Monthly Traffic Safety Analysis

22 CRASHES IN
WEBSTER, MA
APRIL 2023

All metrics benchmarked againstApril 2022

Total crashes in WEBSTER, MA increased by 10% year-over-year, rising from 20 in April 2022 to 22 in April 2023. This period saw a significant 75% increase in total injuries, from 8 in April 2022 to 14 in April 2023. Fatalities remained at zero in both periods.

22

10.0%was 20

Total Crash Events

0

Persons Killed

14

75.0%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 · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in WEBSTER, MA showed an upward trend year-over-year. Total crashes increased by 10%, from 20 in April 2022 to 22 in April 2023. More notably, total injuries rose by 75%, from 8 in April 2022 to 14 in April 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

13

Motorists Injured

Prior: 862.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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. In April 2023, the peak day for crashes was Friday with 8 incidents, compared to Monday with 6 incidents in April 2022. The peak hour also changed, with 5 PM recording the most crashes (4) in April 2023, whereas 9 PM had the highest count (3) in April 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While fatal crashes remained at zero in both periods, the proportion of injury-involved crashes increased. In April 2023, 10 out of 22 crashes (45.5% share) resulted in some level of injury, compared to 8 out of 20 crashes (40% share) in April 2022. The number of serious injuries (severity A) increased from 0 in April 2022 to 1 in April 2023.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.5%
Minor Injury7minor injury crashes31.8%
40.0%prior 5
Possible Injury2possible injury crashes9.1%
-33.3%prior 3
No Injury12no injury crashes54.5%
9.1%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record

Top Contributing Factors

Among common contributing factors, "Inattention" decreased from 6 crashes in April 2022 to 4 crashes in April 2023, and "No improper driving" decreased from 5 to 4 crashes. Conversely, crashes attributed to "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" increased from 1 to 3 incidents. "Failed to yield right of way" and "Other improper action" also saw increases, each rising from 1 crash in April 2022 to 2 crashes in April 2023.

Officer-Reported Primary Contributing Cause

Inattention4 (18.2%)-33.3%prior 6
No improper driving4 (18.2%)-20.0%prior 5
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (13.6%)
Failed to yield right of way2 (9.1%)
Followed too closely2 (9.1%)
Other improper action2 (9.1%)
Driving too fast for conditions1 (4.5%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.5%)
Made an improper turn1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in adverse weather conditions (Cloudy, Rain, Cloudy/Rain) slightly increased in count from 5 in April 2022 to 6 in April 2023, representing a 25% share and 27.3% share of total crashes, respectively. The number of crashes on wet road surfaces increased from 4 to 5 year-over-year. Crashes during non-daylight conditions remained consistent at 6 incidents in both periods, though their share decreased from 30% to 27.3% due to the overall increase in crashes.

Weather

Clear16 (72.7%)
14.3%prior 14
Cloudy/Rain3 (13.6%)
Rain2 (9.1%)
Cloudy1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash

Lighting

Daylight16 (72.7%)
14.3%prior 14
Dark - roadway not lighted3 (13.6%)
Dark - lighted roadway2 (9.1%)
Dusk1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field

Road Surface

Dry17 (77.3%)
6.3%prior 16
Wet5 (22.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (38 vehicles)

1
HYUNDAI5 (13.2%)
2
NISSAN4 (10.5%)
3
TOYOTA4 (10.5%)
-42.9%prior 7
4
SUBARU3 (7.9%)
5
HONDA3 (7.9%)
6
CHEVROLET3 (7.9%)
-50.0%prior 6
7
FORD3 (7.9%)
-50.0%prior 6
8
KIA2 (5.3%)
9
MAZDA2 (5.3%)
10
VOLVO1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records

Sex Distribution (54 persons with recorded sex)

Male29 (53.7%)
45.0%prior 20
Female25 (46.3%)
66.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased from 9 in April 2022 to 12 in April 2023. Crashes in 65 mph zones doubled from 2 to 4 incidents year-over-year. Conversely, crashes in 40 mph zones decreased from 3 to 1. Crashes in 25 mph zones saw a slight increase from 2 to 3.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-04-01 through 2023-04-30 (30 days)
  • Geographic scope: WEBSTER, MA
  • Total crash records analyzed: 22
  • Total persons involved: 54
  • Total vehicles involved: 38

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: April 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/webster/april-2023-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 — April 2023 | ThatCarHitMe.com