Monthly Traffic Safety Analysis

60 CRASHES IN
REVERE, MA
FEBRUARY 2026

All metrics benchmarked againstFebruary 2025

In February 2026, Revere experienced 60 total crashes, a decrease from the 71 crashes reported in February 2025. This represents a 15.5% reduction in overall crash incidents year-over-year. A notable shift was the 150% increase in speeding-related crashes, rising from 2 to 5 incidents.

60

-15.5%was 71

Total Crash Events

0

Persons Killed

31

-11.4%was 35

Persons Injured

6

50.0%was 4

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.

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 Revere showed a downward trend year-over-year, with total crashes decreasing from 71 in February 2025 to 60 in February 2026. This represents a 15.5% reduction in crash volume for the month.

6

Hit-and-Run Crashes — February 2026

50.0% vs prior (4)

Hit-and-run crashes increased from 4 incidents in February 2025 to 6 incidents in February 2026, representing a 50% rise. Consequently, the hit-and-run rate also increased from 5.6% to 10% of all crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 2-50.0%

30

Motorists Injured

Prior: 32-6.3%

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 Friday in February 2025 (14 crashes) to Saturday in February 2026 (12 crashes). The peak hour also changed, moving from 5 PM in the prior period (7 crashes) to 2 PM in the current period (6 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

Fatalities remained at zero in both February 2025 and February 2026. Total injuries decreased from 35 to 31, an 11.4% reduction year-over-year. While minor injuries remained constant at 16, possible injuries increased from 4 to 8 incidents.

Outcome by Severity (Crash Events)

Minor Injury16minor injury crashes26.7%
0.0%prior 16
Possible Injury8possible injury crashes13.3%
100.0%prior 4
No Injury36no injury crashes60%
-25.0%prior 48

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, 'No improper driving,' decreased by 50%, from 18 incidents in February 2025 to 9 in February 2026. Conversely, 'Failed to yield right of way' incidents increased significantly by 200%, rising from 2 to 6. 'Inattention' also saw an increase, from 6 incidents to 8, representing a 33.3% rise.

Officer-Reported Primary Contributing Cause

No improper driving9 (15%)-50.0%prior 18
Inattention8 (13.3%)33.3%prior 6
Failed to yield right of way6 (10%)
Followed too closely3 (5%)
Disregarded traffic signs, signals, road markings3 (5%)
Exceeded authorized speed limit2 (3.3%)
Made an improper turn2 (3.3%)
Driving too fast for conditions2 (3.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.3%)
Other improper action2 (3.3%)

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 under 'Clear' weather conditions decreased from 42 to 38, while those in 'Cloudy' conditions increased from 4 to 9 incidents. Similarly, crashes on 'Dry' road surfaces decreased from 50 to 41, but 'Wet' road surface crashes increased from 6 to 9. Crashes during 'Daylight' increased from 32 to 38, whereas those in 'Dark - lighted roadway' conditions decreased from 28 to 18.

Weather

Clear38 (63.3%)
-9.5%prior 42
Cloudy9 (15.0%)
Clear/Clear4 (6.7%)
-42.9%prior 7
Snow2 (3.3%)
-66.7%prior 6
Snow/Rain2 (3.3%)
Clear/Snow1 (1.7%)
Snow/Snow1 (1.7%)
Snow/Severe crosswinds1 (1.7%)
Snow/Sleet, hail (freezing rain or drizzle)1 (1.7%)
Cloudy/Unknown1 (1.7%)

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

Lighting

Daylight38 (63.3%)
18.8%prior 32
Dark - lighted roadway18 (30.0%)
-35.7%prior 28
Dark - roadway not lighted2 (3.3%)
Dawn1 (1.7%)
Dusk1 (1.7%)

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

Road Surface

Dry41 (68.3%)
-18.0%prior 50
Wet9 (15.0%)
50.0%prior 6
Snow4 (6.7%)
-66.7%prior 12
Ice2 (3.3%)
Slush2 (3.3%)
Sand, mud, dirt, oil, gravel1 (1.7%)
Other1 (1.7%)

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 136 in February 2025 to 127 in February 2026. The ranking of top vehicle makes shifted, with Toyota moving from third to first place (16 to 30 vehicles), while Honda dropped from first to second (32 to 27 vehicles). The 65+ age group saw an increase in persons involved, from 13 to 22, whereas the 21-25 age group experienced a decrease from 23 to 13.

Top Vehicle Makes (127 vehicles)

1
TOYOTA30 (23.6%)
87.5%prior 16
2
HONDA27 (21.3%)
-15.6%prior 32
3
FORD10 (7.9%)
-52.4%prior 21
4
BMW6 (4.7%)
5
NISSAN5 (3.9%)
-28.6%prior 7
6
MAZDA4 (3.1%)
7
CHEVROLET4 (3.1%)
-20.0%prior 5
8
LEXUS4 (3.1%)
9
HYUNDAI3 (2.4%)
10
KIA3 (2.4%)

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

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

Sex Distribution (143 persons with recorded sex)

Male91 (63.6%)
-9.0%prior 100
Female52 (36.4%)
-18.8%prior 64

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 25 mph speed zone remained the most frequent, decreasing slightly from 30 to 29 incidents. Crashes in the 35 mph zone saw a reduction from 8 to 4 incidents, a 50% decrease. Conversely, crashes in the 55 mph zone tripled, increasing from 2 to 6 incidents.

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: REVERE, MA
  • Total crash records analyzed: 60
  • Total persons involved: 165
  • Total vehicles involved: 127

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). "REVERE, 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/revere/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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Revere, MA Crash Report — February 2026 | ThatCarHitMe.com