ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · OXFORD, 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/oxford/2025-annual-report
Yearly Traffic Safety Analysis
284 CRASHES IN
OXFORD, MA
2025
In 2025, Oxford recorded 284 total traffic crashes, a 37.9% decrease from the 457 crashes reported in 2024. Despite the overall drop in collisions, 2025 saw two fatal crashes resulting in two deaths, whereas no fatalities were recorded in the prior year. Total injuries also decreased from 133 in 2024 to 80 in 2025.
284
▼ -37.9%was 457
Total Crash Events
2
Persons Killed
80
▼ -39.8%was 133
Persons Injured
20
▼ -20.0%was 25
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 4 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
The overall trend in traffic crashes in Oxford shows a significant year-over-year decrease. Total collisions dropped by 37.9%, from 457 in 2024 to 284 in 2025. Similarly, the number of people injured in these incidents declined by 39.8%, from 133 to 80. However, this period also saw the emergence of two traffic fatalities, compared to none in the previous year.
20
Hit-and-Run Crashes — 2025
▼ -20.0% vs prior (25)
The total number of hit-and-run incidents decreased from 25 in 2024 to 20 in 2025. However, due to the larger overall reduction in total crashes, the proportion of crashes that were hit-and-runs increased. The hit-and-run rate rose from 5.5% of all crashes in 2024 to 7.0% in 2025.
Vulnerable Road User Casualties
1
Pedestrians Killed
1
Motorists Killed
0
Pedestrians Injured
80
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
Temporal analysis shows that Friday remained the peak day for crashes in both 2024 and 2025, though the number of incidents on Friday fell from 82 to 51. The peak hour for crashes shifted from 3 p.m. in 2024, which saw 41 crashes, to 5 p.m. in 2025 with 26 crashes. Overall, crash volumes decreased across most days of the week and hours of the day.
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
While total crashes decreased, the severity profile shifted with the introduction of two fatal crashes in 2025, compared to none in 2024, resulting in a fatal crash rate of 0.7%. The proportion of crashes involving minor injuries increased from 14.0% in 2024 to 16.2% in 2025. The share of crashes resulting in serious injuries remained stable at 1.1% for both years.
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
The leading contributing factors for crashes saw a shift in ranking between the two periods. In 2025, 'Inattention' became the top factor with 61 crashes, despite its count decreasing by 18.7% from 75 crashes in 2024. Crashes attributed to 'No improper driving' saw a 45.1% reduction in count, from 91 to 50, moving it from the top spot to second place. Notably, crashes from 'Failed to yield right of way' dropped significantly, with the count falling by 65.6% from 64 to 22.
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
Crashes in both periods predominantly occurred in clear weather and on dry roads during daylight hours. The proportion of crashes happening during daylight was nearly identical, at 69.0% in 2025 compared to 69.1% in 2024. The share of crashes on dry road surfaces also remained stable, accounting for 79.6% of incidents in 2025 versus 78.8% in 2024. There was a slight increase in the proportion of crashes occurring in clear weather, which rose from 69.6% to 73.6% 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 involved in crashes showed a consistent pattern, with Toyota, Ford, and Chevrolet being the top three most frequently involved makes in both 2025 and 2024. The age distribution of persons involved in crashes also remained stable between the two periods. The proportional representation of all age groups, from '16-20' to '65+', saw minimal change year-over-year.
Top Vehicle Makes (541 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
68 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (595 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
While the total number of crashes decreased across most speed zones, the distribution of crashes remained similar, with 35 mph and 65 mph zones seeing the highest volumes in both years. Crashes in 35 mph zones dropped from 132 to 95, and those in 65 mph zones fell from 106 to 81. A significant change was the occurrence of two fatal crashes in 2025—one in a 30 mph zone and one in a 35 mph zone—whereas 2024 had no fatal crashes reported in any speed zone.
Fatal crashes by zone: 30 mph: 1 of 35 (2.857%) · 35 mph: 1 of 95 (1.053%)
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: OXFORD, MA
- Total crash records analyzed: 284
- Total persons involved: 665
- Total vehicles involved: 541
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). "OXFORD, 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/oxford/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