ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BARNSTABLE, MA · FEBRUARY 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/barnstable/february-2023-report
Monthly Traffic Safety Analysis
85 CRASHES IN
BARNSTABLE, MA
FEBRUARY 2023
BARNSTABLE experienced an increase in total crashes from 72 in February 2022 to 85 in February 2023, representing an 18.06% rise year-over-year. Despite this overall increase, a notable positive shift was observed in hit-and-run incidents, which decreased by 75% from 4 crashes to 1 crash. Similarly, DUI-related crashes also saw a 75% reduction over the same period.
85
▲ 18.1%was 72
Total Crash Events
1
Persons Killed
22
▼ -18.5%was 27
Persons Injured
1
▼ -75.0%was 4
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates an increase in crash incidents in BARNSTABLE, with total crashes rising by 18.06% from 72 to 85. This suggests a notable upward trend in crash frequency year-over-year. However, total injuries decreased by 18.52%, from 27 to 22.
1
Hit-and-Run Crashes — February 2023
▼ -75.0% vs prior (4)
Hit-and-run crashes significantly decreased by 75%, falling from 4 incidents in February 2022 to 1 in February 2023. Correspondingly, the hit-and-run rate dropped from 5.6% to 1.2% of total crashes. This indicates a positive downward trend in hit-and-run incidents.
Vulnerable Road User Casualties
1
Motorists Killed
22
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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 Saturday (14 crashes) in February 2022 to Thursday (16 crashes) in February 2023. The peak hour for crashes also changed, moving from 2 PM (7 crashes) in the prior period to 4 PM (13 crashes) in the current period. This indicates a shift in crash concentration towards later afternoon hours and different weekdays.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes remained stable at 1 in both periods, though the fatal rate slightly decreased from 1.39% to 1.18% of total crashes. Total injuries decreased by 18.52%, from 27 in February 2022 to 22 in February 2023. The proportion of 'No Injury' crashes significantly increased from 61.1% to 77.6% of all crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record
Top Contributing Factors
The contributing factor 'Failed to yield right of way' saw a 60% increase in count, rising from 10 crashes to 16 crashes, and moved from the third to the second most frequent factor. 'No improper driving' increased by 18.75% in count, from 16 to 19 crashes, maintaining its position as the most frequent factor. Factors like 'Over-correcting/over-steering,' 'Glare,' and 'Distracted' each saw a 200% increase in count, rising from 1 to 3 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased by 55.88% in count, from 34 to 53. Similarly, crashes on 'Dry' road surfaces rose by 70% in count, from 40 to 68. Conversely, crashes in adverse conditions like 'Wet' road surfaces decreased by 30.77% in count, from 13 to 9, and 'Ice' conditions saw a 71.43% decrease, from 7 to 2 crashes.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 24.03%, from 129 to 160. Among the top vehicle makes, Honda saw a substantial increase in count, rising from 9 to 19, while Toyota experienced a decrease from 24 to 21. The 45-54 age group showed a significant 73.33% increase in persons involved, rising from 15 to 26, and the 16-20 age group also saw a 63.64% increase, from 11 to 18 persons.
Top Vehicle Makes (160 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (177 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones increased by 31.25% in count, from 16 to 21, and this zone recorded the single fatal crash in the current period. Crashes in 35 mph zones saw a significant 136.36% increase in count, rising from 11 to 26. The fatal crash in the prior period occurred in a 40 mph zone, which did not record any fatal crashes in the current period.
Fatal crashes by zone: 30 mph: 1 of 21 (4.762%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-02-01 through 2023-02-28 (28 days)
- Geographic scope: BARNSTABLE, MA
- Total crash records analyzed: 85
- Total persons involved: 182
- Total vehicles involved: 160
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: February 2023." Published June 21, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/barnstable/february-2023-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: 2023-02-01 – 2023-02-28
Generated: June 21, 2026 · All rights reserved