Monthly Traffic Safety Analysis

88 CRASHES IN
ANDOVER, MA
FEBRUARY 2026

All metrics benchmarked againstFebruary 2025

ANDOVER experienced a notable decrease in overall crashes, with 88 incidents in February 2026 compared to 120 in February 2025, representing a 26.7% reduction. The most significant year-over-year shift was in hit-and-run crashes, which decreased by 81.3%, from 16 incidents to 3.

88

-26.7%was 120

Total Crash Events

0

Persons Killed

19

-17.4%was 23

Persons Injured

3

-81.3%was 16

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. 1 crash with unreported severity is 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 crash incidents in ANDOVER showed a declining trend, decreasing from 120 crashes in February 2025 to 88 crashes in February 2026. This represents a 26.7% reduction in total crashes year-over-year. Fatalities remained at zero in both periods.

3

Hit-and-Run Crashes — February 2026

-81.3% vs prior (16)

Hit-and-run crashes decreased significantly from 16 incidents in February 2025 to 3 incidents in February 2026. This represents an 81.3% reduction in hit-and-run crash count, and the hit-and-run rate decreased from 13.3% to 3.4% of total crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

19

Motorists Injured

Prior: 23-17.4%

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 temporal patterns for crashes in ANDOVER shifted year-over-year. In February 2026, the peak day for crashes was Saturday with 21 incidents, and the peak hour was 9 AM with 8 incidents. This contrasts with February 2025, where Tuesday was the peak day with 21 crashes, and 6 PM was the peak hour with 10 crashes.

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

Fatal crashes remained at zero for both February 2025 and February 2026. Total injuries decreased from 23 in the prior period to 19 in the current period, a 17.4% reduction. The proportion of minor injuries increased from 7.5% to 13.6% of total crashes, while possible injuries saw a slight decrease from 6.7% to 5.7%.

Outcome by Severity (Crash Events)

Minor Injury12minor injury crashes13.6%
33.3%prior 9
Possible Injury5possible injury crashes5.7%
-37.5%prior 8
No Injury70no injury crashes79.5%
-27.8%prior 97

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

Crashes attributed to 'No improper driving' decreased significantly from 25 in February 2025 to 9 in February 2026, a 64% reduction in count. 'Driving too fast for conditions' also saw a substantial decrease, falling from 24 crashes to 9 crashes, a 62.5% reduction in count. Conversely, 'Failed to yield right of way' crashes slightly increased from 14 to 15, and 'Failure to keep in proper lane or running off road' increased from 11 to 12.

Officer-Reported Primary Contributing Cause

Failed to yield right of way15 (17%)7.1%prior 14
Failure to keep in proper lane or running off road12 (13.6%)9.1%prior 11
Followed too closely10 (11.4%)-23.1%prior 13
No improper driving9 (10.2%)-64.0%prior 25
Driving too fast for conditions9 (10.2%)-62.5%prior 24
Inattention8 (9.1%)-20.0%prior 10
Disregarded traffic signs, signals, road markings6 (6.8%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway4 (4.5%)
Operating defective equipment2 (2.3%)
Visibility obstructed2 (2.3%)

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

Crashes occurring in 'Clear' weather conditions (including 'Clear/Clear') decreased from a combined 76 incidents in February 2025 to 53 incidents in February 2026. Crashes on 'Dry' road surfaces decreased from 61 to 54, while those on 'Ice' decreased from 13 to 4. Incidents during 'Daylight' conditions also saw a reduction, from 66 to 55.

Weather

Clear27 (30.7%)
-15.6%prior 32
Clear/Clear26 (29.5%)
-40.9%prior 44
Cloudy6 (6.8%)
Snow/Snow5 (5.7%)
Snow5 (5.7%)
-54.5%prior 11
Cloudy/Clear4 (4.5%)
Snow/Blowing sand, snow4 (4.5%)
Snow/Cloudy4 (4.5%)
Snow/Sleet, hail (freezing rain or drizzle)2 (2.3%)
-60.0%prior 5
Cloudy/Cloudy2 (2.3%)

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

Lighting

Daylight55 (62.5%)
-16.7%prior 66
Dark - lighted roadway22 (25.0%)
-29.0%prior 31
Dark - roadway not lighted6 (6.8%)
-53.8%prior 13
Dusk3 (3.4%)
Dawn2 (2.3%)
-60.0%prior 5

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

Road Surface

Dry54 (61.4%)
-11.5%prior 61
Snow18 (20.5%)
-21.7%prior 23
Wet11 (12.5%)
-35.3%prior 17
Ice4 (4.5%)
-69.2%prior 13
Slush1 (1.1%)

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 211 in February 2025 to 160 in February 2026. HONDA, the top make in February 2025 with 41 vehicles, saw its involvement drop to 23 vehicles, being surpassed by TOYOTA which had 24 vehicles in February 2026. Person involvement for age groups 35-44 and 45-54 experienced the largest decreases, dropping from 56 to 33 and 62 to 22 respectively.

Top Vehicle Makes (160 vehicles)

1
TOYOTA24 (15%)
-7.7%prior 26
2
HONDA23 (14.4%)
-43.9%prior 41
3
FORD11 (6.9%)
-26.7%prior 15
4
NISSAN10 (6.3%)
11.1%prior 9
5
CHEVROLET9 (5.6%)
-47.1%prior 17
6
HYUNDAI9 (5.6%)
7
SUBARU7 (4.4%)
0.0%prior 7
8
LEXUS6 (3.8%)
9
KIA6 (3.8%)
10
TESL5 (3.1%)

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

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

Sex Distribution (190 persons with recorded sex)

Male121 (63.7%)
-9.0%prior 133
Female69 (36.3%)
-42.0%prior 119

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 occurring in 65 mph speed zones decreased from 39 in February 2025 to 25 in February 2026, a 35.9% reduction. Conversely, crashes in 25 mph speed zones increased from 27 to 34, a 25.9% rise. No fatal crashes were recorded in any speed zone for 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: ANDOVER, MA
  • Total crash records analyzed: 88
  • Total persons involved: 205
  • Total vehicles involved: 160

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). "ANDOVER, 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/andover/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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Andover, MA Crash Report — February 2026 | ThatCarHitMe.com