Monthly Traffic Safety Analysis

163 CRASHES IN
LAWRENCE, MA
MARCH 2025

All metrics benchmarked againstMarch 2024

In March 2025, LAWRENCE experienced 163 total crashes, a decrease of 8.9% compared to the 179 crashes reported in March 2024. A notable year-over-year shift was observed in speeding-related crashes, which decreased significantly from 8 incidents in the prior period to just 1 in the current period.

163

-8.9%was 179

Total Crash Events

0

Persons Killed

48

-27.3%was 66

Persons Injured

4

-33.3%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. 2 crashes with unreported severity are not shown in the severity breakdown.

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

Total crashes in LAWRENCE decreased from 179 in March 2024 to 163 in March 2025, representing an 8.9% reduction year-over-year. This indicates a declining trend in overall crash incidents for the month.

4

Hit-and-Run Crashes — March 2025

-33.3% vs prior (6)

Hit-and-run crashes decreased from 6 in March 2024 to 4 in March 2025. The hit-and-run rate also saw a decline, moving from 3.4% of all crashes in the prior period to 2.5% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 30.0%

45

Motorists Injured

Prior: 63-28.6%

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 peak day for crashes shifted from Thursday in March 2024, with 32 incidents, to Saturday in March 2025, with 31 incidents. The peak hour for crashes also shifted from 2 PM (18 crashes) in the prior period to 4 PM (17 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

No fatalities were reported in either March 2024 or March 2025. Total injuries decreased from 66 in March 2024 to 48 in March 2025. Serious injuries decreased from 5 (2.8% of crashes) to 3 (1.8% of crashes) year-over-year, while minor injuries also saw a reduction from 29 (16.2%) to 20 (12.3%).

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes1.8%
-40.0%prior 5
Minor Injury20minor injury crashes12.3%
-31.0%prior 29
Possible Injury9possible injury crashes5.5%
50.0%prior 6
No Injury129no injury crashes79.1%
-5.1%prior 136

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 'Failed to yield right of way' decreased from 34 in March 2024 to 27 in March 2025. 'Inattention' also saw a slight decrease from 29 to 27 crashes. Conversely, crashes with 'No improper driving' as a factor increased from 21 to 31 year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving31 (19%)47.6%prior 21
Inattention27 (16.6%)-6.9%prior 29
Failed to yield right of way27 (16.6%)-20.6%prior 34
Other improper action10 (6.1%)25.0%prior 8
Distracted7 (4.3%)-12.5%prior 8
Disregarded traffic signs, signals, road markings6 (3.7%)-25.0%prior 8
Followed too closely6 (3.7%)-33.3%prior 9
Visibility obstructed5 (3.1%)
Operating defective equipment5 (3.1%)
Glare3 (1.8%)

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 'Clear' weather conditions increased from 99 to 108, while those in 'Rain' conditions significantly decreased from 36 to 10. Correspondingly, crashes on 'Dry' road surfaces increased from 121 to 147, and those on 'Wet' surfaces decreased from 52 to 16. The proportion of crashes occurring during daylight remained stable, with 115 in March 2025 compared to 113 in March 2024.

Weather

Clear108 (66.3%)
9.1%prior 99
Clear/Clear20 (12.3%)
81.8%prior 11
Cloudy15 (9.2%)
-6.3%prior 16
Rain10 (6.1%)
-72.2%prior 36
Rain/Rain3 (1.8%)
Cloudy/Rain2 (1.2%)
Sleet, hail (freezing rain or drizzle)1 (0.6%)
Clear/Blowing sand, snow1 (0.6%)
Cloudy/Clear1 (0.6%)
Cloudy/Cloudy1 (0.6%)

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

Lighting

Daylight115 (70.6%)
1.8%prior 113
Dark - lighted roadway42 (25.8%)
-14.3%prior 49
Dark - roadway not lighted3 (1.8%)
-70.0%prior 10
Dusk2 (1.2%)
Dawn1 (0.6%)

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

Road Surface

Dry147 (90.2%)
21.5%prior 121
Wet16 (9.8%)
-69.2%prior 52

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

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 373 in March 2024 to 334 in March 2025. Honda remained the top make involved, though its count decreased from 116 to 95, while Toyota-involved crashes increased from 36 to 47. There was a notable decrease in persons aged 16-20 involved in crashes, from 63 to 19.

Top Vehicle Makes (334 vehicles)

1
HONDA95 (28.4%)
-18.1%prior 116
2
TOYOTA47 (14.1%)
30.6%prior 36
3
FORD34 (10.2%)
-17.1%prior 41
4
CHEVROLET19 (5.7%)
-13.6%prior 22
5
NISSAN15 (4.5%)
-6.3%prior 16
6
ACURA14 (4.2%)
-6.7%prior 15
7
SUBARU13 (3.9%)
62.5%prior 8
8
JEEP12 (3.6%)
-14.3%prior 14
9
BMW8 (2.4%)
14.3%prior 7
10
DODGE6 (1.8%)
-33.3%prior 9

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

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

Sex Distribution (391 persons with recorded sex)

Male232 (59.3%)
-16.5%prior 278
Female159 (40.7%)
-17.2%prior 192

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

The majority of crashes in both periods occurred in 30 mph speed zones, though the count decreased from 155 in March 2024 to 136 in March 2025. Crashes in 25 mph zones increased from 4 to 12. No fatalities were reported in any speed zone during either period.

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: LAWRENCE, MA
  • Total crash records analyzed: 163
  • Total persons involved: 424
  • 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). "LAWRENCE, 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/lawrence/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

ThatCarHitMe.com · An Injuria.ai Company

Lawrence, MA Crash Report — March 2025 | ThatCarHitMe.com