ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LYNN, MA · FEBRUARY 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/lynn/february-2023-report
Monthly Traffic Safety Analysis
149 CRASHES IN
LYNN, MA
FEBRUARY 2023
Total crashes in LYNN decreased by 9.7% year-over-year, from 165 in February 2022 to 149 in February 2023. Despite the overall reduction in crashes, total injuries increased by 21.1%, rising from 38 to 46. The most notable shift was a significant increase in pedestrian crashes, which rose from 2 to 10 incidents.
149
▼ -9.7%was 165
Total Crash Events
0
Persons Killed
46
▲ 21.1%was 38
Persons Injured
39
▼ -20.4%was 49
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. 9 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a decrease in total crashes, falling from 165 in February 2022 to 149 in February 2023. This represents a reduction of 16 crashes, or approximately 9.7% year-over-year. However, total injuries increased from 38 to 46, marking a 21.1% rise.
39
Hit-and-Run Crashes — February 2023
▼ -20.4% vs prior (49)
The number of hit-and-run crashes decreased from 49 in February 2022 to 39 in February 2023. Correspondingly, the hit-and-run rate decreased from 29.7% to 26.2% year-over-year. This indicates a downward trend in both the count and proportion of hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
9
Pedestrians Injured
37
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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 Monday with 30 incidents in February 2022 to Wednesday with 26 incidents in February 2023. The peak hour also changed, moving from 12p (15 crashes) in the prior period to 6p (15 crashes) in the current period, though the crash count for the peak hour remained constant.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities and fatal crashes remained at zero for both February 2022 and February 2023. Total injuries increased from 38 to 46, with serious injuries rising from 1 to 2 and minor injuries increasing from 17 to 26. Conversely, possible injuries decreased from 8 to 6.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record
Top Contributing Factors
The number of crashes attributed to 'No improper driving' slightly increased from 51 in February 2022 to 53 in February 2023. 'Inattention' remained stable at 4 crashes in both periods, as did 'Failed to yield right of way' with 3 crashes. 'Other improper action' decreased significantly from 4 crashes in the prior period to 1 crash in the current period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 99 to 104 year-over-year. There was a notable decrease in crashes during adverse weather, with snow-related incidents falling from 14 to 8 and sleet-related incidents decreasing from 14 to 3. Crashes on dry road surfaces increased from 76 to 115, while those on wet surfaces decreased from 39 to 13.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Road surface condition field
Vehicles & Demographics
The top vehicle make involved in crashes shifted from Honda (68 vehicles) in February 2022 to Toyota (57 vehicles) in February 2023. Toyota's involvement increased from 46 to 57 vehicles, while Honda's decreased from 68 to 52 vehicles. Among persons involved in crashes, the 26-34 age group saw a decrease from 72 to 62, while the 65+ age group increased from 19 to 34.
Top Vehicle Makes (290 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Vehicle unit records
170 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (302 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 mph speed zones decreased from 102 in February 2022 to 76 in February 2023. Conversely, crashes in 30 mph zones increased from 33 to 39 during the same period. No fatal crashes were recorded in any speed zone for either February 2022 or February 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-02-01 through 2023-02-28 (28 days)
- Geographic scope: LYNN, MA
- Total crash records analyzed: 149
- Total persons involved: 465
- Total vehicles involved: 290
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). "LYNN, MA Crash Intelligence Report: February 2023." Published June 21, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lynn/february-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: 2023-02-01 – 2023-02-28
Generated: June 21, 2026 · All rights reserved