ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ORANGE, 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/orange/2025-annual-report
Yearly Traffic Safety Analysis
99 CRASHES IN
ORANGE, MA
2025
In Orange, total traffic crashes increased by 160.5%, from 38 incidents in 2024 to 99 in 2025. This rise was accompanied by a significant increase in injuries from 9 to 34. The most notable shift was the occurrence of one fatal crash in 2025, whereas none were recorded in the prior year.
99
▲ 160.5%was 38
Total Crash Events
1
Persons Killed
34
▲ 277.8%was 9
Persons Injured
1
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. 1 crash with unreported severity is 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
Traffic safety trends in Orange show a significant year-over-year increase in crash volume. Total crashes rose from 38 in 2024 to 99 in 2025, a 160.5% increase. This upward trend is also reflected in crash outcomes, with total injuries climbing from 9 to 34 and fatalities increasing from zero to one.
1
Hit-and-Run Crashes — 2025
▼ 0.0% vs prior (1)
The total number of hit-and-run crashes was stable, with one incident recorded in 2025 and one in 2024. However, due to the large increase in overall crash volume, the hit-and-run rate as a percentage of all crashes decreased from 2.6% in 2024 to 1.0% in 2025.
Vulnerable Road User Casualties
0
Cyclists Killed
1
Motorists Killed
1
Cyclists Injured
33
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 peak day for crashes shifted from Thursday (8 crashes) in 2024 to Wednesday (21 crashes) in 2025. The 3 p.m. hour remained the single busiest time for crashes in both periods, but the crash count during this hour more than doubled from 7 to 15. Crash activity during evening hours after 6 p.m. also saw a substantial increase in 2025 compared to the previous year.
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 worsened year-over-year, with one fatal crash recorded in 2025, accounting for 1% of all incidents, compared to zero fatal crashes in 2024. The proportion of crashes involving minor injuries nearly doubled, increasing from 10.5% of crashes in 2024 to 20.2% in 2025. Consequently, the share of crashes with no reported injuries fell from 78.9% to 72.7%.
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
Inattention remained the top contributing factor in both years, with the number of related crashes tripling from 11 in 2024 to 33 in 2025. While the count of crashes attributed to 'Followed too closely' decreased from 7 to 5, its share of all incidents dropped from 18.4% in 2024 to 5.1% in 2025. Crashes involving 'Driving too fast for conditions' and 'erratic/reckless driving' both increased from 2 incidents in 2024 to 5 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
While crashes on dry roads were most common in both periods, their share of the total decreased from 86.8% in 2024 to 77.8% in 2025. There was a corresponding increase in the number and proportion of crashes occurring on wet roads, which rose from 1 incident (2.6% of total) in 2024 to 12 incidents (12.1% of total) in 2025. Similarly, the proportion of crashes in clear weather decreased from 63.2% to 56.6% year-over-year.
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 makes of vehicles most frequently involved in crashes shifted between the two periods. Subaru involvement increased from 11 vehicles in 2024 to 22 in 2025, making it the top-ranked make, while Ford involvement grew from 4 to 19 vehicles. Among persons involved in crashes, all age groups saw an increase in counts, with the 16-20 age group experiencing a fourfold rise from 8 individuals in 2024 to 32 in 2025.
Top Vehicle Makes (165 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
11 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (191 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 increased across most posted speed zones, with the largest absolute growth in 30 mph zones (from 8 to 24 crashes) and 40 mph zones (from 5 to 15 crashes). The city's only fatal crash in 2025 occurred in a 40 mph zone. In the prior year, no fatal crashes were recorded in any speed zone.
Fatal crashes by zone: 40 mph: 1 of 15 (6.667%)
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: ORANGE, MA
- Total crash records analyzed: 99
- Total persons involved: 203
- Total vehicles involved: 165
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). "ORANGE, 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/orange/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