Monthly Traffic Safety Analysis

17 CRASHES IN
MASHPEE, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

In January 2023, MASHPEE recorded 17 crashes, an increase of 13.33% compared to the 15 crashes reported in January 2022. Total injuries rose by 66.67%, from 3 in January 2022 to 5 in January 2023, representing the most notable year-over-year shift.

17

13.3%was 15

Total Crash Events

0

Persons Killed

5

66.7%was 3

Persons Injured

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in MASHPEE increased year-over-year, with 17 crashes in January 2023 compared to 15 in January 2022, representing a 13.33% rise. Total injuries also saw a substantial increase of 66.67%, from 3 to 5.

1

Hit-and-Run Crashes — January 2023

5.9% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 366.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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 Saturday with 6 crashes in January 2022 to Tuesday with 4 crashes in January 2023. While both periods had a peak hour with 3 crashes, the specific peak hour shifted from 8p in January 2022 to 7p in January 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities in either January 2023 or January 2022. The proportion of minor injury crashes increased from 20% (3 crashes) in January 2022 to 23.5% (4 crashes) in January 2023. Additionally, possible injury crashes, which were absent in January 2022, accounted for 5.9% (1 crash) of incidents in January 2023, while no-injury crashes decreased from 80% to 64.7% of the total.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes23.5%
33.3%prior 3
Possible Injury1possible injury crashes5.9%
No Injury11no injury crashes64.7%
-8.3%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor shifted from 'Inattention' with 5 crashes in January 2022 to 'No improper driving' with 4 crashes in January 2023. Crashes attributed to 'No improper driving' increased by 3 (from 1 to 4), while 'Inattention' crashes decreased by 4 (from 5 to 1). 'Followed too closely' crashes increased from 2 to 3, and 'Failed to yield right of way' crashes increased from 1 to 2.

Officer-Reported Primary Contributing Cause

No improper driving4 (23.5%)
Followed too closely3 (17.6%)
Failed to yield right of way2 (11.8%)
Distracted2 (11.8%)
Driving too fast for conditions2 (11.8%)
Inattention1 (5.9%)-80.0%prior 5
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (5.9%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather decreased by 5, from 7 in January 2022 to 2 in January 2023, while crashes in rainy conditions increased by 3, from 1 to 4. Incidents on wet road surfaces rose by 3, from 7 to 10, and those on dry surfaces decreased by 2, from 6 to 4. Daylight crashes saw a slight increase of 1, from 8 to 9, while crashes in dark-lighted roadway conditions remained constant at 4.

Weather

Cloudy4 (25.0%)
Rain4 (25.0%)
Clear2 (12.5%)
-71.4%prior 7
Sleet, hail (freezing rain or drizzle)1 (6.3%)
Sleet, hail (freezing rain or drizzle)/Cloudy1 (6.3%)
Snow1 (6.3%)
Snow/Sleet, hail (freezing rain or drizzle)1 (6.3%)
Cloudy/Clear1 (6.3%)
Cloudy/Rain1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Weather condition at time of crash

Lighting

Daylight9 (56.3%)
12.5%prior 8
Dark - lighted roadway4 (25.0%)
Dark - roadway not lighted2 (12.5%)
Dusk1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Lighting condition field

Road Surface

Wet10 (62.5%)
42.9%prior 7
Dry4 (25.0%)
-33.3%prior 6
Slush1 (6.3%)
Snow1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (29 vehicles)

1
TOYOTA6 (20.7%)
2
CHEVROLET4 (13.8%)
3
NISSAN4 (13.8%)
4
FORD4 (13.8%)
5
GMC3 (10.3%)
6
HONDA2 (6.9%)
7
VOLKSWAGEN2 (6.9%)
8
HYUNDAI1 (3.4%)
9
AUDI1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Vehicle unit records

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

Sex Distribution (32 persons with recorded sex)

Female16 (50.0%)
33.3%prior 12
Male16 (50.0%)
-33.3%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 50 mph speed zones increased from 3 in January 2022 to 5 in January 2023, and crashes in 45 mph zones also increased from 2 to 4. Conversely, crashes in 40 mph zones decreased from 4 to 3. There were no fatal crashes reported across any speed zones in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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: 2023-01-01 through 2023-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-01-31 (31 days)
  • Geographic scope: MASHPEE, MA
  • Total crash records analyzed: 17
  • Total persons involved: 34
  • Total vehicles involved: 29

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). "MASHPEE, MA Crash Intelligence Report: January 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/mashpee/january-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

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Mashpee, MA Crash Report — January 2023 | ThatCarHitMe.com