ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MATTAPOISETT, MA · 2022
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/mattapoisett/2022-annual-report
Yearly Traffic Safety Analysis
144 CRASHES IN
MATTAPOISETT, MA
2022
In 2022, Mattapoisett recorded 144 vehicle crashes, a 13.4% increase from the 127 crashes reported in 2021. Despite the rise in total incidents, the most notable year-over-year shift was the decrease in fatalities, which dropped from two in the prior year to zero in the current year. The total number of injuries increased from 22 to 30 over the same period.
144
▲ 13.4%was 127
Total Crash Events
0
▼ -100.0%was 2
Persons Killed
30
▲ 36.4%was 22
Persons Injured
4
▼ -20.0%was 5
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. 7 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
Overall crash trends in Mattapoisett show an increase year-over-year. Total crashes rose by 13.4%, from 127 in 2021 to 144 in 2022. Similarly, the number of people injured in these incidents increased by 36.4%, from 22 to 30, while fatalities decreased from two to zero.
4
Hit-and-Run Crashes — 2022
▼ -20.0% vs prior (5)
The number of hit-and-run incidents decreased from five in 2021 to four in 2022. Correspondingly, the hit-and-run rate, which measures the percentage of total crashes that were hit-and-runs, also trended downward. The rate fell from 3.9% in the prior year to 2.8% in the current year.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
2
Cyclists Injured
28
Motorists Injured
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 timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Wednesday with 25 incidents, a change from Tuesday which saw the most crashes (28) in 2021. The peak hour also moved from 2 p.m. (13 crashes) in the prior year to 12 p.m. (13 crashes) in the current year. The months with the highest crash counts in 2022 were September and November, each with 18 incidents.
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 improved, with fatal crashes decreasing from one in 2021 to zero in 2022. The proportion of crashes resulting in any form of injury remained relatively stable, accounting for 16.0% of all crashes in 2022 compared to 15.0% in 2021. The count of serious injury crashes increased slightly from two to three, while crashes with no injuries rose from 98 to 114.
Outcome by Severity (Crash Events)
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 leading contributing factors cited in crashes remained consistent year-over-year, with 'No improper driving,' 'Inattention,' and 'Failed to yield right of way' as the top three in both 2021 and 2022. The count of crashes where 'No improper driving' was cited increased by 51.5%, from 33 to 50 incidents. Crashes involving 'Inattention' grew from 17 to 20, and those involving 'Failed to yield right of way' increased from 11 to 13.
Officer-Reported Primary Contributing Cause
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 showed some shifts between the two years. The percentage of crashes occurring in clear weather decreased from 77.2% in 2021 to 70.1% in 2022. Correspondingly, crashes on dry road surfaces declined as a share of the total, from 81.9% to 76.4%. Incidents in daylight conditions also saw a proportional decrease, from 70.1% of all crashes in the prior year to 63.9% in the current year, while the count of crashes on dark but lighted roadways increased from 18 to 32.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
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 three vehicle makes involved in crashes remained Ford, Toyota, and Honda in both years, though their order changed. In 2022, Toyota (29 vehicles) was the most frequent make, swapping places with Ford (23 vehicles), which was the top make in 2021 with 33 vehicles. Regarding the age of persons involved, the 65+ age group saw an increase in involvement from 40 individuals in 2021 to 50 in 2022. The number of persons in the 16-20 age group also rose from 36 to 40.
Top Vehicle Makes (216 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
21 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (233 persons with recorded sex)
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 became more frequent in several key speed zones year-over-year. Incidents in 65 mph zones increased from 20 to 28, and those in 35 mph zones rose from 20 to 26. A significant positive change was the absence of fatal crashes in 2022; in the prior year, one fatal crash occurred in a 65 mph zone. Crashes in 25 mph zones also saw a notable increase, rising from 11 in 2021 to 20 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: MATTAPOISETT, MA
- Total crash records analyzed: 144
- Total persons involved: 256
- Total vehicles involved: 216
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). "MATTAPOISETT, 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/mattapoisett/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved