Monthly Traffic Safety Analysis

57 CRASHES IN
SOMERVILLE, MA
JANUARY 2026

All metrics benchmarked againstJanuary 2025

In January 2026, Somerville experienced 57 total crashes, a 29.5% increase compared to the 44 crashes recorded in January 2025. This period also saw a notable rise in total injuries, increasing from 10 to 16 year-over-year. The most significant shift was the increase in crashes occurring on snow-covered roads, which rose from 4 to 19.

57

29.5%was 44

Total Crash Events

0

Persons Killed

16

60.0%was 10

Persons Injured

3

-40.0%was 5

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. 6 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for Somerville shows an upward trend year-over-year. Total crashes increased by 13, from 44 in January 2025 to 57 in January 2026, representing a 29.5% rise. Similarly, total injuries rose by 6, from 10 to 16, marking a 60% increase.

3

Hit-and-Run Crashes — January 2026

-40.0% vs prior (5)

Hit-and-run crashes decreased year-over-year, falling from 5 incidents in January 2025 to 3 in January 2026. This resulted in a decrease in the hit-and-run rate, which dropped from 11.4% to 5.3% of total crashes.

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: 4-50.0%

1

Cyclists Injured

Prior: 0%

12

Motorists Injured

Prior: 6100.0%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Friday with 9 crashes in January 2025 to Tuesday with 11 crashes in January 2026. The peak crash hour also changed, moving from 6 PM with 4 crashes in the prior period to 3 PM with 5 crashes in the current period. While Friday was the highest crash day previously, Tuesday and Thursday now show the highest counts.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities reported in either January 2025 or January 2026. Total injuries increased from 10 to 16 year-over-year, a 60% rise. Minor injuries (severity B) increased from 5 to 11, while possible injuries (severity C) rose from 3 to 5; the prior period also reported 1 serious injury (severity A) which was not present in the current period.

Outcome by Severity (Crash Events)

Minor Injury11minor injury crashes19.3%
120.0%prior 5
Possible Injury5possible injury crashes8.8%
66.7%prior 3
No Injury35no injury crashes61.4%
2.9%prior 34

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'No improper driving,' increased by 9 crashes, from 12 in January 2025 to 21 in January 2026. 'Failed to yield right of way' also saw an increase of 3 crashes, rising from 3 to 6. Conversely, 'Followed too closely' decreased by 1 crash, from 5 to 4, and 'Failure to keep in proper lane or running off road' decreased from 4 to 3 crashes.

Officer-Reported Primary Contributing Cause

No improper driving21 (36.8%)75.0%prior 12
Failed to yield right of way6 (10.5%)
Other improper action5 (8.8%)
Followed too closely4 (7%)-20.0%prior 5
Driving too fast for conditions3 (5.3%)
Failure to keep in proper lane or running off road3 (5.3%)
Made an improper turn1 (1.8%)
Inattention1 (1.8%)
Disregarded traffic signs, signals, road markings1 (1.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes on snow-covered roads significantly increased from 4 in January 2025 to 19 in January 2026. Concurrently, crashes under dry road conditions decreased from 31 to 24. Daylight crashes increased from 24 to 30, while crashes in dark-lighted roadway conditions rose from 12 to 21.

Weather

Clear15 (26.3%)
-28.6%prior 21
Clear/Clear12 (21.1%)
0.0%prior 12
Cloudy/Cloudy5 (8.8%)
Snow5 (8.8%)
Snow/Snow5 (8.8%)
Cloudy5 (8.8%)
Snow/Blowing sand, snow2 (3.5%)
Sleet, hail (freezing rain or drizzle)/Cloudy2 (3.5%)
Snow/Sleet, hail (freezing rain or drizzle)2 (3.5%)
Rain1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash

Lighting

Daylight30 (52.6%)
25.0%prior 24
Dark - lighted roadway21 (36.8%)
75.0%prior 12
Dark - unknown roadway lighting2 (3.5%)
Dusk2 (3.5%)
Dark - roadway not lighted1 (1.8%)
Dawn1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field

Road Surface

Dry24 (42.9%)
-22.6%prior 31
Snow19 (33.9%)
Wet11 (19.6%)
57.1%prior 7
Ice1 (1.8%)
Slush1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 32, from 83 in January 2025 to 115 in January 2026. Toyota remained the top make involved, increasing from 17 to 22, and Honda increased from 10 to 14. The 55-64 age group saw a notable increase in persons involved, rising from 11 to 18.

Top Vehicle Makes (115 vehicles)

1
TOYOTA22 (19.1%)
29.4%prior 17
2
HONDA14 (12.2%)
40.0%prior 10
3
FORD11 (9.6%)
-15.4%prior 13
4
SUBARU10 (8.7%)
5
CHEVROLET9 (7.8%)
6
JEEP7 (6.1%)
7
LEXUS6 (5.2%)
8
NISSAN6 (5.2%)
-14.3%prior 7
9
MAZDA4 (3.5%)
10
TESL3 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Vehicle unit records

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

Sex Distribution (97 persons with recorded sex)

Male69 (71.1%)
19.0%prior 58
Female28 (28.9%)
-9.7%prior 31

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone increased from 22 in January 2025 to 31 in January 2026. Crashes in the 20 mph zone also rose from 5 to 8, and in the 35 mph zone from 5 to 8. No fatal crashes were recorded in any speed zone during either period.

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

Data Coverage

  • Reporting period: 2026-01-01 through 2026-01-31 (31 days)
  • Geographic scope: SOMERVILLE, MA
  • Total crash records analyzed: 57
  • Total persons involved: 125
  • Total vehicles involved: 115

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). "SOMERVILLE, MA Crash Intelligence Report: January 2026." Published June 21, 2026. Reporting period: 2026-01-01 to 2026-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/somerville/january-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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Somerville, MA Crash Report — January 2026 | ThatCarHitMe.com