Monthly Traffic Safety Analysis

169 CRASHES IN
LYNN, MA
JANUARY 2025

All metrics benchmarked againstJanuary 2024

In January 2025, Lynn, MA experienced 169 crashes, an increase of 10.46% compared to the 153 crashes reported in January 2024. The most notable year-over-year shift was a 150% increase in serious injury crashes, rising from 2 in January 2024 to 5 in January 2025.

169

10.5%was 153

Total Crash Events

0

Persons Killed

68

54.5%was 44

Persons Injured

25

-26.5%was 34

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. 8 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 2025-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Total crashes in Lynn, MA increased year-over-year, rising from 153 crashes in January 2024 to 169 crashes in January 2025. This represents an increase of 16 crashes, or 10.46%, indicating an upward trend in crash incidents.

25

Hit-and-Run Crashes — January 2025

-26.5% vs prior (34)

Hit-and-run crashes decreased from 34 in January 2024 to 25 in January 2025. This reduction also led to a decrease in the hit-and-run rate, which fell from 22.2% of total crashes in the prior period to 14.8% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

13

Pedestrians Injured

Prior: 862.5%

1

Cyclists Injured

Prior: 10.0%

54

Motorists Injured

Prior: 3554.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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 Monday in both periods, with 32 crashes in January 2024 and 37 crashes in January 2025. However, the peak hour shifted from 5 PM with 13 crashes in January 2024 to 7 AM with 14 crashes in January 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either January 2024 or January 2025. Serious injury crashes (severity A) increased from 2 (1.3% of total crashes) in January 2024 to 5 (3.0% of total crashes) in January 2025. Total injuries rose from 44 to 68, with minor injury crashes (severity B) increasing from 28 (18.3%) to 40 (23.7%) year-over-year.

Outcome by Severity (Crash Events)

Serious Injury5serious injury crashes3%
150.0%prior 2
Minor Injury40minor injury crashes23.7%
42.9%prior 28
Possible Injury7possible injury crashes4.1%
0.0%prior 7
No Injury109no injury crashes64.5%
5.8%prior 103

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor in both periods remained 'No improper driving,' increasing in count from 71 to 74. Factors showing increased counts include 'Inattention' (from 9 to 11), 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' (from 7 to 10), and 'Driving too fast for conditions' (from 2 to 3). Conversely, 'Distracted' driving decreased in count from 5 to 2, and 'Failure to keep in proper lane or running off road' decreased from 3 to 2.

Officer-Reported Primary Contributing Cause

No improper driving74 (43.8%)4.2%prior 71
Inattention11 (6.5%)22.2%prior 9
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner10 (5.9%)42.9%prior 7
Other improper action5 (3%)
Disregarded traffic signs, signals, road markings3 (1.8%)
Driving too fast for conditions3 (1.8%)
Distracted2 (1.2%)-60.0%prior 5
Failed to yield right of way2 (1.2%)
Failure to keep in proper lane or running off road2 (1.2%)
Followed too closely2 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 82 in January 2024 to 97 in January 2025, while crashes in 'Snow' conditions rose from 11 to 21. Conversely, crashes in 'Rain' decreased from 11 to 7. Regarding road surface, crashes on 'Dry' roads increased from 86 to 101, and on 'Ice' from 8 to 16, while crashes on 'Wet' roads decreased from 32 to 23.

Weather

Clear97 (57.4%)
18.3%prior 82
Snow21 (12.4%)
90.9%prior 11
Clear/Clear18 (10.7%)
50.0%prior 12
Cloudy16 (9.5%)
0.0%prior 16
Rain7 (4.1%)
-36.4%prior 11
Snow/Sleet, hail (freezing rain or drizzle)2 (1.2%)
Snow/Clear1 (0.6%)
Blowing sand, snow/Snow1 (0.6%)
Snow/Snow1 (0.6%)
Clear/Snow1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash

Lighting

Daylight90 (53.3%)
21.6%prior 74
Dark - lighted roadway69 (40.8%)
1.5%prior 68
Dawn5 (3.0%)
Dark - unknown roadway lighting2 (1.2%)
Dusk2 (1.2%)
-75.0%prior 8
Dark - roadway not lighted1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field

Road Surface

Dry101 (59.8%)
17.4%prior 86
Snow26 (15.4%)
36.8%prior 19
Wet23 (13.6%)
-28.1%prior 32
Ice16 (9.5%)
100.0%prior 8
Slush2 (1.2%)
Other1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 289 in January 2024 to 334 in January 2025. The ranking of top vehicle makes shifted, with Toyota moving from third (30 vehicles) to first (78 vehicles), while Honda moved from first (65 vehicles) to second (63 vehicles). The age group 16-20 saw the largest increase in persons involved, rising from 22 to 40 year-over-year.

Top Vehicle Makes (334 vehicles)

1
TOYOTA78 (23.4%)
160.0%prior 30
2
HONDA63 (18.9%)
-3.1%prior 65
3
FORD36 (10.8%)
-10.0%prior 40
4
NISSAN25 (7.5%)
8.7%prior 23
5
CHEVROLET20 (6%)
5.3%prior 19
6
JEEP16 (4.8%)
23.1%prior 13
7
SUBARU11 (3.3%)
120.0%prior 5
8
KIA9 (2.7%)
50.0%prior 6
9
HYUNDAI8 (2.4%)
-33.3%prior 12
10
GMC7 (2.1%)
-12.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records

68 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (377 persons with recorded sex)

Male225 (59.7%)
21.0%prior 186
Female152 (40.3%)
15.2%prior 132

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones increased from 100 in January 2024 to 123 in January 2025. Conversely, crashes in 20 mph zones decreased from 22 to 10. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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: 2025-01-01 through 2025-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-01-31 (31 days)
  • Geographic scope: LYNN, MA
  • Total crash records analyzed: 169
  • Total persons involved: 439
  • Total vehicles involved: 334

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: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lynn/january-2025-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

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Lynn, MA Crash Report — January 2025 | ThatCarHitMe.com