ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · BARNSTABLE, MA · 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/2023-annual-report
Yearly Traffic Safety Analysis
1,253 CRASHES IN
BARNSTABLE, MA
2023
In Barnstable, total traffic crashes increased by 3.6% from 1,209 in 2022 to 1,253 in 2023. While the number of fatalities decreased from 5 to 4, the number of people injured in crashes rose significantly by 15.4%, from 397 in the prior year to 458 in the current year. This increase in injuries represents the most notable year-over-year shift in the city's crash data.
1,253
▲ 3.6%was 1,209
Total Crash Events
4
▼ -20.0%was 5
Persons Killed
458
▲ 15.4%was 397
Persons Injured
67
▲ 28.8%was 52
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. 42 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Barnstable show an increase year-over-year. The total number of crashes rose by 3.6%, from 1,209 to 1,253. This was accompanied by a more pronounced 15.4% increase in total injuries, which grew from 397 to 458. Conversely, traffic fatalities saw a slight decline, with 4 recorded in 2023 compared to 5 in 2022.
67
Hit-and-Run Crashes — 2023
▲ 28.8% vs prior (52)
Hit-and-run crashes trended upward in Barnstable. The total count of hit-and-run incidents increased by 28.8%, from 52 in 2022 to 67 in 2023. The hit-and-run rate, which measures these incidents as a percentage of total crashes, also rose from 4.3% in the prior year to 5.3% in the current year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
8
Pedestrians Injured
17
Cyclists Injured
428
Motorists Injured
5
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes saw a shift in the most common day for incidents. In 2023, Tuesday was the peak day with 203 crashes, whereas in 2022, Thursday was the peak with 204 crashes. The peak hour for crashes, however, remained consistent at 4 p.m. in both periods, with a slight increase in volume from 112 to 118 crashes during that hour.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes shifted year-over-year, with a decrease in fatalities but an increase in injuries. The number of fatal crashes dropped from 5 to 4, and the fatal crash rate decreased from 0.41% to 0.32%. However, crashes resulting in serious injuries increased from 21 to 26, and minor injury crashes rose from 188 to 217. Consequently, the proportion of all crashes involving any level of injury (fatal, serious, minor, or possible) increased from 24.7% in 2022 to 25.8% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'Inattention' remained a leading contributing factor in both years, its count decreased from 221 crashes in 2022 to 208 in 2023. Conversely, crashes attributed to 'Failed to yield right of way' increased in count from 129 to 151. 'Followed too closely' also saw a slight increase from 87 to 91 incidents. The count for 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from 64 in 2022 to 45 in 2023.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained broadly similar between the two periods, with most incidents in both years occurring in daylight (70.9% in 2022 vs. 72.1% in 2023) and on dry roads (81.6% vs. 82.4%). There was a slight increase in the share of crashes happening on wet road surfaces, which accounted for 13.1% of crashes in 2022 and rose to 15.0% in 2023. Similarly, crashes during rain increased proportionally, from 4.6% of all crashes in 2022 to 6.1% in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent: Toyota (384 in 2022 vs. 392 in 2023), Ford (276 vs. 298), and Honda (254 vs. 233). Regarding persons involved, the 65+ age group remained the most represented demographic in both years, with its count increasing from 447 to 478. The representation of the 26-34 age group grew, moving it into the top three most involved age groups in 2023 with 434 persons, up from 396 in the prior year.
Top Vehicle Makes (2,334 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
152 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,634 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
Year-over-year, there was an increase in crashes within lower speed zones. Incidents in 30 mph zones rose from 306 to 368, and crashes in 35 mph zones increased from 282 to 297. The distribution of fatal crashes also shifted; in 2022, fatalities occurred in 30, 35, 40, and 50 mph zones. In 2023, fatalities were recorded in 30, 35, and 45 mph zones, with the 30 mph zone seeing two fatal crashes in both years.
Fatal crashes by zone: 30 mph: 2 of 368 (0.543%) · 35 mph: 1 of 297 (0.337%) · 45 mph: 1 of 95 (1.053%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: BARNSTABLE, MA
- Total crash records analyzed: 1,253
- Total persons involved: 2,859
- Total vehicles involved: 2,334
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/barnstable/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved