ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · ACUSHNET, MA · 2025
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/acushnet/2025-annual-report
Yearly Traffic Safety Analysis
152 CRASHES IN
ACUSHNET, MA
2025
In 2025, Acushnet recorded 152 total traffic crashes, a 32.2% increase from the 115 crashes documented in 2024. This period also saw one fatal crash resulting in one fatality, compared to zero in the prior year. A significant year-over-year shift was the 140% rise in crashes attributed to inattention, which increased from 10 incidents in 2024 to 24 in 2025.
152
▲ 32.2%was 115
Total Crash Events
1
Persons Killed
46
▲ 48.4%was 31
Persons Injured
9
▲ 125.0%was 4
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. 6 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for Acushnet indicates a rising trend year-over-year. Total crashes increased by 32.2%, from 115 in 2024 to 152 in 2025. This upward trend is also reflected in crash outcomes, with total injuries rising by 48.4% from 31 to 46, and one fatality recorded in 2025 compared to none in the previous year.
9
Hit-and-Run Crashes — 2025
▲ 125.0% vs prior (4)
Hit-and-run incidents increased significantly in 2025 compared to the previous year. The total number of hit-and-run crashes more than doubled, rising from 4 in 2024 to 9 in 2025, which represents a 125% increase in count. Consequently, the hit-and-run rate, or the percentage of all crashes that were hit-and-runs, trended upward from 3.5% to 5.9%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
44
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between 2024 and 2025. In 2025, the highest number of crashes occurred on Sundays, Mondays, and Wednesdays, each with 24 incidents, whereas in 2024, Monday was the sole peak day with 24 crashes. The peak time for crashes also shifted; in 2025, the hours of 12 p.m., 1 p.m., and 4 p.m. each saw the highest frequency with 11 crashes, a change from the single peak hour of 5 p.m. in 2024, which had 9 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity saw a notable change with the occurrence of one fatal crash in 2025, resulting in a fatal crash rate of 0.66 per 100 crashes, up from zero in 2024. Despite the new fatality, the overall proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) slightly decreased from 20.8% of total crashes in 2024 to 19.8% in 2025. The share of crashes with no reported injuries remained stable, at 76.3% in 2025 compared to 76.5% in the prior year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
A comparison of contributing factors reveals significant shifts in driver behavior between the two periods. Crashes attributed to 'Inattention' saw a 140% increase in count, rising from 10 in 2024 to 24 in 2025 and moving from the third to the second most cited factor. Conversely, incidents where drivers 'Failed to yield right of way' decreased by 50% in count, from 14 to 7, dropping from the second-ranked factor in 2024 to the fourth in 2025. Crashes where 'No improper driving' was noted increased from 41 to 60.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The conditions under which crashes occurred remained largely consistent year-over-year. In both 2025 and 2024, the majority of crashes happened in daylight (58.6% and 57.4% of crashes, respectively) and on dry roads (77.6% and 75.7%, respectively). There was a slight increase in the proportion of crashes occurring in clear weather, which accounted for 77.0% of incidents in 2025, up from 69.6% in 2024. Correspondingly, the share of crashes on non-dry road surfaces saw a small decrease from 22.6% to 18.4%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent, with Toyota, Ford, and Chevrolet being the most frequent in both 2024 and 2025. An analysis of the age distribution of persons involved in crashes shows a shift toward young adult and middle-aged groups. The proportion of individuals in the 16-20 age group increased from 12.3% of the total in 2024 to 15.0% in 2025, while the 35-44 age group's representation also grew from 12.3% to 15.7%.
Top Vehicle Makes (239 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
24 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (274 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones shifted between 2024 and 2025. The proportion of crashes in 25 mph zones increased from 15.0% to 22.8% of all crashes with a recorded speed limit. Conversely, the share of crashes occurring in 40 mph zones, while still the most common location, decreased from 38.3% to 32.4%. The single fatal crash recorded in 2025 occurred in a 35 mph zone, where no fatalities were reported in the prior year.
Fatal crashes by zone: 35 mph: 1 of 29 (3.448%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: ACUSHNET, MA
- Total crash records analyzed: 152
- Total persons involved: 298
- Total vehicles involved: 239
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). "ACUSHNET, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/acushnet/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved