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YEAR-OVER-YEAR CRASH REPORT · WEST BOYLSTON, MA · 2022
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/2022-annual-report
Yearly Traffic Safety Analysis
123 CRASHES IN
WEST BOYLSTON, MA
2022
In 2022, West Boylston recorded 123 total vehicle crashes, a 20.6% decrease from the 155 crashes documented in 2021. While total crashes and injuries (51 to 43) declined, the number of fatalities remained constant at two deaths in both periods. The most notable year-over-year shift was the significant increase in serious injury crashes, which rose from one in 2021 to five in 2022.
123
▼ -20.6%was 155
Total Crash Events
2
Persons Killed
43
▼ -15.7%was 51
Persons Injured
5
▲ 25.0%was 4
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for West Boylston indicates a downward trend year-over-year, with total crashes falling by 20.6% from 155 in 2021 to 123 in 2022. The number of people injured in these incidents also decreased from 51 to 43. However, the number of fatalities held steady at two in both years, resulting in a higher fatal crash rate in 2022 (1.63%) compared to 2021 (1.29%).
5
Hit-and-Run Crashes — 2022
▲ 25.0% vs prior (4)
The number of hit-and-run incidents increased from four in 2021 to five in 2022. Due to the overall decrease in total crashes for the year, the hit-and-run rate saw a more pronounced increase, rising from 2.6% of all crashes in 2021 to 4.1% in 2022. This indicates an upward trend in the proportion of crashes where a driver left the scene.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
41
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some consistency and some shifts between the two periods. Thursday remained the peak day for crashes in both 2022 (26 crashes) and 2021 (35 crashes), though the volume on that day decreased. The peak hour for collisions shifted slightly later in the afternoon, moving from the 4 p.m. hour in 2021 (18 crashes) to the 5 p.m. hour in 2022 (16 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the number of fatal crashes remained unchanged at two, the fatal crash rate increased from 1.29% in 2021 to 1.63% in 2022 due to the lower overall crash volume. A significant change occurred in crash severity, with serious injury crashes increasing from one incident (0.6% of total) in 2021 to five incidents (4.1% of total) in 2022. Consequently, the share of crashes resulting in either a fatality or serious injury rose from 1.9% in 2021 to 5.7% in 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors showed some shifts in volume despite consistent rankings. Crashes where 'Failed to yield right of way' was a factor held steady at 16 in both 2021 and 2022. The count of crashes attributed to 'Inattention' was halved, dropping from 14 in 2021 to 7 in 2022. Conversely, crashes involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' more than doubled, increasing from 3 to 8 over the same period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In both 2021 and 2022, the majority of crashes occurred in clear weather, during daylight hours, and on dry road surfaces. The proportion of crashes happening on dry roads remained stable, accounting for 72.9% of crashes in 2021 and 74.0% in 2022. Similarly, the share of crashes occurring during daylight was consistent at 63.9% in 2021 and 60.2% in 2022, indicating no major shift in crash conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in collisions remained consistent year-over-year, with Toyota, Ford, and Honda ranking as the top three in both periods. An analysis of persons involved in crashes shows the 26-34 age group had the highest count in both years, and this group's share of total persons involved increased from 16.4% in 2021 to 18.7% in 2022. Conversely, the representation of the 16-20 age group decreased from 13.5% of all persons involved in 2021 to 10.8% in 2022.
Top Vehicle Makes (207 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
10 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (225 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
There was a noticeable shift in where crashes occurred relative to posted speed limits. Collisions in 40 mph zones increased from 40 in 2021 to become the most frequent zone with 50 crashes in 2022. Conversely, crashes in 30 mph zones decreased from 44 to 33 over the same period. One fatal crash occurred in a 30 mph zone in both years, while the second fatality shifted from a 35 mph zone in 2021 to a 65 mph zone in 2022.
Fatal crashes by zone: 30 mph: 1 of 33 (3.03%) · 65 mph: 1 of 25 (4%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: WEST BOYLSTON, MA
- Total crash records analyzed: 123
- Total persons involved: 251
- Total vehicles involved: 207
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-boylston/2022-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved