Monthly Traffic Safety Analysis

169 CRASHES IN
LAWRENCE, MA
JANUARY 2025

All metrics benchmarked againstJanuary 2024

In January 2025, Lawrence experienced 169 total crashes, an 8.15% decrease compared to the 184 crashes recorded in January 2024. The most significant year-over-year shift was in fatalities, which increased from 0 in January 2024 to 2 in January 2025.

169

-8.2%was 184

Total Crash Events

2

Persons Killed

56

47.4%was 38

Persons Injured

2

-50.0%was 4

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. 3 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

The overall trend shows a decrease in total crashes, falling by 8.15% from 184 in January 2024 to 169 in January 2025. Despite this reduction in total crashes, the number of fatalities increased from 0 to 2, and total injuries rose from 38 to 56.

2

Hit-and-Run Crashes — January 2025

-50.0% vs prior (4)

Hit-and-run crashes decreased by 50%, falling from 4 incidents in January 2024 to 2 incidents in January 2025. Consequently, the hit-and-run rate also decreased from 2.2% to 1.2% year-over-year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

1

Motorists Killed

Prior: 0%

8

Pedestrians Injured

Prior: 4100.0%

48

Motorists Injured

Prior: 3441.2%

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 shifted from Tuesday, with 33 crashes in January 2024, to Wednesday and Thursday, both recording 31 crashes in January 2025. The peak hour for crashes also changed, moving from 3 PM with 21 crashes in January 2024 to 8 AM with 20 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

Fatal crashes increased from 0 in January 2024 to 2 in January 2025, resulting in a fatal crash rate increase from 0% to 1.2%. Serious injuries, coded as 'A', rose from 0 to 4, while minor injuries ('B') increased from 17 to 21. Possible injuries ('C') remained constant at 14 for both periods.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.2%
Serious Injury4serious injury crashes2.4%
Minor Injury21minor injury crashes12.4%
23.5%prior 17
Possible Injury14possible injury crashes8.3%
0.0%prior 14
No Injury125no injury crashes74%
-17.8%prior 152

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 leading contributing factor, 'Inattention,' increased by 14 crashes, from 22 in January 2024 to 36 in January 2025, representing a 63.6% increase in count. Conversely, 'No improper driving' decreased by 22 crashes, from 49 to 27, a 44.9% reduction in count. 'Failed to yield right of way' saw a slight decrease of 2 crashes, from 29 to 27.

Officer-Reported Primary Contributing Cause

Inattention36 (21.3%)63.6%prior 22
No improper driving27 (16%)-44.9%prior 49
Failed to yield right of way27 (16%)-6.9%prior 29
Failure to keep in proper lane or running off road8 (4.7%)60.0%prior 5
Followed too closely7 (4.1%)0.0%prior 7
Disregarded traffic signs, signals, road markings5 (3%)0.0%prior 5
Visibility obstructed4 (2.4%)-50.0%prior 8
Driving too fast for conditions4 (2.4%)-20.0%prior 5
Over-correcting/over-steering3 (1.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (1.8%)

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 (including 'Clear' and 'Clear/Clear') increased from 102 in January 2024 to 136 in January 2025. Crashes on dry road surfaces also increased significantly, from 94 to 126, while those on wet surfaces decreased from 49 to 25. The number of crashes during daylight hours decreased from 107 to 94.

Weather

Clear110 (65.1%)
15.8%prior 95
Clear/Clear26 (15.4%)
271.4%prior 7
Snow11 (6.5%)
-50.0%prior 22
Cloudy7 (4.1%)
-68.2%prior 22
Rain3 (1.8%)
-70.0%prior 10
Cloudy/Rain2 (1.2%)
Sleet, hail (freezing rain or drizzle)2 (1.2%)
-66.7%prior 6
Rain/Clear1 (0.6%)
Rain/Cloudy1 (0.6%)
Clear/Cloudy1 (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

Daylight94 (55.6%)
-12.1%prior 107
Dark - lighted roadway56 (33.1%)
-16.4%prior 67
Dark - roadway not lighted8 (4.7%)
60.0%prior 5
Dusk8 (4.7%)
Dawn2 (1.2%)
Other1 (0.6%)

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

Road Surface

Dry126 (74.6%)
34.0%prior 94
Wet25 (14.8%)
-49.0%prior 49
Snow12 (7.1%)
-60.0%prior 30
Ice3 (1.8%)
Other2 (1.2%)
Slush1 (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 decreased from 374 in January 2024 to 354 in January 2025. While Honda remained the top vehicle make, its involvement decreased from 118 to 114, whereas Toyota involvement increased from 41 to 48. In terms of person demographics, the 0-15 age group saw an increase from 25 to 38 persons involved, while the 55-64 age group decreased from 50 to 24 persons involved.

Top Vehicle Makes (354 vehicles)

1
HONDA114 (32.2%)
-3.4%prior 118
2
TOYOTA48 (13.6%)
17.1%prior 41
3
FORD27 (7.6%)
-18.2%prior 33
4
CHEVROLET17 (4.8%)
-10.5%prior 19
5
JEEP16 (4.5%)
-15.8%prior 19
6
ACURA13 (3.7%)
-35.0%prior 20
7
NISSAN11 (3.1%)
-47.6%prior 21
8
SUBARU10 (2.8%)
25.0%prior 8
9
KIA9 (2.5%)
10
HYUNDAI9 (2.5%)
12.5%prior 8

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

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

Sex Distribution (409 persons with recorded sex)

Male242 (59.2%)
-9.0%prior 266
Female167 (40.8%)
-4.0%prior 174

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 30 mph speed zones decreased from 156 to 146, but this zone recorded one fatal crash in January 2025 compared to none in January 2024. The 65 mph speed zone maintained 5 crashes in both periods, but also saw one fatal crash in January 2025, whereas no fatal crashes were reported in this zone in the prior period.

Fatal crashes by zone: 30 mph: 1 of 146 (0.685%) · 65 mph: 1 of 5 (20%)

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: LAWRENCE, MA
  • Total crash records analyzed: 169
  • Total persons involved: 462
  • Total vehicles involved: 354

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: 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/lawrence/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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Lawrence, MA Crash Report — January 2025 | ThatCarHitMe.com