Monthly Traffic Safety Analysis

20 CRASHES IN
LYNNFIELD, MA
MARCH 2025

All metrics benchmarked againstMarch 2024

In March 2025, LYNNFIELD experienced 20 total crashes, marking a 16.67% decrease compared to the 24 crashes reported in March 2024. The most notable shift was a significant 70% reduction in total injuries, falling from 10 in the prior period to 3 in the current period.

20

-16.7%was 24

Total Crash Events

0

Persons Killed

3

-70.0%was 10

Persons Injured

3

-50.0%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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for LYNNFIELD shows a downward trend year-over-year, with total crashes decreasing by 4 incidents from 24 to 20, representing a 16.67% reduction. This decline is further emphasized by a substantial decrease in total injuries, which fell from 10 to 3.

3

Hit-and-Run Crashes — March 2025

-50.0% vs prior (6)

Hit-and-run crashes decreased by 50%, falling from 6 incidents in March 2024 to 3 in March 2025. Consequently, the hit-and-run rate also declined from 25% of all crashes in the prior period to 15% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

3

Motorists Injured

Prior: 10-70.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted year-over-year, with the peak day moving from Friday (8 crashes) in March 2024 to Monday (6 crashes) in March 2025. Similarly, the peak crash hour changed from 7 AM (3 crashes) in the prior period to 6 PM (4 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero for both March 2024 and March 2025. Total injuries decreased significantly from 10 in the prior period to 3 in the current period. The proportion of crashes resulting in no injury increased from 70.8% in March 2024 to 85% in March 2025.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes15%
50.0%prior 2
No Injury17no injury crashes85%
0.0%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record

Top Contributing Factors

The number of crashes attributed to 'No improper driving' decreased from 8 in March 2024 to 5 in March 2025, while 'Inattention' crashes increased from 2 to 4. 'Followed too closely' emerged as a significant factor in March 2025 with 4 crashes, whereas it was not listed among the top factors in March 2024. Factors like 'Other improper action' (3 crashes) and 'Failed to yield right of way' (2 crashes) from March 2024 were not present in March 2025's contributing factors.

Officer-Reported Primary Contributing Cause

No improper driving5 (25%)-37.5%prior 8
Followed too closely4 (20%)
Inattention4 (20%)
Failure to keep in proper lane or running off road2 (10%)
Made an improper turn1 (5%)
Exceeded authorized speed limit1 (5%)
Driving too fast for conditions1 (5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Daylight' conditions decreased from 14 in March 2024 to 9 in March 2025, and those in 'Dark - lighted roadway' conditions decreased from 7 to 4. Conversely, crashes in 'Dusk' conditions increased from 1 to 3, and 'Dawn' crashes increased from 0 to 1. The number of crashes on 'Dry' road surfaces decreased from 17 to 15, and on 'Wet' surfaces from 7 to 5.

Weather

Clear10 (50.0%)
-28.6%prior 14
Clear/Clear3 (15.0%)
Cloudy2 (10.0%)
Rain2 (10.0%)
Rain/Rain2 (10.0%)
Clear/Unknown1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash

Lighting

Daylight9 (45.0%)
-35.7%prior 14
Dark - lighted roadway4 (20.0%)
-42.9%prior 7
Dark - roadway not lighted3 (15.0%)
Dusk3 (15.0%)
Dawn1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field

Road Surface

Dry15 (75.0%)
-11.8%prior 17
Wet5 (25.0%)
-28.6%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (35 vehicles)

1
NISSAN6 (17.1%)
2
HONDA5 (14.3%)
0.0%prior 5
3
FORD4 (11.4%)
-33.3%prior 6
4
CHEVROLET4 (11.4%)
-20.0%prior 5
5
TOYOTA3 (8.6%)
-50.0%prior 6
6
GMC2 (5.7%)
7
VOLKSWAGEN1 (2.9%)
8
HYUNDAI1 (2.9%)
9
KIA1 (2.9%)
10
LEXUS1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records

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

Sex Distribution (35 persons with recorded sex)

Male23 (65.7%)
-11.5%prior 26
Female12 (34.3%)
-40.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 15 mph speed zone decreased from 2 in March 2024 to 0 in March 2025, and those in the 25 mph zone decreased from 4 to 3. Crashes in the 50 mph speed zone saw a slight increase from 3 to 4. Fatal rates remained at zero across all speed zones for both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-03-01 through 2025-03-31 (31 days)
  • Geographic scope: LYNNFIELD, MA
  • Total crash records analyzed: 20
  • Total persons involved: 40
  • Total vehicles involved: 35

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). "LYNNFIELD, MA Crash Intelligence Report: March 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lynnfield/march-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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Lynnfield, MA Crash Report — March 2025 | ThatCarHitMe.com