashes) in November 2021 to 2 (1.9% of total crashes) in November 2022. Consequently, crashes with no injuries increased from 69 (70.4% share) to 84 (80% share) year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw notable changes year-over-year. Crashes attributed to 'No improper driving' decreased by 3 incidents, from 29 to 26. 'Inattention' also decreased by 5 incidents, from 22 to 17, while 'Failed to yield right of way' saw a decrease of 4 incidents, from 14 to 10. Conversely, 'Followed too closely' increased by 3 incidents (from 4 to 7), 'Exceeded authorized speed limit' increased by 3 incidents (from 1 to 4), and 'Failure to keep in proper lane or running off road' also increased by 3 incidents (from 2 to 5).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 70 in November 2021 to 84 in November 2022, while those in cloudy/rain conditions decreased from 8 to 3. Crashes during daylight hours decreased from 61 to 56, but incidents in dark-lighted roadway conditions increased from 26 to 29, and dusk crashes rose from 6 to 11. The number of crashes on dry road surfaces increased from 82 to 90, while crashes on wet surfaces slightly decreased from 15 to 13.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 188 to 199 year-over-year. The 0-15 age group saw a decrease of 7 persons involved, from 19 to 12, while the 21-25 age group increased by 5 persons, from 18 to 23. Among vehicle makes, TOYOTA involvement decreased by 7 (from 42 to 35) and FORD decreased by 10 (from 23 to 13), while HONDA increased by 3 (from 25 to 28) and CHEVROLET increased by 3 (from 13 to 16).
Top Vehicle Makes (199 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records
18 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (223 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph zones increased from 22 to 30, marking an increase of 8 incidents. Conversely, crashes in 35 mph zones decreased from 26 to 22, and incidents in 45 mph zones decreased from 10 to 4. Crashes in 55 mph zones increased from 3 to 6 year-over-year. Fatalities remained at 0 across all reported speed zones in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-11-01 through 2022-11-30 (30 days)
- Geographic scope: BARNSTABLE, MA
- Total crash records analyzed: 105
- Total persons involved: 243
- Total vehicles involved: 199
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: November 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/barnstable/november-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: 2022-11-01 – 2022-11-30
Generated: June 21, 2026 · All rights reserved