Monthly Traffic Safety Analysis

80 CRASHES IN
BARNSTABLE, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

In February 2024, Barnstable experienced 80 crashes, a 5.9% decrease from the 85 crashes reported in February 2023. The most notable shift was a 100% reduction in total fatalities, dropping from 1 to 0, and a 31.8% decrease in total injuries, from 22 to 15.

80

-5.9%was 85

Total Crash Events

0

-100.0%was 1

Persons Killed

15

-31.8%was 22

Persons Injured

3

200.0%was 1

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. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends for February indicate a decrease year-over-year, with total crashes falling by 5.9% from 85 in February 2023 to 80 in February 2024. Total fatalities saw a 100% reduction, dropping from 1 to 0, while total injuries decreased by 31.8%, from 22 to 15.

3

Hit-and-Run Crashes — February 2024

200.0% vs prior (1)

Hit-and-run crashes increased from 1 in February 2023 to 3 in February 2024. Correspondingly, the hit-and-run rate rose from 1.2% to 3.8% year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

1

Pedestrians Injured

Prior: 0%

14

Motorists Injured

Prior: 22-36.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Thursday in both periods, with 16 crashes recorded in February 2024, matching February 2023's peak count. The peak hour remained 4 PM, but the number of crashes at this hour decreased from 13 in February 2023 to 8 in February 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

February 2024 saw no fatal crashes or fatalities, a decrease from one fatal crash and one fatality in February 2023. Total injuries decreased from 22 to 15 year-over-year. Minor injuries decreased from 11 to 9, and possible injuries decreased from 6 to 4, while serious injuries remained at 1 in both periods.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.3%
0.0%prior 1
Minor Injury9minor injury crashes11.3%
-18.2%prior 11
Possible Injury4possible injury crashes5%
-33.3%prior 6
No Injury64no injury crashes80%
-3.0%prior 66

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Most severe injury per crash record

Top Contributing Factors

The top contributing factors remained consistent, with 'No improper driving', 'Failed to yield right of way', and 'Inattention' being the most frequent in both periods, though their counts decreased. 'No improper driving' decreased from 19 to 14 crashes, 'Failed to yield right of way' decreased from 16 to 11 crashes, and 'Inattention' decreased from 12 to 10 crashes. Conversely, 'Driving too fast for conditions' increased from 1 to 5 crashes, and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' also increased from 1 to 5 crashes.

Officer-Reported Primary Contributing Cause

No improper driving14 (17.5%)-26.3%prior 19
Failed to yield right of way11 (13.8%)-31.3%prior 16
Inattention10 (12.5%)-16.7%prior 12
Followed too closely7 (8.8%)
Driving too fast for conditions5 (6.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner5 (6.3%)
Visibility obstructed4 (5%)
Glare4 (5%)
Disregarded traffic signs, signals, road markings4 (5%)
Made an improper turn2 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather decreased from 53 to 49, while those in 'Rain' increased from 1 to 4. Crashes on 'Dry' road surfaces decreased from 68 to 48, but crashes on 'Wet' surfaces increased from 9 to 14, and those on 'Snow' surfaces increased from 5 to 11. Crashes during 'Daylight' conditions decreased from 58 to 48.

Weather

Clear49 (62.0%)
-7.5%prior 53
Cloudy12 (15.2%)
20.0%prior 10
Rain4 (5.1%)
Snow4 (5.1%)
Cloudy/Snow2 (2.5%)
Snow/Blowing sand, snow2 (2.5%)
Snow/Sleet, hail (freezing rain or drizzle)1 (1.3%)
Clear/Cloudy1 (1.3%)
Clear/Unknown1 (1.3%)
Cloudy/Rain1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash

Lighting

Daylight48 (60.8%)
-17.2%prior 58
Dark - lighted roadway14 (17.7%)
-22.2%prior 18
Dark - roadway not lighted7 (8.9%)
40.0%prior 5
Dusk5 (6.3%)
Dark - unknown roadway lighting4 (5.1%)
Dawn1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field

Road Surface

Dry48 (60.8%)
-29.4%prior 68
Wet14 (17.7%)
55.6%prior 9
Snow11 (13.9%)
120.0%prior 5
Ice3 (3.8%)
Other1 (1.3%)
Slush1 (1.3%)
Water (standing, moving)1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 160 in February 2023 to 145 in February 2024. Toyota remained the top vehicle make involved, increasing from 21 to 29, while Honda decreased from 19 to 16. The age group 0-15 saw a notable increase in persons involved, from 7 to 41, while the 21-25 age group decreased from 23 to 12.

Top Vehicle Makes (145 vehicles)

1
TOYOTA29 (20%)
38.1%prior 21
2
FORD19 (13.1%)
0.0%prior 19
3
HONDA16 (11%)
-15.8%prior 19
4
JEEP7 (4.8%)
0.0%prior 7
5
NISSAN6 (4.1%)
20.0%prior 5
6
CHEVROLET6 (4.1%)
-64.7%prior 17
7
HYUNDAI5 (3.4%)
8
SUBARU5 (3.4%)
0.0%prior 5
9
DODGE5 (3.4%)
10
GMC5 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records

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

Sex Distribution (203 persons with recorded sex)

Male112 (55.2%)
23.1%prior 91
Female91 (44.8%)
5.8%prior 86

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones increased from 21 to 30, and in 45 mph zones increased from 8 to 16. Conversely, crashes in 35 mph zones decreased from 26 to 11. While February 2023 recorded one fatal crash in a 30 mph zone, February 2024 reported no fatal crashes across any speed zone.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-02-01 through 2024-02-29 (29 days)
  • Geographic scope: BARNSTABLE, MA
  • Total crash records analyzed: 80
  • Total persons involved: 216
  • Total vehicles involved: 145

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 2024." Published June 21, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/barnstable/february-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

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Barnstable, MA Crash Report — February 2024 | ThatCarHitMe.com