Monthly Traffic Safety Analysis

42 CRASHES IN
FALMOUTH, MA
JANUARY 2022

All metrics benchmarked againstJanuary 2021

In January 2022, FALMOUTH experienced 42 total crashes, a decrease of 26.3% compared to the 57 crashes recorded in January 2021. The most notable shift was the absence of fatalities in the current period, down from one fatality in the prior year.

42

-26.3%was 57

Total Crash Events

0

-100.0%was 1

Persons Killed

14

-22.2%was 18

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in FALMOUTH showed a downward trend year-over-year, decreasing by 15 incidents from 57 in January 2021 to 42 in January 2022. Total injuries also decreased by 4, from 18 to 14, representing a 22.2% reduction.

2

Hit-and-Run Crashes — January 2022

4.8% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

1

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 10.0%

12

Motorists Injured

Prior: 17-29.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · 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 (14 crashes) in January 2021 to Saturday (9 crashes) in January 2022. The peak hour remained 2p in both periods, though the count at this hour decreased from 8 crashes in the prior period to 6 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities in January 2022, a decrease from one fatal crash and one fatality in January 2021. The number of serious injury crashes remained constant at 2 in both periods, while possible injury crashes decreased from 5 to 3.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes4.8%
0.0%prior 2
Minor Injury7minor injury crashes16.7%
0.0%prior 7
Possible Injury3possible injury crashes7.1%
-40.0%prior 5
No Injury28no injury crashes66.7%
-26.3%prior 38

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Inattention' saw a significant increase in count, rising from 2 crashes in January 2021 to 10 crashes in January 2022. Conversely, 'No improper driving' decreased by 8 crashes, from 18 to 10, and 'Failed to yield right of way' decreased by 5 crashes, from 8 to 3.

Officer-Reported Primary Contributing Cause

Inattention10 (23.8%)
No improper driving10 (23.8%)-44.4%prior 18
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner5 (11.9%)-16.7%prior 6
Exceeded authorized speed limit3 (7.1%)
Failed to yield right of way3 (7.1%)-62.5%prior 8
Driving too fast for conditions2 (4.8%)
Followed too closely2 (4.8%)
Distracted2 (4.8%)
Failure to keep in proper lane or running off road1 (2.4%)
Other improper action1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 40 in January 2021 to 28 in January 2022. Similarly, crashes under 'Daylight' conditions decreased from 33 to 24, and crashes on 'Dry' road surfaces decreased from 46 to 28. Notably, crashes on 'Ice' road surfaces increased from 1 to 4 year-over-year.

Weather

Clear28 (66.7%)
-30.0%prior 40
Snow4 (9.5%)
Cloudy3 (7.1%)
Rain2 (4.8%)
Clear/Unknown2 (4.8%)
Cloudy/Rain1 (2.4%)
Cloudy/Snow1 (2.4%)
Cloudy/Unknown1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Weather condition at time of crash

Lighting

Daylight24 (58.5%)
-27.3%prior 33
Dark - lighted roadway9 (22.0%)
-25.0%prior 12
Dark - roadway not lighted6 (14.6%)
-14.3%prior 7
Dusk2 (4.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Lighting condition field

Road Surface

Dry28 (66.7%)
-39.1%prior 46
Wet6 (14.3%)
20.0%prior 5
Ice4 (9.5%)
Snow4 (9.5%)
-20.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Road surface condition field

Vehicles & Demographics

The number of Toyota vehicles involved in crashes decreased from 22 in January 2021 to 13 in January 2022. For persons involved, the 65+ age group saw a decrease from 19 to 14, while the 26-34 and 55-64 age groups each increased by 2, from 15 to 17 and 14 to 17 respectively.

Top Vehicle Makes (70 vehicles)

1
TOYOTA13 (18.6%)
-40.9%prior 22
2
FORD10 (14.3%)
-9.1%prior 11
3
HONDA7 (10%)
16.7%prior 6
4
CHEVROLET5 (7.1%)
-44.4%prior 9
5
NISSAN4 (5.7%)
-20.0%prior 5
6
GMC4 (5.7%)
-33.3%prior 6
7
LEXUS3 (4.3%)
8
VOLKSWAGEN2 (2.9%)
9
BMW2 (2.9%)
10
JEEP2 (2.9%)
-71.4%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Vehicle unit records

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

Sex Distribution (80 persons with recorded sex)

Male47 (58.8%)
-20.3%prior 59
Female33 (41.3%)
-17.5%prior 40

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 35 mph speed zones decreased slightly from 16 in January 2021 to 15 in January 2022, with the single fatal crash in this zone from the prior period not recurring. Crashes in 40 mph zones saw a more substantial decrease, from 15 to 5 incidents year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · 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: 2022-01-01 through 2022-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-01-31 (31 days)
  • Geographic scope: FALMOUTH, MA
  • Total crash records analyzed: 42
  • Total persons involved: 86
  • Total vehicles involved: 70

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 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/falmouth/january-2022-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 2022 | ThatCarHitMe.com