ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · OXFORD, MA · JUNE 2022
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/june-2022-report
Monthly Traffic Safety Analysis
32 CRASHES IN
OXFORD, MA
JUNE 2022
In June 2022, Oxford experienced 32 crashes, a slight decrease from the 33 crashes reported in June 2021, representing a 3.03% reduction. Despite the decrease in total crashes, the number of total injuries significantly increased by 150%, rising from 6 injuries in June 2021 to 15 injuries in June 2022, with the emergence of one serious injury.
32
▼ -3.0%was 33
Total Crash Events
0
Persons Killed
15
▲ 150.0%was 6
Persons Injured
1
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 · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes remained relatively stable year-over-year, decreasing slightly from 33 crashes in June 2021 to 32 crashes in June 2022. However, total fatalities remained at 0 in both periods, while total injuries saw a substantial increase, rising from 6 in June 2021 to 15 in June 2022.
1
Hit-and-Run Crashes — June 2022
3.1% hit-and-run rate this period vs 0.0% prior. Prior period: 0.
Vulnerable Road User Casualties
0
Motorists Killed
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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 with 7 crashes in June 2021 to Tuesday with 7 crashes in June 2022. Similarly, the peak hour for crashes moved from 12p with 5 crashes in June 2021 to 3p with 5 crashes in June 2022, indicating a shift in the timing of crash occurrences.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution changed notably, with serious injuries (Code A) appearing in June 2022 with 1 crash, compared to 0 in June 2021. Minor injuries (Code B) increased from 2 crashes (6.1% share) in June 2021 to 4 crashes (12.5% share) in June 2022, and possible injuries (Code C) tripled from 2 crashes (6.1% share) to 6 crashes (18.8% share). Conversely, crashes with no injury decreased from 28 (84.8% share) to 20 (62.5% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, 'No improper driving,' saw an increase in count from 9 in June 2021 to 12 in June 2022. 'Inattention' decreased in count from 8 to 6, and 'Followed too closely' decreased from 5 to 2. Factors such as 'Distracted' and 'Driving too fast for conditions' each increased in count from 0 to 2, while 'Visibility obstructed' decreased from 2 to 1.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
There was a shift in reported weather conditions, with 'Clear' conditions decreasing from 29 crashes in June 2021 to 26 crashes in June 2022, while 'Cloudy' conditions increased from 0 to 4 crashes. Regarding lighting, 'Daylight' crashes decreased from 29 to 23, and crashes in 'Dark - roadway not lighted' increased from 1 to 5. Road surface conditions saw 'Dry' crashes decrease from 32 to 27, while 'Wet' crashes increased from 1 to 5.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased slightly from 62 in June 2021 to 59 in June 2022. Among top vehicle makes, Ford increased its count from 8 to 11, while Chevrolet decreased from 10 to 3. In terms of persons, the 55-64 age group saw a significant increase from 10 persons to 19 persons, and the 35-44 age group increased from 4 to 10 persons.
Top Vehicle Makes (59 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (75 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone decreased from 10 in June 2021 to 4 in June 2022, and the 65 mph zone also saw a decrease from 10 to 6 crashes. Conversely, crashes in the 35 mph speed zone increased from 4 to 6. Notably, the 20 mph and 50 mph speed zones appeared in June 2022 with 3 and 2 crashes respectively, while the 10 mph zone, present in June 2021 with 1 crash, was not reported in June 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-06-01 through 2022-06-30 (30 days)
- Geographic scope: OXFORD, MA
- Total crash records analyzed: 32
- Total persons involved: 78
- Total vehicles involved: 59
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: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/oxford/june-2022-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: 2022-06-01 – 2022-06-30
Generated: June 21, 2026 · All rights reserved