ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FALMOUTH, MA · FEBRUARY 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/falmouth/february-2024-report
Monthly Traffic Safety Analysis
50 CRASHES IN
FALMOUTH, MA
FEBRUARY 2024
In February 2024, Falmouth experienced 50 total crashes, marking a 31.6% increase compared to the 38 crashes reported in February 2023. Despite the rise in overall incidents, total injuries significantly decreased by 60%, from 15 to 6. A notable shift was the complete elimination of DUI-related crashes, which dropped from 8 in the prior period to 0 in the current period.
50
▲ 31.6%was 38
Total Crash Events
0
Persons Killed
6
▼ -60.0%was 15
Persons Injured
5
▲ 400.0%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. 6 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 incidents in Falmouth showed an upward trend, increasing by 31.6% from 38 crashes in February 2023 to 50 crashes in February 2024. Conversely, total injuries saw a substantial decline of 60%, falling from 15 to 6. Fatalities remained at zero in both periods, indicating stability in the most severe outcomes.
5
Hit-and-Run Crashes — February 2024
▲ 400.0% vs prior (1)
Hit-and-run crashes increased significantly from 1 in February 2023 to 5 in February 2024. Correspondingly, the hit-and-run rate rose from 2.6% to 10% of all crashes. This indicates an upward trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Motorists Killed
6
Motorists Injured
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 shifted from Thursday in February 2023 (7 crashes) to Wednesday in February 2024 (11 crashes). The peak crash hour remained consistently at 2 p.m. in both periods, with the number of crashes at this hour increasing from 5 to 7. This suggests a slight shift in the day-of-week pattern but consistent afternoon peak activity.
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
Fatal crashes remained at zero in both February 2023 and February 2024. Total injuries decreased from 15 to 6, a 60% reduction year-over-year. The proportion of crashes resulting in no injury increased from 68.4% in the prior period to 78% in the current period, indicating a decrease in injury severity across incidents.
Outcome by Severity (Crash Events)
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
Inattention remained the leading contributing factor, increasing from 14 crashes in February 2023 to 18 crashes in February 2024, a 28.6% rise in count. 'Followed too closely' saw a significant increase from 1 crash to 7 crashes, representing a 600% change in count and moving into the second top factor. Conversely, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased sharply from 7 crashes to 1 crash, an 85.7% reduction in count.
Officer-Reported Primary Contributing Cause
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 conditions increased from 27 to 34 year-over-year, remaining the dominant weather type. Crashes on snow-covered roads significantly increased from 1 to 11, while those on wet roads decreased from 10 to 5. Daylight crashes increased from 24 to 40, while crashes in dark-lighted roadway conditions decreased from 8 to 5.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field
Road Surface
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 increased by 25% from 68 in February 2023 to 85 in February 2024. Toyota remained the most common vehicle make involved, increasing from 14 to 21 counts. Chevrolet saw a notable rise in involvement from 3 to 12 vehicles, while Subaru's involvement decreased from 7 to 1, causing it to drop out of the top three makes.
Top Vehicle Makes (85 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (79 persons with recorded sex)
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 zones increased from 7 to 12, while those in 35 mph zones decreased from 18 to 10. Crashes in 10 mph zones also saw an increase, from 3 to 8. Fatalities remained at zero across all reported speed zones in both periods, indicating no change in the fatal crash rate per 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: FALMOUTH, MA
- Total crash records analyzed: 50
- Total persons involved: 92
- Total vehicles involved: 85
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). "FALMOUTH, 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/falmouth/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-02-01 – 2024-02-29
Generated: June 21, 2026 · All rights reserved