Monthly Traffic Safety Analysis

26 CRASHES IN
WEBSTER, MA
SEPTEMBER 2023

All metrics benchmarked againstSeptember 2022

Total crashes decreased from 32 in September 2022 to 26 in September 2023, representing an 18.75% reduction year-over-year. A notable shift includes the number of crashes resulting in injuries, which decreased by 42.86% from 14 in the prior period to 8 in the current period. Additionally, hit-and-run crashes increased from 0 to 2.

26

-18.8%was 32

Total Crash Events

0

Persons Killed

8

-42.9%was 14

Persons Injured

2

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. 4 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Webster showed a declining trend year-over-year, with total crashes decreasing by 18.75% from 32 in September 2022 to 26 in September 2023. This reduction indicates a positive trend in crash safety for the period.

2

Hit-and-Run Crashes — September 2023

7.7% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

7

Motorists Injured

Prior: 14-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted between the two periods. In September 2023, the peak day for crashes was Thursday with 6 incidents, while in September 2022, Friday was the peak day with 7 incidents. The peak hour for crashes also shifted from 2 PM in September 2022 to 4 PM in September 2023, with both hours recording 5 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both September 2022 and September 2023. The total number of injured persons decreased significantly from 14 in the prior period to 8 in the current period, a 42.86% reduction. Crashes resulting in a serious injury increased from 0 in September 2022 to 1 in September 2023, while minor injury crashes decreased from 6 to 4.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.8%
Minor Injury4minor injury crashes15.4%
-33.3%prior 6
No Injury17no injury crashes65.4%
-22.7%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Most severe injury per crash record

Top Contributing Factors

Among common contributing factors, "No improper driving" decreased by 1 crash, from 10 in September 2022 to 9 in September 2023. "Inattention" saw the largest decrease, dropping by 5 crashes from 9 to 4. Conversely, crashes attributed to "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" increased by 2, from 1 to 3 crashes. "Failed to yield right of way" and "Failure to keep in proper lane or running off road" remained unchanged with 2 and 1 crash respectively.

Officer-Reported Primary Contributing Cause

No improper driving9 (34.6%)-10.0%prior 10
Inattention4 (15.4%)-55.6%prior 9
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (11.5%)
Followed too closely2 (7.7%)
Failed to yield right of way2 (7.7%)
Failure to keep in proper lane or running off road1 (3.8%)
Over-correcting/over-steering1 (3.8%)
Glare1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Clear" weather decreased by 11, from 28 in September 2022 to 17 in September 2023. Conversely, crashes in "Rain" conditions increased by 4, from 2 to 6. Similarly, crashes on "Dry" road surfaces decreased by 10, from 28 to 18, while those on "Wet" surfaces increased by 4, from 4 to 8. Crashes during "Daylight" decreased by 11, from 28 to 17, while those in "Dark - lighted roadway" increased by 3, from 2 to 5.

Weather

Clear17 (68.0%)
-39.3%prior 28
Rain6 (24.0%)
Cloudy1 (4.0%)
Rain/Cloudy1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Weather condition at time of crash

Lighting

Daylight17 (65.4%)
-39.3%prior 28
Dark - lighted roadway5 (19.2%)
Dusk2 (7.7%)
Dark - unknown roadway lighting1 (3.8%)
Dawn1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Lighting condition field

Road Surface

Dry18 (69.2%)
-35.7%prior 28
Wet8 (30.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (43 vehicles)

1
TOYOTA10 (23.3%)
-16.7%prior 12
2
FORD7 (16.3%)
3
CHEVROLET4 (9.3%)
-55.6%prior 9
4
NISSAN3 (7%)
5
HONDA3 (7%)
-57.1%prior 7
6
KAWK1 (2.3%)
7
KIA1 (2.3%)
8
MAZDA1 (2.3%)
9
MNNI1 (2.3%)
10
PTRB1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Vehicle unit records

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

Sex Distribution (42 persons with recorded sex)

Male30 (71.4%)
-26.8%prior 41
Female12 (28.6%)
-61.3%prior 31

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones saw some shifts. Crashes in 30 mph zones decreased by 6, from 18 in September 2022 to 12 in September 2023. Conversely, crashes in 35 mph zones increased by 2, from 2 to 4. There were no fatalities in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · 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: 2023-09-01 through 2023-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-09-01 through 2023-09-30 (30 days)
  • Geographic scope: WEBSTER, MA
  • Total crash records analyzed: 26
  • Total persons involved: 50
  • Total vehicles involved: 43

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: September 2023." Published June 21, 2026. Reporting period: 2023-09-01 to 2023-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/webster/september-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 — September 2023 | ThatCarHitMe.com