ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LYNN, MA · 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/lynn/2025-annual-report
Yearly Traffic Safety Analysis
1,770 CRASHES IN
LYNN, MA
2025
In 2025, Lynn recorded 1,770 total vehicle crashes, an 8.3% decrease from the 1,931 crashes reported in 2024. Despite the overall reduction in collisions, total injuries rose by 5.0% from 694 to 729. One of the most notable shifts was a 57.9% increase in crashes involving bicycles, which rose from 19 to 30 incidents year-over-year.
1,770
▼ -8.3%was 1,931
Total Crash Events
2
▼ -33.3%was 3
Persons Killed
729
▲ 5.0%was 694
Persons Injured
341
▼ -16.4%was 408
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 106 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crash trends in Lynn show a decrease in total incidents and fatalities year-over-year. Total crashes fell by 8.3%, from 1,931 in 2024 to 1,770 in 2025, and fatalities decreased from 3 to 2. However, the number of people injured in these crashes increased by 5.0%, rising from 694 to 729.
341
Hit-and-Run Crashes — 2025
▼ -16.4% vs prior (408)
Incidents of hit-and-run crashes decreased from 2024 to 2025. The total count of hit-and-run crashes fell from 408 to 341, a reduction of 67 incidents. The hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also trended downward, declining from 21.1% in 2024 to 19.3% in 2025.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
75
Pedestrians Injured
34
Cyclists Injured
602
Motorists Injured
18
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some changes between 2024 and 2025. While Monday remained the peak day for crashes in both years, the count of Monday crashes decreased from 306 to 279. The peak hour for collisions shifted from the 3 PM hour in 2024, which saw 131 crashes, to the 5 PM hour in 2025, which recorded 140 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes shifted between the two periods, with a decrease in fatal incidents but an increase in injury-related crashes. The number of fatal crashes dropped from 3 in 2024 to 2 in 2025, and the fatal crash rate per 100 crashes decreased from 0.16 to 0.11. Conversely, the proportion of crashes resulting in an injury increased, with serious injury crashes rising from 1.2% to 1.6% of all incidents and minor injury crashes increasing from 22.0% to 25.4%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes saw shifts in ranking and frequency year-over-year. While 'No improper driving' remained the most cited circumstance, its count decreased by 11.8% from 773 to 682. 'Operating vehicle in an erratic, reckless, careless, negligent or aggressive manner' saw its count drop by 15.9% from 113 to 95, causing it to fall from the second to the fourth most common factor. Meanwhile, 'Other improper action' incidents increased by 9.6% from 94 to 103, moving it up to become the second-ranked contributing factor in 2025.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes under adverse conditions showed mixed trends between 2024 and 2025. The proportion of crashes occurring on wet road surfaces decreased from 16.8% to 14.0% of all incidents. However, crashes on roads with snow or ice increased, rising from 56 incidents (2.9% of total) in 2024 to 87 incidents (4.9% of total) in 2025. Regarding lighting, the share of crashes in daylight decreased from 60.3% to 57.5%, while the share of crashes in darkness on lighted roadways increased from 33.1% to 34.8%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained Honda, Toyota, and Ford in both years, though their counts shifted. The number of Hondas involved decreased from 788 to 718, while Toyotas increased from 691 to 713, narrowing the gap between the top two makes. An analysis of persons involved in crashes shows the 26-34 age group remained the largest cohort in both periods, though its count decreased from 879 to 804. The representation of most age groups as a percentage of total persons involved remained relatively stable.
Top Vehicle Makes (3,510 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
795 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (3,926 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones remained largely consistent, with the 25 mph zone accounting for the majority of incidents in both 2024 (1,197 crashes) and 2025 (1,090 crashes). There was a notable shift in the location of fatal crashes; in 2024, the three fatalities occurred in 30 mph and 35 mph zones. In 2025, both fatal crashes occurred in a 25 mph zone.
Fatal crashes by zone: 25 mph: 2 of 1,090 (0.183%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: LYNN, MA
- Total crash records analyzed: 1,770
- Total persons involved: 4,679
- Total vehicles involved: 3,510
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lynn/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved