ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEBSTER, MA · 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/webster/2024-annual-report
Yearly Traffic Safety Analysis
342 CRASHES IN
WEBSTER, MA
2024
In Webster, total traffic crashes increased from 327 in the prior year to 342 in the current year, a rise of 4.6%. While total injuries saw a decrease, the number of fatal crashes doubled from one to two. The most notable shift was a 300% increase in crashes attributed to failure to keep in the proper lane, which rose from 4 to 16 incidents.
342
▲ 4.6%was 327
Total Crash Events
2
Persons Killed
113
▼ -8.1%was 123
Persons Injured
15
▲ 7.1%was 14
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends in Webster show a mixed picture year-over-year. The total number of crashes increased by 4.6%, from 327 to 342. However, the number of people injured in these incidents decreased by 8.1%, from 123 to 113, while the number of fatalities remained constant at two.
15
Hit-and-Run Crashes — 2024
▲ 7.1% vs prior (14)
The number of hit-and-run crashes remained relatively stable, with a slight increase from 14 incidents in the prior year to 15 in the current year. The corresponding hit-and-run rate saw a negligible change, moving from 4.3% to 4.4% of all crashes.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
2
Pedestrians Injured
5
Cyclists Injured
106
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. The peak day for crashes moved from Friday (63 crashes) in the prior year to Thursday (65 crashes) in the current year. Similarly, the peak hour for collisions shifted an hour earlier, from 5 p.m. in the prior year (46 crashes) to 4 p.m. in the current year (38 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes showed a notable shift year-over-year. The number of fatal crashes doubled from 1 to 2, increasing the fatal crash rate from 0.3% to 0.6% of all crashes. Conversely, serious injury crashes decreased significantly, from 5 incidents (1.5% of total) in the prior year to 2 incidents (0.6%) in the current year. The proportion of crashes resulting in no injuries increased from 69.1% to 72.8%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
Comparing contributing factors, 'Inattention' remained a leading cause, with a slight increase in count from 71 to 74 crashes. The count of crashes involving 'Failure to keep in proper lane or running off road' quadrupled, increasing from 4 to 16 incidents. Crashes attributed to a driver being 'Distracted' more than doubled, rising from 7 to 15. In contrast, incidents involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased by 33.3%, from 27 to 18 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Year-over-year data shows a higher number of crashes occurred in favorable conditions. Crashes in 'Daylight' increased from 224 to 254, and their share of the total rose from 68.5% to 74.3%. Similarly, crashes on 'Dry' road surfaces increased from 248 to 270. Collisions during 'Rain' decreased from 41 to 20, while those in 'Snow' increased from 7 to 17.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top makes of vehicles involved in crashes remained largely consistent, with Toyota, Ford, and Chevrolet being the most frequent in both years. Toyota involvement increased from 94 to 103 vehicles, while Chevrolet involvement rose from 43 to 66. In terms of persons involved, the 26-34 age group remained the largest, with its count increasing from 117 to 129 individuals.
Top Vehicle Makes (621 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
65 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (733 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes continue to be most frequent in 30 MPH zones, with the count increasing from 154 to 180 incidents year-over-year. In the current year, one of the two fatal crashes occurred in a 30 MPH zone, where none had occurred in the prior year. The other fatal crash happened in a 65 MPH zone, consistent with the prior year where the sole fatal crash also occurred in a 65 MPH zone.
Fatal crashes by zone: 30 mph: 1 of 180 (0.556%) · 65 mph: 1 of 29 (3.448%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: WEBSTER, MA
- Total crash records analyzed: 342
- Total persons involved: 805
- Total vehicles involved: 621
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/webster/2024-annual-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved