Monthly Traffic Safety Analysis

107 CRASHES IN
HAVERHILL, MA
MARCH 2025

All metrics benchmarked againstMarch 2024

Total crashes in Haverhill decreased from 135 in March 2024 to 107 in March 2025, representing a 20.74% reduction year-over-year. The most notable shift was a 41.67% decrease in total injuries, falling from 48 to 28.

107

-20.7%was 135

Total Crash Events

0

Persons Killed

28

-41.7%was 48

Persons Injured

15

-42.3%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. 12 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crash incidents year-over-year. Total crashes decreased by 20.74%, from 135 crashes in March 2024 to 107 crashes in March 2025.

15

Hit-and-Run Crashes — March 2025

-42.3% vs prior (26)

The number of hit-and-run crashes decreased from 26 in March 2024 to 15 in March 2025. This resulted in a decrease in the hit-and-run rate from 19.3% to 14% of total crashes, indicating a downward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 30.0%

1

Cyclists Injured

Prior: 0%

24

Motorists Injured

Prior: 42-42.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Saturday in both periods, though the count decreased from 32 crashes in March 2024 to 22 crashes in March 2025. The peak hour for crashes shifted from 12p (12 crashes) in March 2024 to 9a (14 crashes) in March 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both March 2024 and March 2025. Total injuries decreased from 48 to 28, a 41.67% reduction year-over-year. Serious injuries decreased from 3 to 2, minor injuries from 25 to 18, and possible injuries from 7 to 4.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.9%
-33.3%prior 3
Minor Injury18minor injury crashes16.8%
-28.0%prior 25
Possible Injury4possible injury crashes3.7%
-42.9%prior 7
No Injury71no injury crashes66.4%
-17.4%prior 86

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the top contributing factor, decreasing from 43 crashes in March 2024 to 32 crashes in March 2025. 'Failed to yield right of way' saw an increase in count from 10 to 20 crashes, while 'No improper driving' decreased significantly from 15 to 4 crashes. The share of crashes attributed to 'Inattention' was 31.9% in March 2024 and 29.9% in March 2025.

Officer-Reported Primary Contributing Cause

Inattention32 (29.9%)-25.6%prior 43
Failed to yield right of way20 (18.7%)100.0%prior 10
Failure to keep in proper lane or running off road7 (6.5%)0.0%prior 7
Followed too closely6 (5.6%)0.0%prior 6
Disregarded traffic signs, signals, road markings4 (3.7%)-42.9%prior 7
No improper driving4 (3.7%)-73.3%prior 15
Other improper action4 (3.7%)
Over-correcting/over-steering4 (3.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (1.9%)
Glare2 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather decreased from 81 to 75, and 'Rain' condition crashes decreased from 15 to 3. Crashes on 'Wet' road surfaces significantly decreased from 28 in March 2024 to 9 in March 2025. Crashes during 'Daylight' hours decreased from 86 to 76, and 'Dark - lighted roadway' crashes decreased from 31 to 23.

Weather

Clear75 (71.4%)
-7.4%prior 81
Cloudy12 (11.4%)
-33.3%prior 18
Clear/Clear9 (8.6%)
Rain3 (2.9%)
-80.0%prior 15
Rain/Cloudy2 (1.9%)
Sleet, hail (freezing rain or drizzle)1 (1.0%)
-80.0%prior 5
Clear/Rain1 (1.0%)
Cloudy/Clear1 (1.0%)
Cloudy/Rain1 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash

Lighting

Daylight76 (73.1%)
-11.6%prior 86
Dark - lighted roadway23 (22.1%)
-25.8%prior 31
Dark - roadway not lighted2 (1.9%)
-77.8%prior 9
Dusk2 (1.9%)
Dawn1 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field

Road Surface

Dry95 (90.5%)
-2.1%prior 97
Wet9 (8.6%)
-67.9%prior 28
Ice1 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 232 to 184 year-over-year. Honda remained the top vehicle make involved, though its count decreased from 44 to 34. In terms of persons involved, the 0-15 age group saw an increase from 18 to 34, and the 26-34 age group increased from 44 to 56.

Top Vehicle Makes (184 vehicles)

1
HONDA34 (18.5%)
-22.7%prior 44
2
FORD18 (9.8%)
12.5%prior 16
3
TOYOTA17 (9.2%)
-41.4%prior 29
4
SUBARU14 (7.6%)
55.6%prior 9
5
HYUNDAI12 (6.5%)
33.3%prior 9
6
CHEVROLET11 (6%)
-42.1%prior 19
7
NISSAN8 (4.3%)
-52.9%prior 17
8
DODGE7 (3.8%)
40.0%prior 5
9
ACURA6 (3.3%)
10
FRHT6 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records

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

Sex Distribution (230 persons with recorded sex)

Male139 (60.4%)
-10.9%prior 156
Female91 (39.6%)
-9.9%prior 101

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 46 to 37, while crashes in the 35 mph zone increased from 27 to 32. A notable decrease was observed in the 65 mph zone, where crashes fell from 18 to 3. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-03-01 through 2025-03-31 (31 days)
  • Geographic scope: HAVERHILL, MA
  • Total crash records analyzed: 107
  • Total persons involved: 254
  • Total vehicles involved: 184

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 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/haverhill/march-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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Haverhill, MA Crash Report — March 2025 | ThatCarHitMe.com