ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · OXFORD, MA · 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/2022-annual-report
Yearly Traffic Safety Analysis
334 CRASHES IN
OXFORD, MA
2022
In Oxford, total traffic crashes increased from 272 in 2021 to 334 in 2022, a rise of 22.8%. While the number of fatalities remained stable at two, the number of persons injured rose by 32.4%, from 71 in the prior year to 94 in the current year. The most notable shifts occurred in the circumstances of crashes, with significant increases in incidents involving erratic driving and those occurring in darkness.
334
▲ 22.8%was 272
Total Crash Events
2
Persons Killed
94
▲ 32.4%was 71
Persons Injured
16
▲ 60.0%was 10
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. 8 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for Oxford indicates a rising trend in traffic incidents year-over-year. The total number of crashes increased by 22.8%, from 272 in 2021 to 334 in 2022. Similarly, the number of people injured in these incidents grew from 71 to 94, a 32.4% increase, while fatalities held constant at two for both periods.
16
Hit-and-Run Crashes — 2022
▲ 60.0% vs prior (10)
Hit-and-run incidents trended upward in 2022 compared to the previous year. The absolute number of hit-and-run crashes increased by 60%, from 10 in 2021 to 16 in 2022. Consequently, the hit-and-run rate, representing the proportion of all crashes that were hit-and-runs, also rose from 3.7% to 4.8%.
Vulnerable Road User Casualties
2
Motorists Killed
94
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Friday with 58 incidents, a change from 2021 when Wednesday was the peak day with 47 crashes. The busiest time of day also moved earlier, with the peak hour shifting from 5 p.m. in 2021 (31 crashes) to 2 p.m. in 2022 (23 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the number of fatal crashes remained unchanged at two in both 2021 and 2022, the overall severity of crashes showed some changes. The fatal crash rate per incident decreased slightly from 0.74% to 0.6%. However, the number of crashes involving injuries increased from 53 to 75, with notable growth in 'Possible Injury' crashes, which more than doubled from 10 to 22 incidents.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors remained consistent across both years: 'No improper driving,' 'Inattention,' and 'Followed too closely.' However, the count of crashes attributed to several other factors grew significantly. Incidents citing 'Failed to yield right of way' increased by 55.6% in count, from 18 to 28, while crashes involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' rose by 61.5% in count, from 13 to 21.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
While the majority of crashes in both years occurred on dry roads in clear weather, there was a notable shift in lighting conditions. The number of crashes occurring in dark conditions (both lighted and unlighted roadways) increased from 63 in 2021 to 104 in 2022, representing a proportional increase from 23.2% to 31.1% of all crashes. Conversely, the share of crashes occurring during adverse weather like rain or snow decreased from 19.5% to 13.5% of the annual total.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes shifted year-over-year, with Ford (88 vehicles) overtaking Toyota (74 vehicles) for the most-involved make in 2022, reversing the 2021 ranking where Toyota led with 80 vehicles. The age demographics of persons involved in crashes also changed, with the share of individuals in the 21-25 and 65+ age groups increasing, while the 26-34 age group saw its representation decrease from 19.9% in 2021 to 17.2% in 2022.
Top Vehicle Makes (562 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
40 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (668 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
In both years, the 65 mph speed zone accounted for the highest number of crashes, with the count increasing from 77 in 2021 to 94 in 2022. The locations of fatal crashes shifted to lower speed zones in the more recent period. In 2022, the two fatal crashes occurred in 20 mph and 30 mph zones, whereas in 2021, they occurred in 35 mph and 65 mph zones.
Fatal crashes by zone: 20 mph: 1 of 9 (11.111%) · 30 mph: 1 of 60 (1.667%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: OXFORD, MA
- Total crash records analyzed: 334
- Total persons involved: 710
- Total vehicles involved: 562
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/oxford/2022-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved