ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WELLESLEY, MA · NOVEMBER 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/wellesley/november-2022-report
Monthly Traffic Safety Analysis
71 CRASHES IN
WELLESLEY, MA
NOVEMBER 2022
In November 2022, Wellesley experienced 71 total crashes, marking a 26.8% increase compared to the 56 crashes recorded in November 2021. The most significant year-over-year shift was an 80% decrease in hit-and-run crashes, falling from 5 to 1. Total injuries also rose by 25%, from 8 to 10.
71
▲ 26.8%was 56
Total Crash Events
0
Persons Killed
10
▲ 25.0%was 8
Persons Injured
1
▼ -80.0%was 5
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash data for Wellesley indicates an upward trend year-over-year, with total crashes increasing by 26.8% from 56 in November 2021 to 71 in November 2022. This rise in crash incidents was accompanied by a 25% increase in total injuries, from 8 to 10. There were no fatalities reported in either period.
1
Hit-and-Run Crashes — November 2022
▼ -80.0% vs prior (5)
Hit-and-run crashes significantly decreased by 80%, falling from 5 incidents in November 2021 to just 1 in November 2022. Consequently, the hit-and-run rate dropped from 8.9% of all crashes in November 2021 to 1.4% in November 2022. This indicates a positive trend in reducing hit-and-run incidents.
Vulnerable Road User Casualties
0
Motorists Killed
10
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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 Friday in November 2021 (15 crashes) to Wednesday in November 2022 (18 crashes). While the peak hour remained 5 p.m. in both periods, the number of crashes during this hour increased from 8 to 9. Crashes on Mondays decreased from 13 to 9, while crashes on Wednesdays saw a substantial increase from 2 to 18.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
No fatal crashes occurred in either November 2021 or November 2022. Total injuries increased by 25%, from 8 in November 2021 to 10 in November 2022. Serious injuries (Severity A) decreased from 3 crashes in November 2021 to 1 crash in November 2022, while minor (Severity B) and possible (Severity C) injury crashes remained constant at 4 and 1, respectively. The proportion of crashes resulting in no injury increased from 80.4% to 90.1%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor shifted from 'No improper driving' in November 2021 to 'Inattention' in November 2022. Crashes attributed to 'Inattention' more than doubled, increasing by 112.5% from 8 to 17, while 'No improper driving' decreased by 31.3% from 16 to 11. 'Followed too closely' also saw a significant increase of 60%, from 5 to 8 crashes, and 'Failed to yield right of way' doubled from 3 to 6 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 42 to 55, while those in 'Rain' decreased from 5 to 3. 'Cloudy' conditions remained constant at 6 crashes in both periods. Crashes during 'Daylight' increased from 32 to 44, and those in 'Dark - lighted roadway' conditions rose from 15 to 22. The number of crashes on 'Dry' road surfaces increased from 45 to 60, and on 'Wet' surfaces from 9 to 11.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 34.9%, from 103 in November 2021 to 139 in November 2022. The age group 45-54 saw the largest increase in persons involved, rising from 14 to 27, while the 26-34 age group also significantly increased from 14 to 25. The number of males involved increased from 50 to 79, and females from 54 to 69. Toyota remained the top vehicle make involved, increasing from 21 to 23, and Jeep crashes doubled from 6 to 12.
Top Vehicle Makes (139 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records
7 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (148 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone increased from 32 in November 2021 to 39 in November 2022, maintaining its position as the zone with the most crashes. The 20 mph zone saw a notable increase in crashes from 1 to 5, and the 25 mph zone also rose from 1 to 4 crashes. Conversely, crashes in the 50 mph zone slightly decreased from 14 to 13. No fatal crashes were reported across any speed zones in either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-11-01 through 2022-11-30 (30 days)
- Geographic scope: WELLESLEY, MA
- Total crash records analyzed: 71
- Total persons involved: 157
- Total vehicles involved: 139
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). "WELLESLEY, MA Crash Intelligence Report: November 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wellesley/november-2022-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: 2022-11-01 – 2022-11-30
Generated: June 21, 2026 · All rights reserved