Monthly Traffic Safety Analysis

141 CRASHES IN
HAVERHILL, MA
FEBRUARY 2026

All metrics benchmarked againstFebruary 2025

Total crashes in HAVERHILL decreased by 13.5% from 163 in February 2025 to 141 in February 2026. Despite this reduction in total crashes, the number of total injuries rose by 42.3%, from 26 to 37, marking a significant shift in crash outcomes.

141

-13.5%was 163

Total Crash Events

0

Persons Killed

37

42.3%was 26

Persons Injured

25

-3.8%was 26

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, HAVERHILL experienced a decrease in total crashes, falling from 163 in February 2025 to 141 in February 2026, a 13.5% reduction. However, total injuries increased by 42.3%, from 26 to 37, while fatalities remained at zero in both periods.

25

Hit-and-Run Crashes — February 2026

-3.8% vs prior (26)

The number of hit-and-run crashes slightly decreased from 26 in February 2025 to 25 in February 2026. However, the hit-and-run rate increased from 16% to 17.7% of all crashes, indicating a higher proportion of crashes involved hit-and-run incidents despite the lower absolute count.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

37

Motorists Injured

Prior: 2360.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · 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 Saturday, which had 35 crashes in February 2025, to Thursday and Friday, both recording 26 crashes in February 2026. The peak crash hour remained 2p in both periods, though the count decreased from 19 crashes in February 2025 to 14 crashes in February 2026.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While there were no fatalities in either period, total injuries increased by 42.3%, from 26 in February 2025 to 37 in February 2026. Minor injuries (severity B) saw a count increase from 11 to 15, and possible injuries (severity C) increased from 5 to 9, leading to a higher proportion of injury crashes in the current period.

Outcome by Severity (Crash Events)

Minor Injury15minor injury crashes10.6%
36.4%prior 11
Possible Injury9possible injury crashes6.4%
80.0%prior 5
No Injury102no injury crashes72.3%
-20.9%prior 129

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'Inattention,' saw a significant increase of 20 crashes, rising from 33 in February 2025 to 53 in February 2026, and its share of crashes increased from 20.2% to 37.6%. Conversely, 'Failed to yield right of way' decreased by 6 crashes, from 24 to 18, and 'No improper driving' decreased by 3 crashes, from 18 to 15, indicating a shift in the primary causes of crashes.

Officer-Reported Primary Contributing Cause

Inattention53 (37.6%)60.6%prior 33
Failed to yield right of way18 (12.8%)-25.0%prior 24
No improper driving15 (10.6%)-16.7%prior 18
Failure to keep in proper lane or running off road8 (5.7%)-11.1%prior 9
Driving too fast for conditions7 (5%)-12.5%prior 8
Other improper action6 (4.3%)
Made an improper turn3 (2.1%)-40.0%prior 5
Disregarded traffic signs, signals, road markings2 (1.4%)
Followed too closely2 (1.4%)-77.8%prior 9
Glare2 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift in crash conditions, with crashes occurring in 'Snow' conditions decreasing from 29 in February 2025 to 9 in February 2026, a reduction of 20 crashes. Crashes on 'Dry' road surfaces increased by 16, from 90 to 106, while crashes during 'Daylight' decreased by 20, from 100 to 80. Overall, the data indicates a decrease in crashes under adverse weather and road conditions.

Weather

Clear100 (71.4%)
14.9%prior 87
Clear/Clear12 (8.6%)
50.0%prior 8
Cloudy11 (7.9%)
-38.9%prior 18
Snow9 (6.4%)
-69.0%prior 29
Snow/Blowing sand, snow3 (2.1%)
Snow/Snow3 (2.1%)
Snow/Sleet, hail (freezing rain or drizzle)1 (0.7%)
-83.3%prior 6
Snow/Cloudy1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Weather condition at time of crash

Lighting

Daylight80 (57.6%)
-20.0%prior 100
Dark - lighted roadway40 (28.8%)
-7.0%prior 43
Dark - roadway not lighted10 (7.2%)
25.0%prior 8
Dusk9 (6.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Lighting condition field

Road Surface

Dry106 (75.7%)
17.8%prior 90
Snow23 (16.4%)
-36.1%prior 36
Wet10 (7.1%)
-50.0%prior 20
Sand, mud, dirt, oil, gravel1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 290 in February 2025 to 258 in February 2026. Among top makes, HONDA, TOYOTA, and FORD all saw decreases in involvement, while SUBARU involvement increased by 11 vehicles, from 8 to 19. The age group 0-15 saw a substantial increase in persons involved, rising from 19 to 51, a change of 32 persons.

Top Vehicle Makes (258 vehicles)

1
HONDA42 (16.3%)
-26.3%prior 57
2
TOYOTA34 (13.2%)
-26.1%prior 46
3
FORD28 (10.9%)
-30.0%prior 40
4
SUBARU19 (7.4%)
137.5%prior 8
5
CHEVROLET13 (5%)
-31.6%prior 19
6
NISSAN12 (4.7%)
-50.0%prior 24
7
JEEP11 (4.3%)
120.0%prior 5
8
KIA9 (3.5%)
50.0%prior 6
9
MERCEDES-BENZ7 (2.7%)
10
HYUNDAI7 (2.7%)
-22.2%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Vehicle unit records

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

Sex Distribution (310 persons with recorded sex)

Male189 (61.0%)
14.5%prior 165
Female121 (39.0%)
-6.2%prior 129

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone increased by 6, from 59 in February 2025 to 65 in February 2026. Conversely, crashes in the 35 mph speed zone decreased by 21, from 41 to 20, marking the largest shift among speed zones. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · 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: 2026-02-01 through 2026-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2026-02-01 through 2026-02-28 (28 days)
  • Geographic scope: HAVERHILL, MA
  • Total crash records analyzed: 141
  • Total persons involved: 356
  • Total vehicles involved: 258

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: February 2026." Published June 21, 2026. Reporting period: 2026-02-01 to 2026-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/haverhill/february-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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Haverhill, MA Crash Report — February 2026 | ThatCarHitMe.com