Monthly Traffic Safety Analysis

34 CRASHES IN
WEBSTER, MA
MARCH 2025

All metrics benchmarked againstMarch 2024

In March 2025, WEBSTER recorded 34 total crashes, identical to the 34 crashes reported in March 2024. However, fatalities increased significantly from 0 in March 2024 to 1 in March 2025, marking a notable shift in crash outcomes. Hit-and-run incidents also saw a substantial increase, rising from 1 to 4 crashes.

34

Total Crash Events

1

Persons Killed

9

Persons Injured

4

300.0%was 1

Hit-and-Run Crashes

Note: "Persons Killed" (1) 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 · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Total crashes remained stable at 34 incidents for both March 2025 and March 2024, indicating no change in the overall number of crash events. Despite this stability in total crashes, the number of fatalities increased from 0 to 1, representing an upward trend in crash severity. The rate of hit-and-run crashes also trended upwards.

4

Hit-and-Run Crashes — March 2025

300.0% vs prior (1)

Hit-and-run crashes increased significantly from 1 in March 2024 to 4 in March 2025. This change resulted in the hit-and-run rate rising from 2.9% of all crashes to 11.8% year-over-year, indicating an upward trend in such incidents.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

9

Motorists Injured

Prior: 90.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

In March 2025, the peak day for crashes shifted to Friday with 9 incidents, compared to Thursday with 9 incidents in March 2024. The peak hour also shifted from 4 PM with 6 crashes in March 2024 to 5 PM with 5 crashes in March 2025. These changes indicate a slight shift in the concentration of crashes during the week and day.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The most significant change in crash severity is the increase in fatal crashes, with 1 fatal crash in March 2025 compared to 0 in March 2024. While total injuries remained constant at 9 in both periods, the distribution of injury severity shifted. Minor injury crashes decreased from 6 (17.6% of crashes) to 3 (8.8% of crashes), and possible injury crashes increased from 1 (2.9%) to 3 (8.8%).

Outcome by Severity (Crash Events)

Fatal1fatal crashes2.9%
Minor Injury3minor injury crashes8.8%
-50.0%prior 6
Possible Injury3possible injury crashes8.8%
200.0%prior 1
No Injury26no injury crashes76.5%
-3.7%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record

Top Contributing Factors

The count of crashes attributed to "No improper driving" increased from 10 in March 2024 to 12 in March 2025. Conversely, crashes due to "Inattention" decreased from 9 to 6, and "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" decreased from 3 to 2. A notable increase was observed in "Other improper action" factors, rising from 1 crash to 4 crashes.

Officer-Reported Primary Contributing Cause

No improper driving12 (35.3%)20.0%prior 10
Inattention6 (17.6%)-33.3%prior 9
Other improper action4 (11.8%)
Failure to keep in proper lane or running off road2 (5.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (5.9%)
Failed to yield right of way2 (5.9%)
Fatigued/asleep1 (2.9%)
Physical impairment1 (2.9%)
Distracted1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes occurring on dry road surfaces increased from 23 in March 2024 to 31 in March 2025, while crashes on wet surfaces decreased from 9 to 2. Weather conditions remained similar, with 20 crashes occurring in clear weather in both periods. Crashes during daylight hours decreased slightly from 26 to 24, while those in dark conditions without roadway lighting increased from 1 to 4.

Weather

Clear20 (60.6%)
0.0%prior 20
Cloudy8 (24.2%)
Clear/Clear2 (6.1%)
Clear/Other2 (6.1%)
Rain/Rain1 (3.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash

Lighting

Daylight24 (75.0%)
-7.7%prior 26
Dark - roadway not lighted4 (12.5%)
Dark - unknown roadway lighting2 (6.3%)
Dark - lighted roadway1 (3.1%)
-83.3%prior 6
Dusk1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field

Road Surface

Dry31 (93.9%)
34.8%prior 23
Wet2 (6.1%)
-77.8%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes saw some shifts year-over-year. FORD crashes increased from 5 in March 2024 to 10 in March 2025, and HONDA crashes increased from 3 to 8. Conversely, TOYOTA crashes decreased from 12 to 10, and NISSAN, which was the second most frequent make in March 2024 with 7 crashes, is no longer in the top five for March 2025.

Top Vehicle Makes (60 vehicles)

1
FORD10 (16.7%)
100.0%prior 5
2
TOYOTA10 (16.7%)
-16.7%prior 12
3
HONDA8 (13.3%)
4
CHEVROLET6 (10%)
5
HYUNDAI3 (5%)
6
JEEP3 (5%)
7
MERCEDES-BENZ2 (3.3%)
8
BUIC2 (3.3%)
9
INFI2 (3.3%)
10
NISSAN2 (3.3%)
-71.4%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records

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

Sex Distribution (57 persons with recorded sex)

Male29 (50.9%)
-9.4%prior 32
Female28 (49.1%)
-12.5%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone increased from 13 in March 2024 to 21 in March 2025. Crashes in the 25 mph zone decreased from 8 to 5 during the same period. A fatal crash occurred in a 40 mph zone in March 2025, where no fatal crashes were recorded in any speed zone in March 2024.

Fatal crashes by zone: 40 mph: 1 of 1 (100%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-03-01 through 2025-03-31 (31 days)
  • Geographic scope: WEBSTER, MA
  • Total crash records analyzed: 34
  • Total persons involved: 71
  • Total vehicles involved: 60

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: March 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/webster/march-2025-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 — March 2025 | ThatCarHitMe.com