ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FALMOUTH, MA · DECEMBER 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/falmouth/december-2023-report
Monthly Traffic Safety Analysis
30 CRASHES IN
FALMOUTH, MA
DECEMBER 2023
Falmouth experienced a significant decrease in total crashes in December 2023 compared to December 2022, with crashes falling by 48.28% from 58 to 30. Total injuries also saw a substantial reduction, decreasing by 62.5% from 16 to 6. The most notable shift was the absence of serious injuries (Severity A) in December 2023, compared to 3 serious injuries in the prior year.
30
▼ -48.3%was 58
Total Crash Events
0
Persons Killed
6
▼ -62.5%was 16
Persons Injured
3
▼ -25.0%was 4
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 · 2023-12-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for Falmouth shows a downward trend in December 2023 compared to the prior year. Total crashes decreased by 28, from 58 to 30, representing a 48.28% reduction. Similarly, total injuries decreased by 10, from 16 to 6, marking a 62.5% decline year-over-year.
3
Hit-and-Run Crashes — December 2023
▼ -25.0% vs prior (4)
The count of hit and run crashes decreased from 4 in December 2022 to 3 in December 2023. However, the hit and run rate increased from 6.9% of total crashes in the prior period to 10% in the current period.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
5
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 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 distribution of crashes shifted year-over-year, with the peak crash day moving from Thursday in December 2022 (12 crashes) to Friday in December 2023 (7 crashes). The peak hour also shifted from 4 PM (7 crashes) in the prior period to 5 PM (5 crashes) in the current period. Crashes on Mondays and Thursdays saw significant decreases, from 10 to 2 and 12 to 2 respectively.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes reported in either December 2023 or December 2022. Total injuries decreased from 16 in December 2022 to 6 in December 2023, a 62.5% reduction. Specifically, serious injuries (Severity A) were eliminated, dropping from 3 to 0, while minor injuries (Severity B) decreased from 7 to 3, and possible injuries (Severity C) decreased from 2 to 1.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
Several top contributing factors saw decreases in crash counts year-over-year. 'Inattention' decreased from 17 crashes to 8 crashes, while 'Followed too closely' decreased from 9 crashes to 5 crashes. 'No improper driving' crashes saw a substantial drop from 14 to 2, and 'Failed to yield right of way' decreased from 7 crashes to 5 crashes. However, 'Distracted' crashes increased from 1 to 2.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 32 in December 2022 to 24 in December 2023. Crashes on dry road surfaces decreased from 40 to 25, and those on wet surfaces decreased from 17 to 4. Crashes occurring during daylight hours decreased from 32 to 19, while crashes in dark-lighted roadway conditions decreased from 18 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 105 in December 2022 to 53 in December 2023. Toyota, which was the top make in the prior period with 22 vehicles, saw its involvement decrease to 3 vehicles, while Nissan became the top make in the current period with 6 vehicles, up from 4 in the prior period. The 0-15 age group was the only one to see an increase in persons involved, rising from 7 to 10, while all other age groups experienced decreases in person counts, such as the 35-44 age group decreasing from 22 to 11 persons.
Top Vehicle Makes (53 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Vehicle unit records
9 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (61 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 35 mph speed zone, which accounted for the most crashes in both periods, decreased from 26 in December 2022 to 12 in December 2023. Similarly, crashes in the 30 mph zone decreased from 12 to 6, and in the 40 mph zone from 6 to 3. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 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: 2023-12-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-12-01 through 2023-12-31 (31 days)
- Geographic scope: FALMOUTH, MA
- Total crash records analyzed: 30
- Total persons involved: 69
- Total vehicles involved: 53
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: December 2023." Published June 21, 2026. Reporting period: 2023-12-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/falmouth/december-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-12-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved