ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · HAVERHILL, MA · MARCH 2023
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/haverhill/march-2023-report
Monthly Traffic Safety Analysis
132 CRASHES IN
HAVERHILL, MA
MARCH 2023
In March 2023, Haverhill experienced 132 total crashes, a 22.22% increase compared to the 108 crashes recorded in March 2022. The most significant year-over-year shift was a 114.29% increase in speeding-related crashes, rising from 7 in the prior period to 15 in the current period.
132
▲ 22.2%was 108
Total Crash Events
0
Persons Killed
33
▲ 57.1%was 21
Persons Injured
16
▼ -23.8%was 21
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. 10 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a rise in crash incidents, with total crashes increasing by 22.22% from 108 in March 2022 to 132 in March 2023. Concurrently, total injuries saw a substantial increase of 57.14%, from 21 to 33.
16
Hit-and-Run Crashes — March 2023
▼ -23.8% vs prior (21)
Hit-and-run crashes decreased by 5 incidents, from 21 in March 2022 to 16 in March 2023. Consequently, the hit-and-run rate declined from 19.4% in the prior period to 12.1% in the current period, indicating a downward trend in the proportion of crashes involving hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
32
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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, with Friday, Monday, and Tuesday each recording 22 crashes in March 2023, compared to Wednesday with 21 crashes in March 2022. The peak hour also shifted from 1 PM with 10 crashes in March 2022 to 4 PM with 14 crashes in March 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities in either March 2022 or March 2023. Total injuries increased by 57.14%, from 21 in March 2022 to 33 in March 2023. Minor injuries increased from 16 to 17, while possible injuries increased from 2 to 3; serious injuries decreased from 1 to 0.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'Driving too fast for conditions' saw a 140% increase, rising from 5 in March 2022 to 12 in March 2023. 'Inattention' crashes increased by 23.3%, from 30 to 37, while 'No improper driving' crashes decreased by 27.8%, from 18 to 13. 'Followed too closely' crashes increased by 50%, from 6 to 9, and 'Failed to yield right of way' crashes decreased by 13.3%, from 15 to 13.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 77 in March 2022 to 79 in March 2023. Crashes in 'Snow' conditions saw a substantial increase from 4 to 14, while crashes on 'Dry' road surfaces increased from 82 to 92. Crashes during 'Daylight' hours increased from 70 to 92, and crashes in 'Dark - lighted roadway' conditions decreased from 29 to 27.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 33.1%, from 178 in March 2022 to 237 in March 2023. Honda vehicles involved in crashes increased by 69.2% (from 26 to 44), while Chevrolet saw a 180% increase (from 10 to 28). Ford vehicles involved decreased by 23.8% (from 21 to 16), and Nissan vehicles involved decreased by 11.8% (from 17 to 15).
Top Vehicle Makes (237 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records
33 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (282 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events
Speed Limit Zones
The number of crashes occurring in 30 mph zones increased by 21.6%, from 37 in March 2022 to 45 in March 2023. Crashes in 65 mph zones saw a significant increase of 128.6%, rising from 7 to 16. The number of crashes in 35 mph zones remained stable at 32 for both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-03-01 through 2023-03-31 (31 days)
- Geographic scope: HAVERHILL, MA
- Total crash records analyzed: 132
- Total persons involved: 324
- Total vehicles involved: 237
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). "HAVERHILL, MA Crash Intelligence Report: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/haverhill/march-2023-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: 2023-03-01 – 2023-03-31
Generated: June 21, 2026 · All rights reserved