ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BARNSTABLE, MA · DECEMBER 2024
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/december-2024-report
Monthly Traffic Safety Analysis
115 CRASHES IN
BARNSTABLE, MA
DECEMBER 2024
BARNSTABLE experienced a 16.16% increase in total crashes, rising from 99 in December 2023 to 115 in December 2024. The number of hit-and-run crashes saw a significant increase of 66.7%, growing from 3 to 5 incidents. Total injuries, however, decreased by 9.76% year-over-year.
115
▲ 16.2%was 99
Total Crash Events
0
Persons Killed
37
▼ -9.8%was 41
Persons Injured
5
▲ 66.7%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. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes in BARNSTABLE increased by 16.16% year-over-year, from 99 crashes in December 2023 to 115 crashes in December 2024. Despite this increase in total crashes, the number of total injuries decreased by 9.76%, from 41 to 37. Fatalities remained at 0 in both periods.
5
Hit-and-Run Crashes — December 2024
▲ 66.7% vs prior (3)
Hit-and-run crashes increased by 66.7% year-over-year, rising from 3 crashes in December 2023 to 5 crashes in December 2024. The hit-and-run rate also increased from 3% to 4.3%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
36
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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 Friday in December 2023, with 22 crashes, to Monday in December 2024, with 24 crashes. The peak hour for crashes remained 5p in both periods, with the count increasing from 8 crashes in December 2023 to 11 crashes in December 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at 0 in both December 2023 and December 2024. Crashes resulting in serious injuries (Severity A) decreased from 4 crashes (4% of total crashes) in the prior period to 2 crashes (1.7% of total crashes) in the current period. Conversely, crashes with minor injuries (Severity B) increased from 13 crashes (13.1% of total crashes) to 21 crashes (18.3% of total crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The number of crashes attributed to 'No improper driving' decreased from 23 to 22, a 4.3% decrease in count. 'Inattention' also saw a decrease in count, from 22 crashes to 20 crashes, representing a 9.1% reduction. 'Failure to keep in proper lane or running off road' significantly increased by 133.3%, rising from 3 crashes to 7 crashes, while 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway' accounted for 5 crashes in December 2024 but none in the prior period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather increased from 63 to 70, while 'Rain' conditions saw a decrease from 13 crashes to 5 crashes. Crashes on 'Dry' road surfaces slightly increased from 74 to 77, and crashes on 'Snow' road surfaces accounted for 13 crashes in December 2024, a condition not reported in December 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
FORD became the most frequently involved vehicle make, increasing from 25 vehicles in December 2023 to 34 in December 2024, a 36% increase. TOYOTA involvement also rose from 27 to 32 vehicles, an 18.5% increase, while HONDA involvement decreased from 23 to 18 vehicles. The 45-54 age group experienced the largest increase in persons involved, rising by 11 individuals from 27 to 38.
Top Vehicle Makes (212 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records
15 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (233 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone significantly increased from 22 in December 2023 to 49 in December 2024, a 122.7% rise, making it the zone with the highest crash count. Conversely, crashes in the 35 mph zone decreased from 28 to 22, a 21.4% reduction. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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: 2024-12-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-12-01 through 2024-12-31 (31 days)
- Geographic scope: BARNSTABLE, MA
- Total crash records analyzed: 115
- Total persons involved: 249
- Total vehicles involved: 212
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: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/barnstable/december-2024-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: 2024-12-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved