Monthly Traffic Safety Analysis

10,753 CRASHES IN
MASSACHUSETTS, MA
FEBRUARY 2026

All metrics benchmarked againstFebruary 2025

In February 2026, there were 10,753 total crashes, a 1.3% increase from the 10,617 crashes recorded in February 2025. Despite the slight rise in total incidents, the number of fatalities decreased significantly, falling 37.5% from 24 in the prior year to 15 in the current period. The most notable change in contributing factors was a 15.8% increase in crashes attributed to a failure to yield the right of way.

10,753

1.3%was 10,617

Total Crash Events

15

-37.5%was 24

Persons Killed

2,601

-1.5%was 2,640

Persons Injured

1,119

14.5%was 977

Hit-and-Run Crashes

Note: "Persons Killed" (15) counts individual fatalities across all crash events. "Fatal" in the severity table below (13) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 457 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 crash volume remained relatively stable, increasing by 1.3% from 10,617 in February 2025 to 10,753 in February 2026. However, the severity of these crashes lessened, with total injuries decreasing by 1.5% and total fatalities dropping by 37.5% year-over-year.

1,119

Hit-and-Run Crashes — February 2026

14.5% vs prior (977)

Hit-and-run incidents increased in both absolute numbers and as a proportion of total crashes. The count of hit-and-run crashes rose by 14.5%, from 977 in February 2025 to 1,119 in February 2026. This caused the hit-and-run rate to trend upward, increasing from 9.2% to 10.4% of all crashes.

Vulnerable Road User Casualties

6

Pedestrians Killed

Prior: 8-25.0%

0

Cyclists Killed

Prior: 1-100.0%

9

Motorists Killed

Prior: 15-40.0%

0

Other Killed

Prior: 00.0%

87

Pedestrians Injured

Prior: 92-5.4%

12

Cyclists Injured

Prior: 29-58.6%

2,490

Motorists Injured

Prior: 2,508-0.7%

12

Other Injured

Prior: 119.1%

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 timing of crashes showed some changes year-over-year. The peak hour for collisions remained consistent at 3 p.m. in both February 2025 (822 crashes) and February 2026 (850 crashes). However, the peak day for crashes shifted from Thursday (1,743 crashes) in the prior year to Saturday (1,867 crashes) in the current period.

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

Crash severity decreased in February 2026 compared to the previous year. The proportion of fatal crashes fell from 0.2% to 0.1% of all incidents, and the share of serious injury crashes decreased from 1.1% to 0.8%. Consequently, the proportion of non-injury crashes increased from 76.3% in the prior period to 77.5% in the current period.

Severity is per crash event (most severe injury). 13 fatal crash events resulted in 15 persons killed.

Outcome by Severity (Crash Events)

Fatal13fatal crashes0.1%
-43.5%prior 23
Serious Injury86serious injury crashes0.8%
-25.9%prior 116
Minor Injury1,256minor injury crashes11.7%
-2.8%prior 1,292
Possible Injury611possible injury crashes5.7%
0.0%prior 611
No Injury8,330no injury crashes77.5%
2.9%prior 8,099

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 top two contributing factors, 'No improper driving' and 'Inattention,' saw their counts decrease slightly from the prior year. The count for crashes involving 'Failed to yield right of way' increased by 15.8% from 916 to 1,061. Conversely, crashes attributed to 'Driving too fast for conditions' saw a 20.4% decrease in count, falling from 710 incidents to 565.

Officer-Reported Primary Contributing Cause

No improper driving2,937 (27.3%)-1.6%prior 2,986
Inattention1,170 (10.9%)-2.7%prior 1,203
Failed to yield right of way1,061 (9.9%)15.8%prior 916
Followed too closely753 (7%)5.3%prior 715
Driving too fast for conditions565 (5.3%)-20.4%prior 710
Failure to keep in proper lane or running off road539 (5%)14.2%prior 472
Other improper action345 (3.2%)1.2%prior 341
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway316 (2.9%)9.7%prior 288
Disregarded traffic signs, signals, road markings272 (2.5%)-3.2%prior 281
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner255 (2.4%)1.6%prior 251

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 on snowy road surfaces increased from 1,771 to 2,331 year-over-year, while those on icy surfaces decreased from 900 to 458. The number of crashes occurring in daylight increased from 6,552 to 6,972. The overall proportion of crashes on adverse road surfaces (snow, wet, ice, or slush) remained similar, moving from 41.6% in the prior year to 40.4% in the current period.

Weather

Clear5,584 (53.1%)
4.2%prior 5,358
Clear/Clear1,375 (13.1%)
25.2%prior 1,098
Snow1,026 (9.8%)
3.1%prior 995
Cloudy721 (6.9%)
-5.8%prior 765
Snow/Sleet, hail (freezing rain or drizzle)216 (2.1%)
-38.6%prior 352
Snow/Blowing sand, snow208 (2.0%)
258.6%prior 58
Snow/Snow194 (1.8%)
6.6%prior 182
Clear/Cloudy145 (1.4%)
6.6%prior 136
Snow/Cloudy134 (1.3%)
42.6%prior 94
Cloudy/Snow109 (1.0%)
49.3%prior 73

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

Lighting

Daylight6,972 (66.1%)
6.4%prior 6,552
Dark - lighted roadway2,196 (20.8%)
-14.5%prior 2,568
Dark - roadway not lighted704 (6.7%)
-0.7%prior 709
Dusk350 (3.3%)
11.1%prior 315
Dawn210 (2.0%)
-13.6%prior 243
Dark - unknown roadway lighting87 (0.8%)
11.5%prior 78
Other23 (0.2%)
76.9%prior 13

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

Road Surface

Dry6,047 (57.9%)
1.3%prior 5,969
Snow2,331 (22.3%)
31.6%prior 1,771
Wet1,295 (12.4%)
-10.8%prior 1,452
Ice458 (4.4%)
-49.1%prior 900
Slush257 (2.5%)
-12.0%prior 292
Sand, mud, dirt, oil, gravel34 (0.3%)
88.9%prior 18
Other24 (0.2%)
20.0%prior 20
Water (standing, moving)3 (0.0%)

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

Vehicles & Demographics

The top three vehicle makes involved in crashes remained unchanged: Toyota, Honda, and Ford. An analysis of all persons involved in crashes shows a shift in age demographics, with the number of individuals in the 16-20 age group decreasing from 2,112 to 1,975. In contrast, involvement for the 65+ age group increased from 2,242 individuals to 2,530.

Top Vehicle Makes (20,042 vehicles)

1
TOYOTA3,310 (16.5%)
4.0%prior 3,183
2
HONDA2,557 (12.8%)
0.0%prior 2,556
3
FORD2,212 (11%)
12.7%prior 1,962
4
CHEVROLET1,349 (6.7%)
7.2%prior 1,258
5
NISSAN1,081 (5.4%)
-4.8%prior 1,136
6
JEEP867 (4.3%)
5.6%prior 821
7
SUBARU801 (4%)
-2.9%prior 825
8
HYUNDAI800 (4%)
7.1%prior 747
9
KIA491 (2.4%)
2.3%prior 480
10
GMC467 (2.3%)
11.5%prior 419

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

2,917 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (21,328 persons with recorded sex)

Male12,641 (59.3%)
5.1%prior 12,027
Female8,677 (40.7%)
3.1%prior 8,418
X / Unspecified10 (0.0%)
100.0%prior 5

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

There was a shift in where crashes occurred relative to posted speed limits. Crashes in 65 mph zones decreased from 761 to 654, while incidents in 30 mph zones increased from 2,535 to 2,698. Despite more crashes in lower speed zones, the number of fatal crashes in 25 mph and 30 mph zones combined dropped from 13 in the prior year to 3 in the current period.

Fatal crashes by zone: 25 mph: 2 of 2,630 (0.076%) · 30 mph: 1 of 2,698 (0.037%) · 35 mph: 2 of 1,264 (0.158%) · 40 mph: 2 of 782 (0.256%) · 45 mph: 1 of 353 (0.283%) · 50 mph: 2 of 212 (0.943%) · 55 mph: 1 of 399 (0.251%) · 65 mph: 2 of 654 (0.306%)

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: massachusetts, MA
  • Total crash records analyzed: 10,753
  • Total persons involved: 24,442
  • Total vehicles involved: 20,042

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). "massachusetts, 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/statewide/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

ThatCarHitMe.com · An Injuria.ai Company