ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SAUGUS, MA · JUNE 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/saugus/june-2023-report
Monthly Traffic Safety Analysis
47 CRASHES IN
SAUGUS, MA
JUNE 2023
In June 2023, SAUGUS experienced 47 total crashes, a decrease of 4.08% compared to the 49 crashes reported in June 2022. Total injuries also saw a significant reduction, falling by 33.33% from 24 to 16. The most notable year-over-year shift was an 85.71% decrease in hit-and-run crashes, which dropped from 7 to 1.
47
▼ -4.1%was 49
Total Crash Events
0
Persons Killed
16
▼ -33.3%was 24
Persons Injured
1
▼ -85.7%was 7
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in SAUGUS showed a slight downward trend, with total crashes decreasing by 4.08% from 49 to 47. More significantly, the number of total injuries decreased by 33.33%, from 24 in June 2022 to 16 in June 2023. There were no fatalities reported in either period.
1
Hit-and-Run Crashes — June 2023
▼ -85.7% vs prior (7)
Hit-and-run crashes saw a significant decrease, falling from 7 in June 2022 to 1 in June 2023. This change resulted in the hit-and-run crash rate dropping from 14.3% of all crashes in the prior period to 2.1% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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 11 crashes in June 2022 to Friday with 12 crashes in June 2023. The peak hour for crashes also changed, moving from 5 p.m. with 10 crashes in the prior period to 4 p.m. with 5 crashes in the current period. This indicates a shift in both the busiest day and hour for crash occurrences.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either June 2022 or June 2023. The proportion of crashes resulting in minor injury decreased from 22.4% (11 crashes) to 19.1% (9 crashes), and possible injury crashes decreased from 14.3% (7 crashes) to 10.6% (5 crashes). Consequently, the share of crashes with no reported injuries increased from 59.2% to 70.2% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record
Top Contributing Factors
The number of crashes attributed to "No improper driving" remained stable at 19 in both periods. Crashes involving "Inattention" decreased by 1, from 7 to 6, and "Followed too closely" also decreased by 1 crash, from 6 to 5. "Failure to keep in proper lane or running off road" crashes decreased by 1, from 2 to 1.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Clear" weather decreased from 42 to 31, while those in "Rain" conditions increased from 1 to 6. Similarly, crashes on "Dry" road surfaces decreased from 46 to 36, and crashes on "Wet" road surfaces increased from 3 to 10. Crashes in "Dark - lighted roadway" conditions also saw an increase, rising from 2 to 8.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 101 to 91 year-over-year. Honda vehicles involved in crashes more than doubled from 11 to 22, while Toyota vehicles decreased from 21 to 15. The number of males involved in crashes increased from 53 to 57, whereas females involved decreased from 53 to 41.
Top Vehicle Makes (91 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records
4 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (98 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph speed zones increased from 16 to 21 year-over-year. Conversely, crashes in 50 mph zones decreased from 16 to 5, and in 55 mph zones from 6 to 2. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-06-01 through 2023-06-30 (30 days)
- Geographic scope: SAUGUS, MA
- Total crash records analyzed: 47
- Total persons involved: 107
- Total vehicles involved: 91
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). "SAUGUS, MA Crash Intelligence Report: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/saugus/june-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: 2023-06-01 – 2023-06-30
Generated: June 21, 2026 · All rights reserved