ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ABINGTON, 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/abington/2025-annual-report
Yearly Traffic Safety Analysis
405 CRASHES IN
ABINGTON, MA
2025
In 2025, Abington recorded 405 total crashes, an 11.6% decrease from the 458 crashes reported in 2024. This downward trend was accompanied by a significant reduction in both fatalities, which dropped from two to one, and total injuries, which fell by 27.9% from 201 to 145 year-over-year. The most notable factor change was a 38.5% increase in the count of crashes attributed to 'Inattention'.
405
▼ -11.6%was 458
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
145
▼ -27.9%was 201
Persons Injured
25
▼ -41.9%was 43
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. 12 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 Abington indicates a notable year-over-year decrease in traffic incidents. Total crashes fell by 11.6%, from 458 in 2024 to 405 in 2025. Similarly, the number of people injured in these crashes decreased by 27.9% during the same period, while fatalities were reduced from two to one.
25
Hit-and-Run Crashes — 2025
▼ -41.9% vs prior (43)
There was a significant year-over-year decrease in hit-and-run incidents in Abington. The total number of hit-and-run crashes fell by 41.9%, from 43 in 2024 to 25 in 2025. Consequently, the hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also declined from 9.4% to 6.2%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
2
Pedestrians Injured
1
Cyclists Injured
142
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 timing of crashes in Abington showed some shifts between 2024 and 2025. While the peak hour for collisions remained consistent at 5 PM in both years (42 crashes in 2025 vs. 44 in 2024), the most frequent day for crashes changed. In 2025, Saturday was the peak day with 63 crashes, a shift from Thursday, which was the peak day in 2024 with 77 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 in Abington improved from 2024 to 2025. The number of fatal crashes was reduced from two to one, causing the fatal crash rate to decrease from 0.44% to 0.25%. The proportion of crashes resulting in any injury also declined, from 30.6% in 2024 to 26.4% in 2025. This was driven by a drop in the share of both serious injuries (from 3.7% to 2.0%) and possible injuries (from 8.1% to 6.4%).
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
'Failed to yield right of way' remained the leading contributing factor in both periods, though its count decreased by 14.4% from 132 incidents in 2024 to 113 in 2025. A notable shift occurred with 'Inattention,' which saw its count increase by 38.5% from 39 to 54, moving it from the fourth to the second most-cited factor year-over-year. Conversely, crashes attributed to 'Followed too closely' decreased by 33.8%, with the count falling from 68 in 2024 to 45 in 2025.
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 proportion of crashes occurring in daylight conditions remained stable, accounting for 65.7% of incidents in 2025 compared to 68.8% in 2024. The share of crashes on dry roads was also consistent, at 77.5% in 2025 versus 80.3% in the prior year. However, there was a notable increase in crashes occurring on snowy roads, with the count rising from 6 in 2024 to 20 in 2025.
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
Toyota and Ford remained the top two vehicle makes involved in crashes in both 2024 and 2025, although the number of vehicles from both makes decreased year-over-year. Honda (85 vehicles) moved into the third position in 2025, replacing Chevrolet from the prior year's top three. Among persons involved in crashes, the 26-34 age group was the most numerous in both periods, with its count decreasing from 182 to 175. The 35-44 age group remained the second-largest, while the 65+ age group (104 persons) replaced the 45-54 age group as the third-largest demographic in 2025.
Top Vehicle Makes (761 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
74 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (890 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
Crashes remained most frequent in 30 mph and 35 mph speed zones in both years, though their order switched. In 2025, the 35 mph zone was the site of the most crashes (108), whereas the 30 mph zone was most common in 2024 (124 crashes). The single fatal crash in 2025 occurred in a 35 mph zone. This compares to 2024, which saw one fatal crash in a 35 mph zone and another in a 25 mph zone.
Fatal crashes by zone: 35 mph: 1 of 108 (0.926%)
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: ABINGTON, MA
- Total crash records analyzed: 405
- Total persons involved: 967
- Total vehicles involved: 761
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). "ABINGTON, 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/abington/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