ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BARNSTABLE, MA · 2025
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/2025-annual-report
Yearly Traffic Safety Analysis
1,179 CRASHES IN
BARNSTABLE, MA
2025
In Barnstable, total traffic crashes decreased by 4.9% from 1,240 in the prior year to 1,179 in the current year. While overall crashes declined, the most notable year-over-year shift was a significant increase in incidents involving vulnerable road users, with bicycle-related crashes rising from 12 to 20 and the number of cyclists injured increasing from 13 to 24.
1,179
▼ -4.9%was 1,240
Total Crash Events
4
Persons Killed
420
▲ 0.5%was 418
Persons Injured
62
▲ 6.9%was 58
Hit-and-Run Crashes
Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 21 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend shows a slight decrease in the total number of crashes by 4.9% year-over-year. However, the severity of outcomes remained relatively stable, with total fatalities holding steady at 4 and total injuries seeing a negligible increase from 418 to 420.
62
Hit-and-Run Crashes — 2025
▲ 6.9% vs prior (58)
The number of hit-and-run crashes increased from 58 in the prior year to 62 in the current year. Correspondingly, the hit-and-run rate, which measures the proportion of all crashes that are hit-and-runs, also trended upward from 4.7% to 5.3%.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
15
Pedestrians Injured
24
Cyclists Injured
376
Motorists Injured
5
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent between the two periods. Tuesday was the peak day for crashes in both years, with 204 incidents in the current year and 200 in the prior. The peak hour for crashes shifted slightly earlier, from 5 p.m. in the prior year to 4 p.m. in the current year, though the number of crashes at the peak hour was identical at 111.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the number of fatal crashes remained unchanged at 4, the fatal crash rate saw a minor increase from 0.32% to 0.34%. The overall proportion of crashes resulting in an injury rose from 25.2% to 27.3% year-over-year. This increase was primarily driven by a rise in the share of 'Minor Injury' crashes, which grew from 15.6% to 18.7% of all incidents.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, with 'Inattention' being the most common cause in both periods, increasing in count from 240 to 258. In contrast, crashes attributed to 'Failed to yield right of way' decreased from 145 to 119, and incidents where a driver 'Followed too closely' dropped from 83 to 60. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' saw a small increase in count from 51 to 54.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across different environmental conditions showed little change year-over-year. Crashes in daylight accounted for 72.9% of incidents in the current period compared to 71.9% previously. Similarly, the proportion of crashes on dry road surfaces was stable, representing 84.3% of crashes in the current year versus 82.3% in the prior year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
Toyota, Ford, and Honda were the three most common vehicle makes involved in crashes in both years, with Toyota leading at 381 vehicles in the current period, down from 393. Demographically, the 65+ age group remained the most represented group of persons involved in crashes in both periods, with 499 individuals in the current year. The 26-34 age group saw a notable decrease in involvement, from 440 people to 372.
Top Vehicle Makes (2,220 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
182 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,549 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes remained most frequent in 30 mph and 35 mph zones in both periods, although collisions in 30 mph zones decreased from 429 to 362. A notable shift occurred in the location of fatal crashes; in the prior year, they occurred in 30, 35, and 55 mph zones, while in the current year, they were recorded in lower-speed 15, 20, and 30 mph zones.
Fatal crashes by zone: 15 mph: 1 of 51 (1.961%) · 20 mph: 1 of 39 (2.564%) · 30 mph: 2 of 362 (0.552%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: BARNSTABLE, MA
- Total crash records analyzed: 1,179
- Total persons involved: 2,760
- Total vehicles involved: 2,220
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/barnstable/2025-annual-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved