ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SAUGUS, MA · FEBRUARY 2024
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/february-2024-report
Monthly Traffic Safety Analysis
52 CRASHES IN
SAUGUS, MA
FEBRUARY 2024
Total crashes in Saugus increased by 40.54% from 37 in February 2023 to 52 in February 2024. A notable shift was the substantial increase in hit-and-run crashes, which tripled from 2 incidents to 6 incidents year-over-year.
52
▲ 40.5%was 37
Total Crash Events
0
Persons Killed
14
▼ -6.7%was 15
Persons Injured
6
▲ 200.0%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 · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates an increase in crash incidents, with total crashes rising from 37 to 52, representing a 40.54% increase. Despite this rise in crash frequency, total injuries saw a slight decrease from 15 to 14, a 6.67% reduction, while fatalities remained at zero in both periods.
6
Hit-and-Run Crashes — February 2024
▲ 200.0% vs prior (2)
Hit-and-run crashes increased significantly from 2 incidents in February 2023 to 6 incidents in February 2024. Consequently, the hit-and-run rate more than doubled, rising from 5.4% to 11.5% of all crashes, indicating an upward trend in these types of incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
13
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Sunday in both periods, with 9 crashes in February 2023 and 10 crashes in February 2024. However, the peak hour shifted from 2 PM with 5 crashes in February 2023 to 6 PM with 8 crashes in February 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both periods. Serious injury crashes (severity A) decreased from 2 in February 2023 to 1 in February 2024, and minor injury crashes (severity B) decreased from 8 to 7. The proportion of all injury crashes (A, B, and C) decreased from 35.14% of total crashes in February 2023 to 21.15% in February 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'No improper driving,' increased by 50% in count from 12 crashes in February 2023 to 18 crashes in February 2024. 'Followed too closely' crashes increased from 6 to 7, a 16.7% increase in count, while its share of total crashes decreased from 16.2% to 13.5%. 'Inattention' crashes increased by 75% in count from 4 to 7, and its share rose from 10.8% to 13.5%.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 28 to 38 year-over-year, and 'Dry' road surface crashes increased from 29 to 45. A significant shift was observed in lighting conditions, with crashes occurring in 'Dark - lighted roadway' increasing from 11 to 24, while 'Daylight' crashes decreased from 23 to 21.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes saw some shifts; Toyota increased from 14 to 21, and Honda increased from 14 to 19. Acura entered the top three, increasing from 1 vehicle to 7, while Ford decreased from 8 to 3. Significant increases in person counts were observed in the 0-15 age group (from 3 to 11) and the 21-25 age group (from 3 to 21), while the 45-54 age group decreased from 17 to 12.
Top Vehicle Makes (104 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records
10 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (111 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 50 mph speed zones increased from 14 to 17, and crashes in 30 mph zones increased from 8 to 12. There were also increases in 25 mph zones (from 4 to 6) and 35 mph zones (from 2 to 5). New speed zones appeared in February 2024 data, including 1 crash in a 15 mph zone, 1 crash in a 40 mph zone, and 2 crashes in 45 mph zones.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-02-01 through 2024-02-29 (29 days)
- Geographic scope: SAUGUS, MA
- Total crash records analyzed: 52
- Total persons involved: 127
- Total vehicles involved: 104
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: February 2024." Published June 21, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/saugus/february-2024-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: 2024-02-01 – 2024-02-29
Generated: June 21, 2026 · All rights reserved