ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SAUGUS, MA · MAY 2025
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/may-2025-report
Monthly Traffic Safety Analysis
64 CRASHES IN
SAUGUS, MA
MAY 2025
In May 2025, Saugus recorded 64 total crashes, an increase from the 58 crashes reported in May 2024, representing a 10.3% rise year-over-year. A notable shift was observed in hit-and-run incidents, which saw a substantial increase during this period.
64
▲ 10.3%was 58
Total Crash Events
0
Persons Killed
15
▼ -34.8%was 23
Persons Injured
13
▲ 550.0%was 2
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, Saugus experienced an increase in total crashes, rising from 58 in May 2024 to 64 in May 2025, a 10.3% year-over-year increase. Despite the rise in crash volume, total injuries decreased by 34.8% from 23 to 15 during the same period.
13
Hit-and-Run Crashes — May 2025
▲ 550.0% vs prior (2)
Hit-and-run crashes increased dramatically from 2 incidents in May 2024 to 13 incidents in May 2025, representing a 550% increase in count. The hit-and-run rate also saw a substantial rise, climbing from 3.4% of all crashes in May 2024 to 20.3% in May 2025.
Vulnerable Road User Casualties
0
Motorists Killed
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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 Thursday in May 2024, with 10 incidents, to Saturday in May 2025, with 14 incidents. The peak hour also changed, moving from 3 PM with 8 crashes in May 2024 to 9 PM with 6 crashes in May 2025, indicating a shift in the timing of crash occurrences.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Total injuries decreased by 34.8% from 23 in May 2024 to 15 in May 2025. Serious injuries, coded 'A', increased from 1 incident (1.7% of crashes) to 2 incidents (3.1% of crashes) year-over-year. Minor injuries, coded 'B', saw a reduction from 14 incidents (24.1% of crashes) to 8 incidents (12.5% of crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record
Top Contributing Factors
The most frequent contributing factor, 'No improper driving', increased from 19 crashes in May 2024 to 26 crashes in May 2025, a 36.8% rise in count. 'Followed too closely' saw a significant increase from 3 crashes in May 2024 to 14 crashes in May 2025, representing a 366.7% surge in count. Conversely, crashes attributed to 'Inattention' decreased by 66.7% in count, from 6 incidents to 2.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The number of crashes occurring in 'Clear' weather conditions decreased from 42 in May 2024 to 36 in May 2025, while crashes in 'Rain' conditions remained stable at 6 incidents in both periods. Crashes during 'Daylight' conditions increased from 42 to 48 year-over-year. The number of crashes on 'Wet' road surfaces rose from 8 in May 2024 to 11 in May 2025.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 33.6%, from 107 in May 2024 to 143 in May 2025. Toyota became the most frequently involved make with 32 incidents in May 2025, surpassing Honda which was the top make in May 2024 with 15 incidents. The age group 26-34 saw the largest increase in persons involved, rising from 19 to 27 year-over-year.
Top Vehicle Makes (143 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records
38 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (137 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 50 mph speed limit zone increased from 16 in May 2024 to 34 in May 2025, making it the most frequent speed zone for crashes in the current period. Conversely, crashes in the 30 mph zone decreased from 21 to 11 incidents during the same period. No fatal crashes were reported in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-05-01 through 2025-05-31 (31 days)
- Geographic scope: SAUGUS, MA
- Total crash records analyzed: 64
- Total persons involved: 175
- Total vehicles involved: 143
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: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/saugus/may-2025-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: 2025-05-01 – 2025-05-31
Generated: June 21, 2026 · All rights reserved