ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LAWRENCE, MA · 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/lawrence/2025-annual-report
Yearly Traffic Safety Analysis
1,818 CRASHES IN
LAWRENCE, MA
2025
In 2025, Lawrence recorded 1,818 total vehicle crashes, a 7.1% decrease from the 1,957 crashes reported in 2024. Despite the overall reduction in collisions, the number of traffic fatalities increased from one in the prior year to four in the current year. Total reported injuries also saw a decrease from 715 to 652.
1,818
▼ -7.1%was 1,957
Total Crash Events
4
▲ 300.0%was 1
Persons Killed
652
▼ -8.8%was 715
Persons Injured
69
▲ 4.5%was 66
Hit-and-Run Crashes
Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 35 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 traffic crash incidents in Lawrence showed a downward trend year-over-year, with total crashes falling by 7.1% from 1,957 in 2024 to 1,818 in 2025. Similarly, the number of people injured in these crashes declined by 8.8%, from 715 to 652. However, this period saw a significant increase in fatalities, which rose from one to four.
69
Hit-and-Run Crashes — 2025
▲ 4.5% vs prior (66)
The number of hit-and-run incidents saw a slight increase, rising from 66 in 2024 to 69 in 2025. Despite an overall decrease in total crashes, the hit-and-run rate also trended upward, increasing from 3.4% to 3.8% of all crashes. This indicates that while overall collisions were down, hit-and-runs became a slightly larger proportion of the total incidents.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
49
Pedestrians Injured
7
Cyclists Injured
588
Motorists Injured
8
Other Injured
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 Lawrence saw some shifts between 2024 and 2025. The peak day for crashes moved from Friday, with 291 incidents in the prior year, to Monday, with 284 incidents in the current year. The peak hour for collisions remained consistent at 3 PM in both periods, although the volume of crashes during this hour decreased from 160 to 147.
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
While total crashes decreased, the severity of crashes worsened in 2025 compared to 2024. The number of fatal crashes increased from one to four, raising the fatal crash rate from 0.05% to 0.22% of all crashes. Crashes resulting in serious injuries also grew in both count and proportion, from 33 incidents (1.7% of total) in 2024 to 43 incidents (2.4% of total) in 2025.
Outcome by Severity (Crash Events)
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 leading contributing factors for crashes remained consistent, with 'Inattention' and 'Failed to yield right of way' ranking as the top two in both years. However, the count of crashes attributed to inattention increased by 9.9%, from 303 in 2024 to 333 in 2025. In contrast, crashes due to failing to yield the right of way decreased in count from 270 to 232. 'Followed too closely' saw a 21.2% reduction in count, falling from 99 to 78 incidents.
Officer-Reported Primary Contributing Cause
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 majority of crashes in both periods occurred in clear weather on dry roads during daylight hours. In 2025, crashes on wet road surfaces decreased from 294 to 231, and their share of total crashes fell from 15.0% to 12.7%. Crashes during daylight hours decreased in absolute numbers from 1,282 to 1,185, but their proportion of total crashes remained stable at approximately 65%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes remained consistent year-over-year, with Honda, Toyota, and Ford being the three most common in both 2024 and 2025. The number of vehicles from these top makes involved in collisions decreased, mirroring the overall reduction in crashes. The age demographics of persons involved also showed a stable pattern, with the 26-34 age group representing the largest cohort in both periods, followed by the 21-25 age group.
Top Vehicle Makes (3,740 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
591 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (4,323 persons with recorded sex)
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 in Lawrence were predominantly concentrated in 30 mph speed zones in both years, accounting for over 82% of all incidents where a speed limit was recorded. In 2025, there were 1,535 crashes in 30 mph zones, down from 1,620 the previous year. The locations of fatal crashes shifted; in 2024, the single fatality occurred in a 20 mph zone, whereas in 2025, two fatalities occurred in 30 mph zones, one in a 25 mph zone, and one in a 65 mph zone.
Fatal crashes by zone: 25 mph: 1 of 97 (1.031%) · 30 mph: 2 of 1,535 (0.13%) · 65 mph: 1 of 52 (1.923%)
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: LAWRENCE, MA
- Total crash records analyzed: 1,818
- Total persons involved: 4,870
- Total vehicles involved: 3,740
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: 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/lawrence/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved