Yearly Traffic Safety Analysis

232 CRASHES IN
LYNNFIELD, MA
2025

All metrics benchmarked against2024

In 2025, Lynnfield recorded 232 total vehicle crashes, a 13.8% decrease from the 269 crashes reported in 2024. The total number of injuries also fell from 93 to 69, a 25.8% reduction. Notably, there were no crash-related fatalities in 2025, compared to one fatality in the prior year.

232

-13.8%was 269

Total Crash Events

0

-100.0%was 1

Persons Killed

69

-25.8%was 93

Persons Injured

23

-23.3%was 30

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. 2 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, Lynnfield experienced a downward trend in traffic crashes year-over-year. Total crashes declined by 13.8%, from 269 in 2024 to 232 in 2025. This trend extended to crash outcomes, with total injuries decreasing by 25.8% and fatalities dropping from one to zero.

23

Hit-and-Run Crashes — 2025

-23.3% vs prior (30)

The incidence of hit-and-run crashes in Lynnfield decreased from 2024 to 2025. The total count of hit-and-run incidents fell by 23.3%, from 30 to 23. The hit-and-run rate, expressed as a percentage of all crashes, also trended downward, declining from 11.2% in the prior year to 9.9% in the current year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

1

Pedestrians Injured

Prior: 0%

3

Cyclists Injured

Prior: 0%

65

Motorists Injured

Prior: 92-29.3%

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 in Lynnfield showed some shifts between 2024 and 2025. The peak day for crashes moved from Wednesday (55 crashes) in 2024 to Thursday (42 crashes) in 2025. The peak hour also shifted later, from the 4 p.m. hour in the prior year (23 crashes) to the 5 p.m. hour in the current year (25 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

Crash severity improved year-over-year, with fatal crashes decreasing from one in 2024 to zero in 2025. While total injury-related crashes decreased, the number of serious injury crashes increased from one to four. The proportion of crashes involving possible injuries fell from 10.4% to 7.8%, while the share of no-injury crashes rose slightly from 73.6% to 74.6% of all incidents.

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes1.7%
300.0%prior 1
Minor Injury35minor injury crashes15.1%
-10.3%prior 39
Possible Injury18possible injury crashes7.8%
-35.7%prior 28
No Injury173no injury crashes74.6%
-12.6%prior 198

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 most frequently cited improper driving action in both years was 'Followed too closely,' with the count of these crashes rising from 47 in 2024 to 49 in 2025. In contrast, crashes attributed to 'Inattention' decreased significantly, with the count falling from 30 to 16. The number of crashes involving 'Failure to keep in proper lane or running off road' increased from 11 in the prior year to 17 in the current year.

Officer-Reported Primary Contributing Cause

No improper driving79 (34.1%)31.7%prior 60
Followed too closely49 (21.1%)4.3%prior 47
Failure to keep in proper lane or running off road17 (7.3%)54.5%prior 11
Inattention16 (6.9%)-46.7%prior 30
Other improper action8 (3.4%)-38.5%prior 13
Driving too fast for conditions5 (2.2%)-28.6%prior 7
Exceeded authorized speed limit5 (2.2%)-37.5%prior 8
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway5 (2.2%)
Disregarded traffic signs, signals, road markings4 (1.7%)-20.0%prior 5
Distracted3 (1.3%)-57.1%prior 7

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

The environmental conditions under which crashes occurred were broadly similar between 2024 and 2025. In both years, a majority of incidents happened in daylight, accounting for 66.9% of crashes in 2024 and 64.7% in 2025. Road surface conditions were also consistent, with over 82% of crashes in both periods taking place on dry roads. There were no significant shifts in the proportion of crashes occurring during adverse weather like rain or snow.

Weather

Clear128 (55.2%)
-29.7%prior 182
Clear/Clear48 (20.7%)
242.9%prior 14
Cloudy14 (6.0%)
-44.0%prior 25
Rain13 (5.6%)
-7.1%prior 14
Clear/Unknown9 (3.9%)
28.6%prior 7
Rain/Rain4 (1.7%)
Snow3 (1.3%)
Cloudy/Cloudy3 (1.3%)
Rain/Cloudy3 (1.3%)
Snow/Snow1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight150 (64.7%)
-16.7%prior 180
Dark - lighted roadway53 (22.8%)
-13.1%prior 61
Dark - roadway not lighted13 (5.6%)
-7.1%prior 14
Dusk12 (5.2%)
20.0%prior 10
Dawn4 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry193 (83.2%)
-12.7%prior 221
Wet31 (13.4%)
-16.2%prior 37
Snow5 (2.2%)
Ice2 (0.9%)
Water (standing, moving)1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The vehicle makes most frequently involved in crashes remained consistent, with Toyota, Honda, and Ford holding the top three spots in both 2024 and 2025. Regarding the demographics of individuals involved, there was a slight shift in age distribution. The proportion of people in the 26-34 age group decreased from representing 19.8% of all persons involved in 2024 to 17.0% in 2025. Other age groups saw their representation remain relatively stable year-over-year.

Top Vehicle Makes (438 vehicles)

1
TOYOTA61 (13.9%)
-15.3%prior 72
2
HONDA49 (11.2%)
-24.6%prior 65
3
FORD47 (10.7%)
0.0%prior 47
4
CHEVROLET33 (7.5%)
-17.5%prior 40
5
NISSAN28 (6.4%)
-24.3%prior 37
6
JEEP22 (5%)
-15.4%prior 26
7
SUBARU21 (4.8%)
-16.0%prior 25
8
HYUNDAI14 (3.2%)
7.7%prior 13
9
ACURA12 (2.7%)
50.0%prior 8
10
BMW12 (2.7%)
9.1%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (458 persons with recorded sex)

Male257 (56.1%)
-18.9%prior 317
Female199 (43.4%)
-19.8%prior 248
X / Unspecified2 (0.4%)

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

Crashes decreased across most posted speed limit zones from 2024 to 2025. The largest drop in crash volume was seen in 55 mph zones, where incidents fell from 83 to 57. The single fatal crash in 2024 occurred in a 55 mph zone; in 2025, there were no fatalities recorded in any speed zone. There was no significant shift in the proportion of crashes from lower to higher speed zones, but rather a general reduction in incidents.

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: LYNNFIELD, MA
  • Total crash records analyzed: 232
  • Total persons involved: 517
  • Total vehicles involved: 438

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: 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/lynnfield/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

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Lynnfield, MA Crash Report — 2025 | ThatCarHitMe.com