Monthly Traffic Safety Analysis

30 CRASHES IN
WESTMINSTER, MA
JANUARY 2022

All metrics benchmarked againstJanuary 2021

Total crashes in Westminster, MA for January 2022 were 30, marking a 50% increase from the 20 crashes reported in January 2021. This notable rise in overall crash incidents was accompanied by a significant increase in speeding-related contributing factors. Fatalities remained at zero for both periods, indicating no change in fatal crash outcomes.

30

50.0%was 20

Total Crash Events

0

Persons Killed

9

12.5%was 8

Persons Injured

0

Fatal Crash Events

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 · 2022-01-01 to 2022-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a substantial increase in crashes year-over-year in Westminster, MA for January. Total crashes rose by 50%, from 20 in January 2021 to 30 in January 2022. Injuries also saw a slight increase, from 8 to 9, representing a 12.5% rise, while fatalities remained unchanged at zero.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

9

Motorists Injured

Prior: 812.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with Friday becoming the clear peak day for crashes in January 2022 with 10 incidents, compared to 5 on both Friday and Thursday in January 2021. The peak hour also changed from 8 AM in January 2021 (4 crashes) to 1 PM in January 2022 (4 crashes). Crashes on Wednesday also notably increased from 4 to 8 incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total injuries slightly increased from 8 to 9, the distribution of injury severity saw a notable change. In January 2022, there were 4 serious injury crashes (Severity A), whereas none were reported in January 2021. Despite the increase in total crashes, the proportion of crashes resulting in any injury decreased from 35% (7 out of 20) in January 2021 to 23.3% (7 out of 30) in January 2022.

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes13.3%
Minor Injury2minor injury crashes6.7%
-50.0%prior 4
Possible Injury1possible injury crashes3.3%
-66.7%prior 3
No Injury23no injury crashes76.7%
91.7%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Most severe injury per crash record

Top Contributing Factors

"Driving too fast for conditions" became the leading contributing factor in January 2022, increasing from 2 crashes in January 2021 to 8 crashes, a 300% increase in count. "No improper driving" also saw a slight increase from 6 to 7 crashes, but its share of total crashes decreased from 30% to 23.3%. Factors like "Inattention" (5 crashes) and "Exceeded authorized speed limit" (3 crashes) emerged as top contributors in the current period, while "Failure to keep in proper lane or running off road" (3 crashes in prior) was not a top factor in the current period.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions8 (26.7%)
No improper driving7 (23.3%)16.7%prior 6
Inattention5 (16.7%)
Exceeded authorized speed limit3 (10%)
Failed to yield right of way2 (6.7%)
Over-correcting/over-steering1 (3.3%)
Illness1 (3.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.3%)
Other improper action1 (3.3%)
Distracted1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased significantly from 5 in January 2021 to 13 in January 2022. Crashes on dry road surfaces also rose from 6 to 11, and those on snow-covered roads nearly doubled from 4 to 9. Despite an increase in the count of crashes under adverse conditions (from 16 to 23), the overall proportion of crashes occurring under adverse road conditions slightly decreased from 80% to 76.7%.

Weather

Clear13 (43.3%)
160.0%prior 5
Cloudy4 (13.3%)
Sleet, hail (freezing rain or drizzle)4 (13.3%)
Snow3 (10.0%)
Rain/Sleet, hail (freezing rain or drizzle)2 (6.7%)
Snow/Blowing sand, snow2 (6.7%)
Clear/Blowing sand, snow1 (3.3%)
Sleet, hail (freezing rain or drizzle)/Cloudy1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Weather condition at time of crash

Lighting

Daylight22 (73.3%)
69.2%prior 13
Dark - roadway not lighted6 (20.0%)
Dark - lighted roadway1 (3.3%)
Dawn1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Lighting condition field

Road Surface

Dry11 (36.7%)
83.3%prior 6
Snow9 (30.0%)
Ice8 (26.7%)
60.0%prior 5
Slush1 (3.3%)
Wet1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (44 vehicles)

1
TOYOTA6 (13.6%)
0.0%prior 6
2
GMC5 (11.4%)
3
FORD5 (11.4%)
0.0%prior 5
4
SUBARU5 (11.4%)
5
CHEVROLET4 (9.1%)
6
JEEP3 (6.8%)
7
NISSAN3 (6.8%)
8
HONDA2 (4.5%)
9
LEXUS2 (4.5%)
10
DODGE2 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Vehicle unit records

Sex Distribution (62 persons with recorded sex)

Male43 (69.4%)
104.8%prior 21
Female19 (30.6%)
90.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Person-level records linked to crash events

Speed Limit Zones

There was a noticeable shift in crashes occurring in mid-range speed zones year-over-year. Crashes in 35 mph zones increased from 2 to 7, and in 40 mph zones from 1 to 5. Conversely, crashes in 55 mph zones decreased from 8 in January 2021 to 6 in January 2022, while crashes in 30 mph zones remained constant at 8 for both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · 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: 2022-01-01 through 2022-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-01-31 (31 days)
  • Geographic scope: WESTMINSTER, MA
  • Total crash records analyzed: 30
  • Total persons involved: 63
  • Total vehicles involved: 44

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). "WESTMINSTER, MA Crash Intelligence Report: January 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/westminster/january-2022-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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Westminster, MA Crash Report — January 2022 | ThatCarHitMe.com