ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEST BOYLSTON, MA · OCTOBER 2023
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/west-boylston/october-2023-report
Monthly Traffic Safety Analysis
12 CRASHES IN
WEST BOYLSTON, MA
OCTOBER 2023
Total crashes in WEST BOYLSTON, MA increased by 33.3% year-over-year, rising from 9 incidents in October 2022 to 12 in October 2023. The most notable shift was the significant increase in crashes attributed to 'No improper driving,' which rose from 2 incidents in the prior period to 10 in the current period. Fatalities remained at 0 in both periods, while total injuries held steady at 1.
12
▲ 33.3%was 9
Total Crash Events
0
Persons Killed
1
Persons Injured
0
▼ -100.0%was 1
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash frequency in WEST BOYLSTON showed an upward trend, with total crashes increasing from 9 in October 2022 to 12 in October 2023, marking a 33.3% rise. Despite this increase in total incidents, the number of fatalities remained stable at 0 in both periods, and total injuries also held constant at 1. The data suggests a rise in non-fatal crash incidents year-over-year.
Vulnerable Road User Casualties
0
Motorists Killed
1
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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 Saturday, with 2 incidents in October 2022, to Friday, which recorded 5 crashes in October 2023. The peak crash hour also moved, from 10 p.m. with 1 crash in the prior period, to 6 p.m. with 3 crashes in the current period. This indicates a shift in crash concentration towards Friday evenings in the current year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Both October 2022 and October 2023 recorded 0 fatalities and 1 injury, indicating no change in the number of severe outcomes. In the prior period, 1 of 9 crashes (11.1% of total crashes) resulted in a possible injury, while in the current period, 1 of 12 crashes (8.3% of total crashes) resulted in a minor injury. Despite the increase in total crashes, the proportion of crashes involving injuries slightly decreased year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record
Top Contributing Factors
The most significant change in contributing factors was 'No improper driving,' which increased from 2 crashes in October 2022 to 10 crashes in October 2023. Factors such as 'Driving too fast for conditions,' 'Failed to yield right of way,' and 'Failure to keep in proper lane or running off road,' each present in 2 crashes in the prior period, were not cited in the current period. Conversely, 'Disregarded traffic signs, signals, road markings' appeared as a factor in 1 crash in October 2023 but was not present in October 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 6 in October 2022 to 9 in October 2023, while those in rainy conditions rose from 2 to 3. The number of crashes on wet road surfaces also increased from 2 to 3 year-over-year. Additionally, 1 crash occurred in 'Dark - roadway not lighted' conditions in October 2023, a condition not observed in the prior period's data.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field
Vehicles & Demographics
Top Vehicle Makes (20 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records
Sex Distribution (23 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph speed zones increased from 2 in October 2022 to 5 in October 2023, and those in 40 mph zones also rose from 2 to 5 crashes. The number of crashes in 65 mph zones remained stable at 2 for both periods. The 35 mph speed zone, which accounted for 2 crashes in the prior period, recorded no crashes in the current period, while no fatal crashes occurred in any speed zone in either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-10-01 through 2023-10-31 (31 days)
- Geographic scope: WEST BOYLSTON, MA
- Total crash records analyzed: 12
- Total persons involved: 23
- Total vehicles involved: 20
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). "WEST BOYLSTON, MA Crash Intelligence Report: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-boylston/october-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-10-01 – 2023-10-31
Generated: June 21, 2026 · All rights reserved