Yearly Traffic Safety Analysis

260 CRASHES IN
MASHPEE, MA
2022

All metrics benchmarked against2021

In 2022, Mashpee recorded 260 total vehicle crashes, an 11.9% decrease from the 295 crashes reported in 2021. This year-over-year improvement was also reflected in outcomes, with total injuries falling from 110 to 73 and fatalities dropping from one to zero. The most notable change was the reduction in crash severity, including a 75% decrease in the count of serious injury crashes.

260

-11.9%was 295

Total Crash Events

0

-100.0%was 1

Persons Killed

73

-33.6%was 110

Persons Injured

0

-100.0%was 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. 9 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 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Mashpee showed a decreasing trend year-over-year. Total crashes fell by 11.9%, from 295 in 2021 to 260 in 2022. This downward trend extended to personal harm, with total injuries decreasing by 33.6% and fatalities being eliminated entirely, dropping from one in the prior year to zero in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 1100.0%

4

Cyclists Injured

Prior: 1300.0%

67

Motorists Injured

Prior: 108-38.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained broadly consistent year-over-year, though with a reduction in volume. Friday continued to be the peak day for crashes in both 2022 (46 crashes) and 2021 (62 crashes). The 3 p.m. hour also remained a primary peak time, although its crash count dropped from 34 to 26. In 2022, the 11 a.m. hour saw an increase in crashes to 26 incidents, matching the 3 p.m. hour's total, a shift from the 19 crashes recorded at 11 a.m. in the prior year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity significantly decreased in 2022 compared to the previous year. Fatal crashes were eliminated, dropping from one in 2021 to zero in 2022. The count of serious injury crashes also fell sharply, from 12 in 2021 to 3 in 2022, with their share of total crashes decreasing from 4.1% to 1.2%. Consequently, the proportion of crashes with no reported injuries increased from 68.8% to 71.9% of all incidents.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes1.2%
-75.0%prior 12
Minor Injury40minor injury crashes15.4%
-25.9%prior 54
Possible Injury21possible injury crashes8.1%
10.5%prior 19
No Injury187no injury crashes71.9%
-7.9%prior 203

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors to crashes remained consistent, with 'Inattention' leading in both periods. The count for inattention-related crashes was unchanged at 76, causing its share of all crashes to grow from 25.8% in 2021 to 29.2% in 2022. Crashes attributed to 'Failed to yield right of way' saw a notable reduction in count, falling 26.8% from 41 in 2021 to 30 in 2022. Similarly, the count for crashes involving 'Followed too closely' decreased from 43 to 40 incidents.

Officer-Reported Primary Contributing Cause

Inattention76 (29.2%)0.0%prior 76
Followed too closely40 (15.4%)-7.0%prior 43
Failed to yield right of way30 (11.5%)-26.8%prior 41
No improper driving26 (10%)-25.7%prior 35
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner14 (5.4%)-22.2%prior 18
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway11 (4.2%)22.2%prior 9
Distracted9 (3.5%)28.6%prior 7
Disregarded traffic signs, signals, road markings6 (2.3%)
Failure to keep in proper lane or running off road6 (2.3%)-40.0%prior 10
Other improper action6 (2.3%)-25.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The environmental conditions during crashes remained remarkably stable year-over-year. In both 2022 and 2021, approximately 74% of crashes occurred in daylight, and about 81% happened on dry road surfaces. The proportion of crashes in clear weather was also nearly identical, at 67.7% in 2022 versus 67.8% in 2021. The data does not indicate a significant shift in crashes occurring during adverse weather, lighting, or road conditions.

Weather

Clear176 (68.2%)
-12.0%prior 200
Cloudy48 (18.6%)
-11.1%prior 54
Rain11 (4.3%)
-38.9%prior 18
Cloudy/Rain11 (4.3%)
83.3%prior 6
Rain/Cloudy4 (1.6%)
Clear/Cloudy2 (0.8%)
Snow/Blowing sand, snow2 (0.8%)
Sleet, hail (freezing rain or drizzle)/Rain1 (0.4%)
Sleet, hail (freezing rain or drizzle)/Severe crosswinds1 (0.4%)
Cloudy/Severe crosswinds1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight191 (73.7%)
-12.8%prior 219
Dark - lighted roadway33 (12.7%)
-13.2%prior 38
Dark - roadway not lighted23 (8.9%)
0.0%prior 23
Dusk11 (4.2%)
37.5%prior 8
Dark - unknown roadway lighting1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry212 (81.9%)
-11.3%prior 239
Wet40 (15.4%)
-7.0%prior 43
Snow5 (1.9%)
-37.5%prior 8
Ice1 (0.4%)
Slush1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top five vehicle makes involved in crashes remained unchanged between 2021 and 2022, with Toyota, Ford, and Honda leading in both years, although the number of vehicles from each of these top makes decreased. Regarding persons involved in crashes, the share of those in the 26-34 age group increased from 13.2% to 16.2% year-over-year. Conversely, the representation of the 16-20 age group decreased from 12.6% of all persons in 2021 to 10.1% in 2022.

Top Vehicle Makes (462 vehicles)

1
TOYOTA67 (14.5%)
-13.0%prior 77
2
FORD54 (11.7%)
-8.5%prior 59
3
HONDA48 (10.4%)
-7.7%prior 52
4
CHEVROLET34 (7.4%)
-33.3%prior 51
5
NISSAN32 (6.9%)
-22.0%prior 41
6
SUBARU24 (5.2%)
84.6%prior 13
7
JEEP22 (4.8%)
-29.0%prior 31
8
GMC18 (3.9%)
-41.9%prior 31
9
MERCEDES-BENZ14 (3%)
75.0%prior 8
10
MAZDA12 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (538 persons with recorded sex)

Male312 (58.0%)
-5.7%prior 331
Female226 (42.0%)
-26.1%prior 306

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes decreased across most higher speed zones in 2022 compared to 2021. Collisions in 50 mph zones fell from 62 to 51, and those in 40 mph zones dropped from 66 to 59. The single fatal crash in 2021 occurred in a 50 mph zone; no fatal crashes were recorded in any speed zone in 2022. In contrast, crashes in 25 mph zones saw an increase, rising from 29 incidents in 2021 to 35 in 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: MASHPEE, MA
  • Total crash records analyzed: 260
  • Total persons involved: 573
  • Total vehicles involved: 462

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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/mashpee/2022-annual-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 — 2022 | ThatCarHitMe.com