ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MEDFORD, MA · AUGUST 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/medford/august-2022-report
Monthly Traffic Safety Analysis
113 CRASHES IN
MEDFORD, MA
AUGUST 2022
In August 2022, Medford experienced 113 total crashes, a 48.7% increase compared to the 76 crashes recorded in August 2021. While overall crashes and injuries rose significantly, a notable shift was the decrease in fatalities from 1 in August 2021 to 0 in August 2022. This period saw a substantial rise in total injuries, increasing from 16 to 30.
113
▲ 48.7%was 76
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
30
▲ 87.5%was 16
Persons Injured
26
▲ 100.0%was 13
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. 15 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for August 2022 indicates a rising trend in crash incidents in Medford compared to the prior year. Total crashes increased by 48.7%, from 76 to 113. Concurrently, total injuries saw an 87.5% increase, rising from 16 to 30, despite a decrease in fatalities from 1 to 0.
26
Hit-and-Run Crashes — August 2022
▲ 100.0% vs prior (13)
Hit-and-run crashes increased significantly, with the count rising by 100% from 13 in August 2021 to 26 in August 2022. Consequently, the hit-and-run rate also trended upwards, increasing from 17.1% of total crashes in August 2021 to 23% in August 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
3
Pedestrians Injured
4
Cyclists Injured
22
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns for crashes shifted between the two periods. In August 2022, Monday was the peak day for crashes with 21 incidents, a change from Friday being the peak day with 20 crashes in August 2021. The peak hour also shifted from 9 AM with 8 crashes in August 2021 to 5 PM with 10 crashes in August 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution changed notably year-over-year; fatal crashes decreased from 1 (1.3% of total crashes) in August 2021 to 0 in August 2022. Serious injuries, coded as 'A', increased from 0 in August 2021 to 4 in August 2022. Minor injuries, coded as 'B', saw a slight increase in count from 11 to 12, while possible injuries, coded as 'C', rose from 2 to 9.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Most severe injury per crash record
Top Contributing Factors
Contributing factors showed significant changes in counts and rankings. 'Failed to yield right of way' crashes increased by 125%, from 8 to 18, maintaining its position as the second most frequent factor. 'Followed too closely' crashes saw a 300% increase, rising from 4 to 16, moving from the sixth to the third most common factor. 'Inattention' crashes also increased by 200%, from 4 to 12, becoming the fourth most frequent factor.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 49 in August 2021 to 84 in August 2022. The number of crashes on wet road surfaces decreased from 10 to 5. Crashes occurring during daylight hours increased from 55 to 79, while those in dark but lighted roadway conditions increased from 16 to 26.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes all showed increased counts year-over-year. Toyota vehicles increased from 29 to 40, Honda from 22 to 33, and Ford from 14 to 22. In terms of persons involved, the 35-44 age group saw a 180% increase from 15 to 42, and the 16-20 age group increased by 88.9% from 9 to 17.
Top Vehicle Makes (208 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Vehicle unit records
46 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (201 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed zones increased by 42.2%, from 45 to 64. Conversely, crashes in 35 mph zones decreased by 23.8%, from 21 to 16. There was a notable increase in crashes in 55 mph zones, rising by 150% from 6 to 15, and the single fatal crash in a 35 mph zone in the prior period was not repeated.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · 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: 2022-08-01 through 2022-08-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-08-01 through 2022-08-31 (31 days)
- Geographic scope: MEDFORD, MA
- Total crash records analyzed: 113
- Total persons involved: 247
- Total vehicles involved: 208
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). "MEDFORD, MA Crash Intelligence Report: August 2022." Published June 21, 2026. Reporting period: 2022-08-01 to 2022-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/medford/august-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: 2022-08-01 – 2022-08-31
Generated: June 21, 2026 · All rights reserved