Monthly Traffic Safety Analysis

47 CRASHES IN
WESTWOOD, MA
JANUARY 2026

All metrics benchmarked againstJanuary 2025

In January 2026, Westwood recorded 47 total crashes, an 11.3% decrease from the 53 crashes reported in January 2025. Total injuries also saw a reduction, falling from 10 in the prior period to 8 in the current period. Notably, serious injuries (severity 'A') were absent in January 2026, compared to 1 serious injury in January 2025.

47

-11.3%was 53

Total Crash Events

0

Persons Killed

8

-20.0%was 10

Persons Injured

1

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 · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for January 2026 shows a downward trend compared to the same month in the prior year. The total number of crashes decreased by 6, from 53 crashes in January 2025 to 47 crashes in January 2026, representing an 11.3% reduction.

1

Hit-and-Run Crashes — January 2026

2.1% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

8

Motorists Injured

Prior: 10-20.0%

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 temporal patterns of crashes shifted year-over-year. The peak day for crashes moved from Wednesday with 13 crashes in January 2025 to Saturday with 9 crashes in January 2026. Similarly, the peak hour for crashes shifted from 3 PM with 9 crashes in January 2025 to 4 PM with 5 crashes in January 2026.

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 fatalities reported in either January 2025 or January 2026. Total injuries decreased from 10 in January 2025 to 8 in January 2026, with serious injuries (severity 'A') dropping from 1 to 0. While minor injuries (severity 'B') increased from 3 (5.7% share) to 7 (14.9% share), possible injuries (severity 'C') decreased from 3 (5.7% share) to 1 (2.1% share).

Outcome by Severity (Crash Events)

Minor Injury7minor injury crashes14.9%
133.3%prior 3
Possible Injury1possible injury crashes2.1%
-66.7%prior 3
No Injury39no injury crashes83%
-15.2%prior 46

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 leading contributing factor, 'Followed too closely,' decreased by 7 crashes, from 18 in January 2025 to 11 in January 2026. Crashes attributed to 'Inattention' increased by 6, rising from 4 in January 2025 to 10 in January 2026, moving from the fourth-ranked factor to the second-ranked. 'Failed to yield right of way' also saw a slight decrease of 1 crash, from 7 to 6.

Officer-Reported Primary Contributing Cause

Followed too closely11 (23.4%)-38.9%prior 18
Inattention10 (21.3%)
Failed to yield right of way6 (12.8%)-14.3%prior 7
Driving too fast for conditions4 (8.5%)
Failure to keep in proper lane or running off road4 (8.5%)
No improper driving3 (6.4%)-40.0%prior 5
Disregarded traffic signs, signals, road markings2 (4.3%)
Made an improper turn2 (4.3%)
Distracted1 (2.1%)
Glare1 (2.1%)

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 occurring under clear weather conditions (Clear/Clear and Clear combined) decreased from 44 in January 2025 to 38 in January 2026. Crashes in 'Dark - lighted roadway' conditions decreased from 13 in the prior period to 7 in the current period. Conversely, crashes on snow-covered road surfaces saw a slight increase from 4 in January 2025 to 5 in January 2026.

Weather

Clear/Clear26 (55.3%)
4.0%prior 25
Clear12 (25.5%)
-36.8%prior 19
Snow/Snow4 (8.5%)
Cloudy/Cloudy2 (4.3%)
Rain/Rain1 (2.1%)
Snow1 (2.1%)
Cloudy1 (2.1%)

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

Lighting

Daylight36 (76.6%)
5.9%prior 34
Dark - lighted roadway7 (14.9%)
-46.2%prior 13
Dark - roadway not lighted3 (6.4%)
Dawn1 (2.1%)

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

Road Surface

Dry39 (84.8%)
-15.2%prior 46
Snow5 (10.9%)
Ice1 (2.2%)
Wet1 (2.2%)

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

Vehicles & Demographics

The top vehicle make involved in crashes shifted, with TOYOTA vehicles increasing from 15 in January 2025 to 18 in January 2026, becoming the most frequent. HONDA vehicles, which were 17 in the prior period, decreased to 9 in the current period. The 0-15 age group saw a significant reduction in persons involved, dropping from 9 in January 2025 to 1 in January 2026, while the 16-20 age group increased from 10 to 15 persons involved.

Top Vehicle Makes (89 vehicles)

1
TOYOTA18 (20.2%)
20.0%prior 15
2
HONDA9 (10.1%)
-47.1%prior 17
3
FORD7 (7.9%)
-22.2%prior 9
4
CHEVROLET6 (6.7%)
5
SUBARU5 (5.6%)
-16.7%prior 6
6
LEXUS4 (4.5%)
7
VOLKSWAGEN4 (4.5%)
8
JEEP4 (4.5%)
-42.9%prior 7
9
BMW3 (3.4%)
10
NISSAN3 (3.4%)

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

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

Sex Distribution (89 persons with recorded sex)

Male53 (59.6%)
-10.2%prior 59
Female36 (40.4%)
-32.1%prior 53

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 30 MPH speed zone decreased from 22 in January 2025 to 17 in January 2026. Similarly, crashes in the 1 MPH speed zone decreased from 7 to 4 between the two periods. Conversely, the 55 MPH speed zone experienced a slight increase in crashes, rising from 6 in January 2025 to 7 in January 2026, with no fatalities reported 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: WESTWOOD, MA
  • Total crash records analyzed: 47
  • Total persons involved: 93
  • Total vehicles involved: 89

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). "WESTWOOD, 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/westwood/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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Westwood, MA Crash Report — January 2026 | ThatCarHitMe.com