Monthly Traffic Safety Analysis

112 CRASHES IN
BARNSTABLE, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

The city of BARNSTABLE experienced 112 crashes in October 2023, a decrease of 12 crashes (9.68%) compared to the 124 crashes in October 2022. A notable shift was the absence of traffic fatalities in October 2023, down from one fatality in the prior year. DUI-related crashes saw a significant decrease from 6 to 2, while hit-and-run crashes increased from 5 to 9.

112

-9.7%was 124

Total Crash Events

0

-100.0%was 1

Persons Killed

42

-14.3%was 49

Persons Injured

9

80.0%was 5

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 · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Total crashes decreased from 124 in October 2022 to 112 in October 2023, representing a 9.68% reduction year-over-year. Concurrently, total injuries also decreased from 49 to 42. This indicates an overall downward trend in crash incidents and associated injuries for the period.

9

Hit-and-Run Crashes — October 2023

80.0% vs prior (5)

Hit-and-run crashes increased from 5 incidents in October 2022 to 9 incidents in October 2023. This represents an 80% increase in the number of hit-and-run crashes year-over-year. Consequently, the hit-and-run rate also increased from 4% to 8%.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

0

Other Killed

Prior: 00.0%

41

Motorists Injured

Prior: 48-14.6%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak hour for crashes remained 5 p.m. in both periods, with crashes at this hour increasing from 11 in October 2022 to 13 in October 2023. The peak day shifted from Monday, with 22 crashes in October 2022, to Tuesday, with 25 crashes in October 2023. This indicates a shift in the day of the week with the highest crash frequency.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

October 2023 saw no traffic fatalities, a decrease from one fatality reported in October 2022. Total injuries decreased from 49 in October 2022 to 42 in October 2023. Serious injuries, however, increased from 1 in the prior period to 2 in the current period, while possible injuries decreased from 8 to 1.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.8%
100.0%prior 1
Minor Injury22minor injury crashes19.6%
-4.3%prior 23
Possible Injury1possible injury crashes0.9%
-87.5%prior 8
No Injury84no injury crashes75%
-3.4%prior 87

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' increased by 6 crashes (25%) from 24 to 30, becoming the most frequent factor in October 2023. 'Inattention' also increased by 5 crashes (33.3%) from 15 to 20. Conversely, 'Failed to yield right of way' decreased by 3 crashes (17.6%) from 17 to 14, and 'Followed too closely' decreased by 6 crashes (46.2%) from 13 to 7.

Officer-Reported Primary Contributing Cause

No improper driving30 (26.8%)25.0%prior 24
Inattention20 (17.9%)33.3%prior 15
Failed to yield right of way14 (12.5%)-17.6%prior 17
Followed too closely7 (6.3%)-46.2%prior 13
Disregarded traffic signs, signals, road markings5 (4.5%)-16.7%prior 6
Distracted4 (3.6%)-33.3%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (2.7%)-66.7%prior 9
Made an improper turn3 (2.7%)
Driving too fast for conditions2 (1.8%)
Other improper action2 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased slightly from 79 in October 2022 to 80 in October 2023. Crashes during rain conditions decreased from 13 to 7, and cloudy conditions decreased from 11 to 6. Similarly, crashes on wet road surfaces decreased from 33 to 15, while crashes on dry road surfaces increased from 91 to 96.

Weather

Clear80 (71.4%)
1.3%prior 79
Rain7 (6.3%)
-46.2%prior 13
Cloudy6 (5.4%)
-45.5%prior 11
Clear/Cloudy5 (4.5%)
-16.7%prior 6
Rain/Cloudy3 (2.7%)
Clear/Other3 (2.7%)
Clear/Unknown3 (2.7%)
Cloudy/Rain3 (2.7%)
-70.0%prior 10
Other1 (0.9%)
Cloudy/Unknown1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight81 (72.3%)
2.5%prior 79
Dark - lighted roadway16 (14.3%)
-27.3%prior 22
Dark - roadway not lighted8 (7.1%)
-27.3%prior 11
Dawn4 (3.6%)
Dusk2 (1.8%)
-71.4%prior 7
Other1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry96 (86.5%)
5.5%prior 91
Wet15 (13.5%)
-54.5%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 233 in October 2022 to 210 in October 2023. Toyota remained the top make involved, with its count increasing slightly from 43 to 44. Ford saw a decrease in involvement from 42 to 26, while Honda's involvement also decreased from 25 to 16.

Top Vehicle Makes (210 vehicles)

1
TOYOTA44 (21%)
2.3%prior 43
2
FORD26 (12.4%)
-38.1%prior 42
3
CHEVROLET19 (9%)
0.0%prior 19
4
JEEP16 (7.6%)
77.8%prior 9
5
HONDA16 (7.6%)
-36.0%prior 25
6
NISSAN15 (7.1%)
-6.3%prior 16
7
HYUNDAI7 (3.3%)
40.0%prior 5
8
SUBARU6 (2.9%)
20.0%prior 5
9
GMC6 (2.9%)
10
KIA5 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

13 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (248 persons with recorded sex)

Male133 (53.6%)
-13.1%prior 153
Female115 (46.4%)
2.7%prior 112

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 35 mph speed zones decreased from 38 in October 2022 to 36 in October 2023. Crashes in 30 mph zones also saw a slight decrease from 32 to 31. Conversely, crashes in 55 mph zones increased from 8 to 11. The single fatal crash in October 2022 occurred in a 30 mph speed zone, with no fatal crashes reported in any speed zone in October 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: BARNSTABLE, MA
  • Total crash records analyzed: 112
  • Total persons involved: 263
  • Total vehicles involved: 210

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: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/barnstable/october-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

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Barnstable, MA Crash Report — October 2023 | ThatCarHitMe.com