ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ABINGTON, MA · FEBRUARY 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/february-2025-report
Monthly Traffic Safety Analysis
30 CRASHES IN
ABINGTON, MA
FEBRUARY 2025
Total crashes in February 2025 remained stable at 30, matching the 30 crashes recorded in February 2024. Despite the consistent crash count, total injuries decreased by 28.6%, from 14 in the prior period to 10 in the current period, representing the most notable year-over-year shift.
30
Total Crash Events
0
Persons Killed
10
▼ -28.6%was 14
Persons Injured
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash numbers remained stable year-over-year, with 30 crashes reported in both February 2025 and February 2024. However, total injuries decreased by 28.6%, falling from 14 in the prior period to 10 in the current period. Fatalities remained at zero in both periods.
2
Hit-and-Run Crashes — February 2025
▼ 0.0% vs prior (2)
The number of hit-and-run crashes remained constant at 2 in both February 2025 and February 2024. Consequently, the hit-and-run crash rate also remained stable at 6.7% for both periods. This indicates no change in the trend for hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Motorists Killed
10
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Wednesday in February 2024 (8 crashes) to Saturday in February 2025 (7 crashes). Similarly, the peak crash hour moved from 5 PM in the prior period (4 crashes) to 11 AM in the current period (5 crashes). This indicates a shift in the most frequent crash times and days between the two periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Total injuries decreased by 28.6%, from 14 in February 2024 to 10 in February 2025. The current period saw one serious injury crash (3.3% of crashes), which was not present in the prior period. Minor injury crashes decreased from 7 (23.3%) to 5 (16.7%), while possible injury crashes decreased from 3 (10%) to 1 (3.3%). Both periods reported zero fatalities and zero fatal crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record
Top Contributing Factors
"Failed to yield right of way" remained the most cited contributing factor, though its count decreased from 10 in February 2024 to 7 in February 2025. Crashes attributed to "Inattention" doubled from 2 in the prior period to 4 in the current period, and "Other improper action" increased from 2 to 3 crashes. Conversely, incidents of "No improper driving" significantly decreased from 7 in the prior period to 1 in the current period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Clear" weather conditions increased from 20 in February 2024 to 23 in February 2025. The current period recorded 3 crashes in "Snow" conditions and 2 in "Ice" conditions, neither of which were present in the prior period's data. Conversely, crashes on "Dry" road surfaces decreased from 25 to 18, while "Wet" road surface crashes increased from 5 to 7.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased slightly from 56 in February 2024 to 54 in February 2025. Toyota, which was the top vehicle make involved in the prior period with 10 vehicles, saw its count decrease to 6 in the current period, falling behind Ford which led with 8 vehicles. The age group 26-34 saw a substantial increase in persons involved, rising from 7 in the prior period to 15 in the current period, while the 35-44 age group decreased from 16 to 8.
Top Vehicle Makes (54 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records
6 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (63 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 35 mph speed limit zone increased from 7 in February 2024 to 10 in February 2025. Conversely, crashes in the 40 mph zone decreased from 4 to 1, and in the 45 mph zone from 8 to 5. Both periods reported zero fatalities across all speed limit zones.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-02-01 through 2025-02-28 (28 days)
- Geographic scope: ABINGTON, MA
- Total crash records analyzed: 30
- Total persons involved: 68
- Total vehicles involved: 54
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: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/abington/february-2025-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: 2025-02-01 – 2025-02-28
Generated: June 21, 2026 · All rights reserved