ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SAUGUS, MA · JANUARY 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/january-2024-report
Monthly Traffic Safety Analysis
52 CRASHES IN
SAUGUS, MA
JANUARY 2024
In January 2024, Saugus experienced 52 total crashes, an 11.9% decrease compared to the 59 crashes recorded in January 2023. A notable shift was the increase in speeding-related crashes, rising from 0 in the prior year to 3 in the current period.
52
▼ -11.9%was 59
Total Crash Events
0
Persons Killed
20
▼ -4.8%was 21
Persons Injured
4
▼ -33.3%was 6
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for Saugus indicates a downward trend, with total crashes decreasing by 11.9% from 59 in January 2023 to 52 in January 2024. Similarly, total injuries saw a slight reduction, falling by 4.8% from 21 to 20 over the same period. There were no fatalities reported in either January 2023 or January 2024.
4
Hit-and-Run Crashes — January 2024
▼ -33.3% vs prior (6)
The number of hit-and-run crashes decreased from 6 in January 2023 to 4 in January 2024. Consequently, the hit-and-run rate also saw a reduction, moving from 10.2% of all crashes in the prior period to 7.7% in the current period.
Vulnerable Road User Casualties
0
Motorists Killed
20
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes showed some shifts year-over-year. The peak day for crashes moved from Wednesday with 12 crashes in January 2023 to Thursday with 10 crashes in January 2024. The peak hour for crashes also shifted, with 5 PM recording 8 crashes in the prior period, while 6 PM recorded 9 crashes in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes showed a slight improvement, with no serious injuries (code A) reported in January 2024 compared to one in January 2023. The number of minor injuries remained constant at 14, while possible injuries decreased from 3 to 1. The proportion of crashes involving any injury also saw a minor decrease, from 30.5% in January 2023 to 28.8% in January 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Most severe injury per crash record
Top Contributing Factors
Analysis of contributing factors reveals several shifts year-over-year. Crashes attributed to 'No improper driving' decreased by 3, from 22 in January 2023 to 19 in January 2024. Conversely, crashes where 'Exceeded authorized speed limit' was a factor increased from 0 to 2, and 'Followed too closely' increased by 1, from 4 to 5. 'Inattention' as a factor decreased by 2, from 3 to 1.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Weather conditions at the time of crashes showed a notable shift, with crashes during 'Snow' conditions increasing from 2 in January 2023 to 8 in January 2024. Correspondingly, crashes on 'Wet' road surfaces decreased significantly from 16 to 7, while those on 'Snow' surfaces increased from 2 to 7. Crashes occurring in 'Daylight' decreased by 5, from 29 to 24, while those in 'Dark - lighted roadway' increased by 2, from 21 to 23.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 121 in January 2023 to 98 in January 2024. Regarding vehicle makes, Toyota and Honda saw decreases in their involvement, while Nissan increased from 9 to 13. A significant shift in person age distribution was observed, with persons aged 16-20 involved in crashes decreasing from 19 to 7, and those aged 45-54 decreasing from 22 to 14. Conversely, involvement for the 26-34 age group increased from 15 to 21.
Top Vehicle Makes (98 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (99 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes within certain speed limit zones showed notable changes year-over-year. Crashes in 20 mph zones decreased from 8 to 1, and in 30 mph zones from 15 to 9. Conversely, crashes in 35 mph zones increased from 2 to 8, and in 55 mph zones from 2 to 6. No fatal crashes were recorded in any speed zone during either January 2023 or January 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · 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: 2024-01-01 through 2024-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-01-31 (31 days)
- Geographic scope: SAUGUS, MA
- Total crash records analyzed: 52
- Total persons involved: 111
- Total vehicles involved: 98
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: January 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/saugus/january-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: 2024-01-01 – 2024-01-31
Generated: June 21, 2026 · All rights reserved