Monthly Traffic Safety Analysis

35 CRASHES IN
FALMOUTH, MA
JANUARY 2026

All metrics benchmarked againstJanuary 2025

Total crashes for January 2026 were 35, a notable decrease from 57 crashes in January 2025. This represents a 38.6% reduction in overall crash incidents year-over-year. The most significant shift observed is the complete absence of fatalities in January 2026, down from 2 fatalities in the prior year.

35

-38.6%was 57

Total Crash Events

0

-100.0%was 2

Persons Killed

12

-25.0%was 16

Persons Injured

2

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in Falmouth saw a substantial downward trend, decreasing by 38.6% from 57 crashes in January 2025 to 35 crashes in January 2026. This reduction indicates a significant improvement in traffic safety outcomes for the period.

2

Hit-and-Run Crashes — January 2026

0.0% vs prior (2)

The number of hit-and-run crashes remained constant at 2 incidents in both January 2025 and January 2026. However, due to the overall decrease in total crashes, the hit-and-run rate increased from 3.5% in the prior year to 5.7% in the current year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

12

Motorists Injured

Prior: 15-20.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted year-over-year; the peak day for crashes moved from Saturday with 11 incidents in January 2025 to Thursday with 7 incidents in January 2026. Similarly, the peak crash hour changed from 7 PM with 7 incidents in the prior year to 4 PM with 5 incidents in the current year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes were eliminated in January 2026, down from 2 fatal crashes (3.5% of total) in January 2025, resulting in a 0% fatal crash rate for the current period. Total injuries decreased from 16 to 12, with minor injury crashes (severity B) decreasing from 10 to 5, while serious injury crashes (severity A) increased from 0 to 2.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes5.7%
Minor Injury5minor injury crashes14.3%
-50.0%prior 10
Possible Injury4possible injury crashes11.4%
33.3%prior 3
No Injury24no injury crashes68.6%
-41.5%prior 41

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor "Inattention" saw a substantial decrease, dropping from 14 crashes in January 2025 to 3 crashes in January 2026. Conversely, "Failed to yield right of way" increased from 7 crashes in the prior year to 11 crashes in the current year, and "Followed too closely" increased from 5 crashes to 7 crashes.

Officer-Reported Primary Contributing Cause

Failed to yield right of way11 (31.4%)57.1%prior 7
Followed too closely7 (20%)40.0%prior 5
No improper driving7 (20%)-22.2%prior 9
Inattention3 (8.6%)-78.6%prior 14
Disregarded traffic signs, signals, road markings2 (5.7%)
Fatigued/asleep1 (2.9%)
Exceeded authorized speed limit1 (2.9%)
Made an improper turn1 (2.9%)
Driving too fast for conditions1 (2.9%)
Over-correcting/over-steering1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Clear" weather conditions decreased from 38 to 27, while crashes on "Dry" road surfaces decreased from 42 to 24 year-over-year. The number of crashes on "Ice" decreased from 5 in January 2025 to 1 in January 2026, and crashes on "Wet" road surfaces decreased from 6 to 5.

Weather

Clear27 (77.1%)
-28.9%prior 38
Snow3 (8.6%)
Cloudy2 (5.7%)
Blowing sand, snow/Snow1 (2.9%)
Rain/Cloudy1 (2.9%)
Snow/Blowing sand, snow1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash

Lighting

Daylight18 (51.4%)
-43.8%prior 32
Dark - lighted roadway10 (28.6%)
-33.3%prior 15
Dark - roadway not lighted5 (14.3%)
-16.7%prior 6
Dusk2 (5.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field

Road Surface

Dry24 (68.6%)
-42.9%prior 42
Wet5 (14.3%)
-16.7%prior 6
Snow4 (11.4%)
Ice1 (2.9%)
-80.0%prior 5
Slush1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 97 to 63 year-over-year. While Toyota remained the top make with 15 vehicles, up from 14, Ford saw a decrease from 12 to 7 vehicles, and Honda decreased from 12 to 4 vehicles. The age group 45-54 saw a significant reduction in involved persons, decreasing from 21 to 8.

Top Vehicle Makes (63 vehicles)

1
TOYOTA15 (23.8%)
7.1%prior 14
2
FORD7 (11.1%)
-41.7%prior 12
3
NISSAN5 (7.9%)
4
SUBARU5 (7.9%)
0.0%prior 5
5
MERCEDES-BENZ4 (6.3%)
6
CHEVROLET4 (6.3%)
-33.3%prior 6
7
HONDA4 (6.3%)
-66.7%prior 12
8
HYUNDAI3 (4.8%)
9
JEEP3 (4.8%)
-62.5%prior 8
10
AUDI2 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Vehicle unit records

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

Sex Distribution (74 persons with recorded sex)

Male42 (56.8%)
-23.6%prior 55
Female32 (43.2%)
-45.8%prior 59

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes at the 30 mph speed limit decreased from 16 to 6, and at 35 mph, they decreased from 18 to 12. There were no fatalities recorded in any speed zone in January 2026, a decrease from 1 fatality each at 35 mph and 40 mph in January 2025. Crashes in lower speed zones (5, 10, 25 mph) observed in the prior year were not present in the current data.

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

Data Coverage

  • Reporting period: 2026-01-01 through 2026-01-31 (31 days)
  • Geographic scope: FALMOUTH, MA
  • Total crash records analyzed: 35
  • Total persons involved: 95
  • Total vehicles involved: 63

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: January 2026." Published June 21, 2026. Reporting period: 2026-01-01 to 2026-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/falmouth/january-2026-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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Falmouth, MA Crash Report — January 2026 | ThatCarHitMe.com