ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SAUGUS, MA · 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/2023-annual-report
Yearly Traffic Safety Analysis
680 CRASHES IN
SAUGUS, MA
2023
In 2023, Saugus recorded 680 total traffic crashes, a 4.4% decrease from the 711 crashes reported in 2022. While total crashes declined, the number of people injured rose from 270 to 286. A notable change was the reduction in traffic fatalities, with zero recorded in 2023 compared to one fatality in the prior year.
680
▼ -4.4%was 711
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
286
▲ 5.9%was 270
Persons Injured
54
▲ 22.7%was 44
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. 24 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic collisions in Saugus showed a downward trend, decreasing by 4.4% from 711 in 2022 to 680 in 2023. Despite the drop in total crashes, the number of people injured increased by 5.9% year-over-year, from 270 to 286. The city recorded zero traffic fatalities in 2023, an improvement from the single fatality reported in the previous year.
54
Hit-and-Run Crashes — 2023
▲ 22.7% vs prior (44)
Hit-and-run incidents increased in both count and as a proportion of total crashes. The number of hit-and-run crashes rose from 44 in 2022 to 54 in 2023, representing a 22.7% increase. The hit-and-run rate also trended upward, climbing from 6.2% of all crashes in 2022 to 7.9% in 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
12
Pedestrians Injured
1
Cyclists Injured
273
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In 2023, the peak day for crashes was Friday with 105 incidents, whereas in 2022, Monday was the peak day with 118 incidents. The peak hour also shifted slightly, moving from 6 p.m. in 2022 (62 crashes) to 5 p.m. in 2023 (63 crashes). Crash distribution by day of the week was more uniform in 2023 compared to the prior year, which saw a distinct spike on Mondays.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While Saugus saw a positive development with fatal crashes dropping from one in 2022 to zero in 2023, the severity of injury-related crashes increased. The count of serious injury crashes rose from 8 to 15, and their share of all crashes increased from 1.1% to 2.2%. Similarly, minor injury crashes grew from 117 to 140, making up 20.6% of all incidents in 2023 compared to 16.5% in 2022. Consequently, the proportion of crashes resulting in no injury decreased from 68.4% to 63.2%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors cited in crashes remained consistent year-over-year, with 'No improper driving,' 'Inattention,' and 'Followed too closely' leading in both periods. However, the counts for some key factors shifted notably. Crashes attributed to 'Failure to keep in proper lane' more than doubled, increasing in count from 11 in 2022 to 26 in 2023. Conversely, incidents involving 'Driving too fast for conditions' saw a significant decrease in count, dropping from 19 to 7.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In both 2022 and 2023, the vast majority of crashes occurred in clear weather, during daylight hours, and on dry roads, with the proportion of crashes under these conditions remaining stable. There was a noticeable increase in crashes on wet roads, which rose from 90 in 2022 to 114 in 2023. Conversely, crashes on roads with ice or snow saw a substantial decrease, dropping from a combined 43 incidents in 2022 to just 11 in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes were Toyota, Honda, and Ford in both 2022 and 2023, maintaining their rankings. The number of Toyotas involved increased from 205 to 218, while the involvement of Hondas and Fords decreased. The age demographics of individuals involved in crashes also remained stable year-over-year, with the 26-34 age group being the most frequently involved demographic in both periods, accounting for 293 individuals in 2023 compared to 296 in 2022.
Top Vehicle Makes (1,341 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
127 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,380 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes were most prevalent in 30 mph and 50 mph speed zones in both years. In 2023, there was a notable decrease in crashes within 50 mph zones, dropping from 244 incidents in 2022 to 209. Crashes in 30 mph zones also saw a slight reduction from 229 to 216. The single fatality recorded in 2022 occurred in a 50 mph zone; in 2023, no fatal crashes were reported in any speed zone.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: SAUGUS, MA
- Total crash records analyzed: 680
- Total persons involved: 1,566
- Total vehicles involved: 1,341
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/saugus/2023-annual-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved