Monthly Traffic Safety Analysis

116 CRASHES IN
CAMBRIDGE, MA
FEBRUARY 2026

All metrics benchmarked againstFebruary 2025

In February 2026, there were 116 total crashes in CAMBRIDGE, a slight increase from 114 crashes in February 2025, representing a 1.75% rise. The most notable year-over-year shift was a significant increase in hit-and-run incidents, which rose from 35 to 44 crashes. This led to an increase in the hit-and-run rate from 30.7% to 37.9% of all crashes.

116

1.8%was 114

Total Crash Events

0

Persons Killed

21

-16.0%was 25

Persons Injured

44

25.7%was 35

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. 46 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, total crashes experienced a slight increase of 1.75%, rising from 114 in February 2025 to 116 in February 2026. Conversely, total injuries decreased by 16%, from 25 to 21, while fatalities remained at zero in both periods.

44

Hit-and-Run Crashes — February 2026

25.7% vs prior (35)

Hit-and-run crashes increased from 35 incidents in February 2025 to 44 incidents in February 2026, representing a rise of 9 crashes. The hit-and-run rate also increased from 30.7% to 37.9% of all crashes, indicating an upward trend year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 5-60.0%

3

Cyclists Injured

Prior: 5-40.0%

15

Motorists Injured

Prior: 1315.4%

1

Other Injured

Prior: 2-50.0%

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 Tuesday with 22 incidents in the prior period to Friday with 30 incidents in the current period. The peak crash hour also changed, moving from 5 PM in the prior period to 3 PM in the current period, with both hours recording 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

Fatalities remained at zero in both periods. Total injuries decreased from 25 in the prior period to 21 in the current period, a 16% reduction. Minor injuries decreased from 18 to 15, while possible injuries saw a larger proportional decrease, falling from 6 to 2.

Outcome by Severity (Crash Events)

Minor Injury15minor injury crashes12.9%
-16.7%prior 18
Possible Injury2possible injury crashes1.7%
-66.7%prior 6
No Injury53no injury crashes45.7%
-20.9%prior 67

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 count of 'No improper driving' as a contributing factor decreased from 25 to 21 crashes, a 16% reduction. 'Other improper action' decreased by 42.9% in count, from 14 crashes to 8 crashes. 'Failed to yield right of way' saw a significant increase in count, rising from 3 crashes to 9 crashes, a 200% change, causing it to move up in ranking.

Officer-Reported Primary Contributing Cause

No improper driving21 (18.1%)-16.0%prior 25
Failed to yield right of way9 (7.8%)
Other improper action8 (6.9%)-42.9%prior 14
Failure to keep in proper lane or running off road3 (2.6%)
Driving too fast for conditions3 (2.6%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (1.7%)
Followed too closely2 (1.7%)
Inattention2 (1.7%)-66.7%prior 6
Glare1 (0.9%)
Disregarded traffic signs, signals, road markings1 (0.9%)-83.3%prior 6

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

The number of crashes occurring in clear or partly clear weather decreased from 78 in the prior period to 73 in the current period. Crashes on dry road surfaces decreased from 66 to 52, while crashes on snow-covered roads increased from 14 to 27. Crashes occurring in dark conditions on lighted roadways decreased from 34 to 27.

Weather

Clear56 (57.1%)
-12.5%prior 64
Clear/Clear17 (17.3%)
21.4%prior 14
Snow9 (9.2%)
50.0%prior 6
Cloudy5 (5.1%)
-44.4%prior 9
Snow/Snow3 (3.1%)
Other/Other2 (2.0%)
Cloudy/Cloudy1 (1.0%)
Clear/Other1 (1.0%)
Clear/Snow1 (1.0%)
Blowing sand, snow1 (1.0%)

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

Lighting

Daylight65 (67.0%)
3.2%prior 63
Dark - lighted roadway27 (27.8%)
-20.6%prior 34
Dawn3 (3.1%)
Other2 (2.1%)

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

Road Surface

Dry52 (54.7%)
-21.2%prior 66
Snow27 (28.4%)
92.9%prior 14
Wet13 (13.7%)
-40.9%prior 22
Slush2 (2.1%)
Other1 (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

Toyota remained the most frequently involved vehicle make, increasing from 38 to 40 vehicles. Ford's involvement decreased from 24 to 12 vehicles, causing it to drop in rank, while Subaru rose in rank with 20 vehicles involved, up from 14. The age group 0-15 saw an increase in persons involved from 9 to 14, whereas the 65+ age group experienced a decrease from 20 to 10 persons involved.

Top Vehicle Makes (194 vehicles)

1
TOYOTA40 (20.6%)
5.3%prior 38
2
HONDA21 (10.8%)
10.5%prior 19
3
SUBARU20 (10.3%)
42.9%prior 14
4
FORD12 (6.2%)
-50.0%prior 24
5
NISSAN8 (4.1%)
-27.3%prior 11
6
MAZDA8 (4.1%)
0.0%prior 8
7
CHEVROLET7 (3.6%)
40.0%prior 5
8
TESL6 (3.1%)
20.0%prior 5
9
JEEP5 (2.6%)
10
KIA5 (2.6%)

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

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

Sex Distribution (147 persons with recorded sex)

Male95 (64.6%)
-15.9%prior 113
Female51 (34.7%)
-21.5%prior 65
X / Unspecified1 (0.7%)

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 20 mph zones increased from 16 to 21, while those in 25 mph zones remained stable, increasing slightly from 79 to 80. Crashes in 30 mph zones increased from 3 to 5. The prior period included 3 crashes in 55 mph zones, a category not present in the current period's data.

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: CAMBRIDGE, MA
  • Total crash records analyzed: 116
  • Total persons involved: 239
  • Total vehicles involved: 194

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). "CAMBRIDGE, 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/cambridge/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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Cambridge, MA Crash Report — February 2026 | ThatCarHitMe.com