ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · OXFORD, MA · SEPTEMBER 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/september-2022-report
Monthly Traffic Safety Analysis
34 CRASHES IN
OXFORD, MA
SEPTEMBER 2022
In September 2022, the city of OXFORD, MA experienced 34 total crashes, an increase from 30 crashes in September 2021. This represents a 13.33% rise in overall crash incidents year-over-year. The most notable shift was the increase in total fatalities, which rose from 0 in September 2021 to 2 in September 2022.
34
▲ 13.3%was 30
Total Crash Events
2
Persons Killed
8
▼ -11.1%was 9
Persons Injured
2
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates an increase in crashes, with total incidents rising from 30 in September 2021 to 34 in September 2022. This constitutes a 13.33% increase in the number of crashes year-over-year. Total injuries decreased slightly from 9 in September 2021 to 8 in September 2022.
2
Hit-and-Run Crashes — September 2022
▼ 0.0% vs prior (2)
The number of hit-and-run crashes remained constant at 2 in both September 2021 and September 2022. However, the hit-and-run rate decreased from 6.7% in the prior period to 5.9% in the current period. This indicates a slight downward trend in the proportion of hit-and-run incidents relative to total crashes.
Vulnerable Road User Casualties
2
Motorists Killed
8
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Wednesday in both periods, though the count decreased from 8 crashes in September 2021 to 7 crashes in September 2022. The peak hour also remained consistent at 3 p.m., with 5 crashes recorded at this time in both September 2021 and September 2022. There was a notable increase in crashes on Sundays, rising from 2 in the prior period to 6 in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The most significant change in crash severity was the increase in fatal crashes, which rose from 0 in September 2021 to 2 in September 2022, resulting in a fatal rate of 5.88% in the current period. The number of serious injury crashes remained constant at 2 in both periods, while minor injury crashes also stayed at 4. The proportion of 'No Injury' crashes remained largely stable, at 76.7% in September 2021 and 76.5% in September 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Most severe injury per crash record
Top Contributing Factors
Inattention remained the top contributing factor, increasing from 7 crashes in September 2021 to 10 crashes in September 2022, a 42.86% increase in count. 'Failed to yield right of way' saw a substantial increase, rising from 1 crash to 6 crashes, a 500% increase in count. Conversely, 'Followed too closely' decreased significantly from 6 crashes in the prior period to 1 crash in the current period, an 83.33% decrease in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Clear weather conditions remained dominant for crashes, increasing from 21 crashes in September 2021 to 24 crashes in September 2022. Crashes occurring in rain decreased slightly from 5 to 4. For lighting conditions, daylight crashes decreased from 22 to 20, while crashes in 'Dark - lighted roadway' increased from 3 to 4. Dry road surfaces continued to be the most common condition, with crashes increasing from 24 to 27.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Road surface condition field
Vehicles & Demographics
The age group 16-20 saw a significant increase in persons involved in crashes, rising from 5 in September 2021 to 15 in September 2022. The 35-44 age group experienced a decrease from 17 to 8 persons. Regarding vehicle makes, FORD, which was the top make with 12 vehicles in September 2021, decreased to 4 in September 2022, while TOYOTA became the top make, increasing from 8 to 9 vehicles.
Top Vehicle Makes (59 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Vehicle unit records
5 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (79 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Person-level records linked to crash events
Speed Limit Zones
Fatal crashes occurred in speed zones of 20 mph (1 crash) and 30 mph (1 crash) in September 2022, whereas no fatal crashes were reported in any speed zone in September 2021. Crashes in 30 mph zones increased from 4 to 7, while crashes in 65 mph zones decreased from 9 to 6. A new speed zone of 20 mph appeared in the current period with 2 crashes, including one fatal incident.
Fatal crashes by zone: 20 mph: 1 of 2 (50%) · 30 mph: 1 of 7 (14.286%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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: 2022-09-01 through 2022-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-09-01 through 2022-09-30 (30 days)
- Geographic scope: OXFORD, MA
- Total crash records analyzed: 34
- Total persons involved: 84
- 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: September 2022." Published June 21, 2026. Reporting period: 2022-09-01 to 2022-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/oxford/september-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: 2022-09-01 – 2022-09-30
Generated: June 21, 2026 · All rights reserved