ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MEDFORD, MA · JULY 2023
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/july-2023-report
Monthly Traffic Safety Analysis
101 CRASHES IN
MEDFORD, MA
JULY 2023
In MEDFORD, MA, total crashes increased by 10.99% from 91 in July 2022 to 101 in July 2023. Concurrently, total injuries rose by 19.35%, from 31 to 37. A notable shift was observed in hit-and-run incidents, which decreased by 26.67% year-over-year.
101
▲ 11.0%was 91
Total Crash Events
0
Persons Killed
37
▲ 19.4%was 31
Persons Injured
11
▼ -26.7%was 15
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. 8 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for MEDFORD, MA indicates an upward trend year-over-year, with total crashes increasing from 91 to 101. Total injuries also rose from 31 to 37 during this period. Fatalities remained stable at zero in both July 2022 and July 2023.
11
Hit-and-Run Crashes — July 2023
▼ -26.7% vs prior (15)
Hit-and-run crashes decreased from 15 incidents in July 2022 to 11 incidents in July 2023. This represents a reduction in the hit-and-run rate from 16.5% to 10.9% of total crashes. The data indicates a downward trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
36
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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 Friday in July 2022, with 19 incidents, to Saturday in July 2023, with 20 incidents. The peak hour for crashes remained 2 PM in both periods, although the count decreased from 12 crashes in July 2022 to 10 crashes in July 2023. These changes suggest a slight shift in when crashes are most concentrated.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes reported in either July 2022 or July 2023. However, serious injury crashes (severity 'A') were present in July 2022 (2 crashes) but absent in July 2023. The proportion of crashes resulting in possible injuries ('C') increased from 7.7% (7 crashes) to 12.9% (13 crashes) year-over-year, while crashes with no injuries ('O') saw their proportion decrease from 69.2% to 64.4%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'No improper driving', increased in count from 17 in July 2022 to 25 in July 2023, representing a 47.1% increase. Conversely, 'Followed too closely' incidents decreased by 33.3% in count, from 15 to 10. 'Other improper action' saw a significant increase in count from 3 to 12, while 'Inattention' incidents decreased from 9 to 3.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 86 (including Clear and Clear/Clear) in July 2022 to 76 (including Clear and Clear/Clear) in July 2023. Conversely, crashes in rainy conditions increased from 3 to 9, and crashes in cloudy conditions increased from 1 to 9. The number of crashes on wet road surfaces more than doubled, rising from 6 in July 2022 to 14 in July 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 174 in July 2022 to 194 in July 2023. Honda and Toyota were tied for the most frequently involved makes in July 2023 with 37 incidents each, both increasing from their July 2022 counts of 21 and 26 respectively. The 26-34 age group saw a rise in involved persons from 28 to 39, while persons aged 0-15 decreased from 6 to 1. The number of males involved increased from 101 to 115, while females decreased from 86 to 77.
Top Vehicle Makes (194 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Vehicle unit records
37 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (192 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 mph speed zones increased from 56 in July 2022 to 66 in July 2023. In contrast, crashes in 35 mph zones slightly decreased from 15 to 13, and incidents in 65 mph zones decreased from 4 to 1. All reported speed zones maintained a fatal crash count of zero in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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: 2023-07-01 through 2023-07-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-07-01 through 2023-07-31 (31 days)
- Geographic scope: MEDFORD, MA
- Total crash records analyzed: 101
- Total persons involved: 225
- Total vehicles involved: 194
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: July 2023." Published June 21, 2026. Reporting period: 2023-07-01 to 2023-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/medford/july-2023-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: 2023-07-01 – 2023-07-31
Generated: June 21, 2026 · All rights reserved