Monthly Traffic Safety Analysis

33 CRASHES IN
WEBSTER, MA
JUNE 2022

All metrics benchmarked againstJune 2021

Total crashes in Webster decreased by 13.16% from 38 in June 2021 to 33 in June 2022. The most significant year-over-year shift was the increase in total fatalities, rising from 0 in June 2021 to 2 in June 2022.

33

-13.2%was 38

Total Crash Events

2

Persons Killed

16

45.5%was 11

Persons Injured

1

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in Webster decreased by 13.16%, from 38 crashes in June 2021 to 33 crashes in June 2022. Despite this decrease in total crashes, the number of fatalities increased from 0 in the prior period to 2 in the current period. Total injuries also rose by 45.45%, from 11 to 16.

1

Hit-and-Run Crashes — June 2022

3.0% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

14

Motorists Injured

Prior: 1127.3%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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 Monday, with 11 crashes in June 2021, to Thursday, with 8 crashes in June 2022. The peak hour for crashes also changed, moving from 5 PM with 4 crashes in June 2021 to 2 PM with 6 crashes in June 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes increased from 0 in June 2021 to 1 in June 2022, resulting in a rise in total fatalities from 0 to 2. Total injuries increased by 45.45%, from 11 in June 2021 to 16 in June 2022. Serious injuries increased from 1 to 2, and minor injuries from 5 to 6 between the two periods.

Severity is per crash event (most severe injury). 1 fatal crash events resulted in 2 persons killed.

Outcome by Severity (Crash Events)

Fatal1fatal crashes3%
Serious Injury2serious injury crashes6.1%
100.0%prior 1
Minor Injury6minor injury crashes18.2%
20.0%prior 5
Possible Injury4possible injury crashes12.1%
33.3%prior 3
No Injury19no injury crashes57.6%
-29.6%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "No improper driving" increased by 22.22%, rising from 9 incidents in June 2021 to 11 in June 2022. Conversely, crashes involving "Followed too closely" decreased by 33.33%, from 3 to 2 incidents. Crashes related to "Driving too fast for conditions" were eliminated, dropping by 100% from 3 incidents in June 2021 to 0 in June 2022.

Officer-Reported Primary Contributing Cause

No improper driving11 (33.3%)22.2%prior 9
Inattention5 (15.2%)0.0%prior 5
Failed to yield right of way2 (6.1%)
Failure to keep in proper lane or running off road2 (6.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (6.1%)
Followed too closely2 (6.1%)
Made an improper turn1 (3%)
Over-correcting/over-steering1 (3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased by 6.9%, from 29 in June 2021 to 27 in June 2022. Crashes during rainy conditions saw a 75% decrease, falling from 4 to 1 incident. Similarly, crashes in daylight conditions decreased by 12.5%, from 32 to 28 incidents year-over-year.

Weather

Clear27 (84.4%)
-6.9%prior 29
Cloudy3 (9.4%)
Rain1 (3.1%)
Rain/Cloudy1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash

Lighting

Daylight28 (90.3%)
-12.5%prior 32
Dark - lighted roadway2 (6.5%)
Dark - roadway not lighted1 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field

Road Surface

Dry31 (93.9%)
-3.1%prior 32
Wet2 (6.1%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased by 6.45%, from 62 in June 2021 to 58 in June 2022. Honda vehicles involved in crashes increased by 166.67%, from 3 to 8, while Ford vehicles involved decreased by 90%, from 10 to 1. The age group "0-15" saw a 200% increase in persons involved (from 2 to 6), and the "16-20" age group saw a 120% increase (from 5 to 11).

Top Vehicle Makes (58 vehicles)

1
HONDA8 (13.8%)
2
CHEVROLET6 (10.3%)
-33.3%prior 9
3
SUBARU5 (8.6%)
4
TOYOTA5 (8.6%)
0.0%prior 5
5
HYUNDAI5 (8.6%)
6
NISSAN5 (8.6%)
0.0%prior 5
7
JEEP4 (6.9%)
-20.0%prior 5
8
RAM2 (3.4%)
9
HD2 (3.4%)
10
BMW2 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records

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

Sex Distribution (72 persons with recorded sex)

Female40 (55.6%)
29.0%prior 31
Male32 (44.4%)
3.2%prior 31

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph speed zones remained consistent with 17 incidents in both June 2021 and June 2022. Crashes in 65 mph speed zones decreased by 66.67%, falling from 6 to 2 incidents. A fatal crash was recorded in a 55 mph zone in June 2022, whereas no fatal crashes were reported in any speed zone in June 2021.

Fatal crashes by zone: 55 mph: 1 of 1 (100%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-06-01 through 2022-06-30 (30 days)
  • Geographic scope: WEBSTER, MA
  • Total crash records analyzed: 33
  • Total persons involved: 80
  • Total vehicles involved: 58

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). "WEBSTER, MA Crash Intelligence Report: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/webster/june-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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Webster, MA Crash Report — June 2022 | ThatCarHitMe.com