Monthly Traffic Safety Analysis

158 CRASHES IN
LAWRENCE, MA
JANUARY 2026

All metrics benchmarked againstJanuary 2025

Total crashes in LAWRENCE, MA decreased by 6.51%, from 169 in January 2025 to 158 in January 2026. A significant year-over-year shift was the absence of fatalities in January 2026, compared to 2 fatalities in January 2025.

158

-6.5%was 169

Total Crash Events

0

-100.0%was 2

Persons Killed

43

-23.2%was 56

Persons Injured

5

150.0%was 2

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. 5 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in LAWRENCE, MA showed a downward trend year-over-year, decreasing by 11 crashes from 169 in January 2025 to 158 in January 2026. This represents a 6.51% reduction in total crashes for the month.

5

Hit-and-Run Crashes — January 2026

150.0% vs prior (2)

Hit-and-run crashes increased significantly year-over-year, rising from 2 in January 2025 to 5 in January 2026. This caused the hit-and-run rate to increase from 1.2% to 3.2% of all crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Motorists Killed

Prior: 1-100.0%

2

Pedestrians Injured

Prior: 8-75.0%

41

Motorists Injured

Prior: 48-14.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · 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 Thursday with 31 crashes in January 2025 to Wednesday with 29 crashes in January 2026. The peak hour also changed, moving from 8 AM with 20 crashes in January 2025 to 3 PM with 18 crashes in January 2026.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 2 in January 2025 to 0 in January 2026, resulting in a fatal rate reduction from 1.18% to 0%. Total injuries also decreased from 56 to 43 year-over-year, with serious injuries decreasing from 4 to 1 and possible injuries decreasing from 14 to 6.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes0.6%
-75.0%prior 4
Minor Injury19minor injury crashes12%
-9.5%prior 21
Possible Injury6possible injury crashes3.8%
-57.1%prior 14
No Injury127no injury crashes80.4%
1.6%prior 125

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor shifted from 'Inattention' (36 crashes) in January 2025 to 'No improper driving' (55 crashes) in January 2026. 'No improper driving' crashes increased by 28, a 103.7% increase, while 'Inattention' crashes decreased by 24, a 66.7% decrease. 'Failed to yield right of way' crashes decreased by 10, a 37.0% decrease, moving from 27 crashes to 17.

Officer-Reported Primary Contributing Cause

No improper driving55 (34.8%)103.7%prior 27
Failed to yield right of way17 (10.8%)-37.0%prior 27
Inattention12 (7.6%)-66.7%prior 36
Followed too closely8 (5.1%)14.3%prior 7
Driving too fast for conditions8 (5.1%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway6 (3.8%)
Disregarded traffic signs, signals, road markings4 (2.5%)-20.0%prior 5
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (2.5%)
Distracted3 (1.9%)
Other improper action3 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 110 in January 2025 to 76 in January 2026, while 'Snow' related crashes increased from 11 to 29. Similarly, crashes on 'Dry' road surfaces decreased from 126 to 75, but crashes on 'Snow' surfaces increased from 12 to 32 and 'Wet' surfaces increased from 25 to 31.

Weather

Clear76 (48.1%)
-30.9%prior 110
Snow29 (18.4%)
163.6%prior 11
Clear/Clear27 (17.1%)
3.8%prior 26
Cloudy10 (6.3%)
42.9%prior 7
Blowing sand, snow3 (1.9%)
Sleet, hail (freezing rain or drizzle)3 (1.9%)
Snow/Cloudy2 (1.3%)
Rain2 (1.3%)
Unknown/Unknown1 (0.6%)
Clear/Unknown1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash

Lighting

Daylight91 (58.0%)
-3.2%prior 94
Dark - lighted roadway50 (31.8%)
-10.7%prior 56
Dusk7 (4.5%)
-12.5%prior 8
Dark - roadway not lighted6 (3.8%)
-25.0%prior 8
Dawn2 (1.3%)
Dark - unknown roadway lighting1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field

Road Surface

Dry75 (47.8%)
-40.5%prior 126
Snow32 (20.4%)
166.7%prior 12
Wet31 (19.7%)
24.0%prior 25
Ice14 (8.9%)
Slush5 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 354 in January 2025 to 326 in January 2026. HONDA remained the top make involved, though its count decreased from 114 to 94, while FORD vehicles involved increased from 27 to 39.

Top Vehicle Makes (326 vehicles)

1
HONDA94 (28.8%)
-17.5%prior 114
2
TOYOTA43 (13.2%)
-10.4%prior 48
3
FORD39 (12%)
44.4%prior 27
4
CHEVROLET14 (4.3%)
-17.6%prior 17
5
ACURA14 (4.3%)
7.7%prior 13
6
NISSAN11 (3.4%)
0.0%prior 11
7
JEEP11 (3.4%)
-31.3%prior 16
8
KIA10 (3.1%)
11.1%prior 9
9
SUBARU9 (2.8%)
-10.0%prior 10
10
HYUNDAI8 (2.5%)
-11.1%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Vehicle unit records

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

Sex Distribution (343 persons with recorded sex)

Male221 (64.4%)
-8.7%prior 242
Female122 (35.6%)
-26.9%prior 167

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased slightly from 146 in January 2025 to 138 in January 2026, with fatalities in this zone decreasing from 1 to 0. The 65 mph speed zone saw 5 crashes in both periods, but fatalities in this zone decreased from 1 in January 2025 to 0 in January 2026.

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

Data Coverage

  • Reporting period: 2026-01-01 through 2026-01-31 (31 days)
  • Geographic scope: LAWRENCE, MA
  • Total crash records analyzed: 158
  • Total persons involved: 400
  • Total vehicles involved: 326

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