ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · MATTAPOISETT, MA · 2024
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/2024-annual-report
Yearly Traffic Safety Analysis
115 CRASHES IN
MATTAPOISETT, MA
2024
In 2024, Mattapoisett recorded 115 total vehicle crashes, a 3.4% decrease from the 119 crashes reported in 2023. While the overall crash volume saw a slight decline, the most significant change was in crash severity. The city experienced one fatal crash resulting in one death in 2024, compared to zero fatalities in the prior year, and total injuries increased by 56.5% from 23 to 36.
115
▼ -3.4%was 119
Total Crash Events
1
Persons Killed
36
▲ 56.5%was 23
Persons Injured
4
▼ -50.0%was 8
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in traffic collisions in Mattapoisett shows a slight year-over-year decrease. Total crashes fell by 3.4%, from 119 incidents in 2023 to 115 in 2024. Despite this modest drop in total incidents, the number of people injured rose from 23 to 36.
4
Hit-and-Run Crashes — 2024
▼ -50.0% vs prior (8)
The incidence of hit-and-run crashes decreased significantly in 2024 compared to the previous year. The total number of hit-and-run incidents was halved, falling from 8 in 2023 to 4 in 2024. This represents a downward trend in the hit-and-run rate, which dropped from 6.7% of all crashes in 2023 to 3.5% in 2024.
Vulnerable Road User Casualties
1
Motorists Killed
36
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. In 2024, the peak day for crashes was Friday with 22 incidents, a change from Thursday (23 incidents) in the prior year. Similarly, the peak hour for collisions moved from the morning commute at 7 a.m. in 2023 (12 crashes) to the afternoon at 3 p.m. in 2024 (12 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased in 2024 compared to the previous year, with the city recording one fatal crash after having none in 2023. The proportion of crashes resulting in any level of injury rose from 16.8% of all crashes in 2023 to 20.0% in 2024. Correspondingly, the share of non-injury crashes decreased from 77.3% to 74.8% of the total.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' remained the most common finding in both years (40 incidents in 2024 vs. 41 in 2023), the ranking of attributed driver actions shifted. Crashes attributed to 'Inattention' were halved, falling from 14 incidents in 2023 to 7 in 2024. Conversely, crashes involving 'Failed to yield right of way' increased from 14 to 16 incidents, becoming the leading attributable factor in 2024.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both years occurred in clear weather on dry roads, with the proportion of crashes on dry surfaces remaining stable at around 77%. There was a notable shift in lighting conditions, with a higher proportion of crashes occurring during daylight hours in 2024 (69.6%) compared to 2023 (59.7%). Consequently, the share of crashes in dark conditions (both lighted and unlighted roadways) decreased from 32.8% to 22.6%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
Toyota (28 vehicles) and Honda (26 vehicles) remained the top two most frequently involved vehicle makes in 2024, both seeing an increase in counts from the prior year. The demographic profile of persons involved in crashes also shifted, with a notable increase in the involvement of younger and older individuals. The number of persons in the 16-20 age group rose from 24 to 38, while those aged 65 and older increased from 33 to 44.
Top Vehicle Makes (180 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
15 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (214 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones changed year-over-year, with a noticeable shift towards higher speed limit areas. In 2024, there was an increase in crashes in 50 mph zones (from 13 to 20) and 45 mph zones (from 11 to 16). This was contrasted by a decrease in incidents in 35 mph zones (from 24 to 11) and 25 mph zones (from 17 to 9). The single fatal crash recorded in 2024 occurred in a 50 mph zone.
Fatal crashes by zone: 50 mph: 1 of 20 (5%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: MATTAPOISETT, MA
- Total crash records analyzed: 115
- Total persons involved: 229
- Total vehicles involved: 180
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/mattapoisett/2024-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved