ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WELLESLEY, MA · MAY 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/wellesley/may-2023-report
Monthly Traffic Safety Analysis
58 CRASHES IN
WELLESLEY, MA
MAY 2023
In Wellesley, May 2023 saw a 45% increase in total crashes, rising from 40 in May 2022 to 58. Despite this increase, total injuries decreased by 58.8%, from 17 to 7. The most notable year-over-year shift was a 300% increase in hit-and-run crashes, rising from 1 to 4.
58
▲ 45.0%was 40
Total Crash Events
0
Persons Killed
7
▼ -58.8%was 17
Persons Injured
4
▲ 300.0%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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a rise in total crash incidents, with a 45% increase from 40 crashes in May 2022 to 58 crashes in May 2023. Conversely, the total number of injuries decreased substantially by 58.8%, from 17 to 7 over the same period. Fatalities remained at zero for both months.
4
Hit-and-Run Crashes — May 2023
▲ 300.0% vs prior (1)
Hit-and-run crashes increased significantly from 1 in May 2022 to 4 in May 2023, marking a 300% increase in count. This led to the hit-and-run crash rate rising from 2.5% of all crashes to 6.9% year-over-year. The data indicates an upward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
5
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
In May 2023, Wednesday emerged as the peak day for crashes with 15 incidents, a notable shift from May 2022 where multiple days, including Friday, recorded 7 crashes. The peak crash hour remained 5 PM in both periods, with the count increasing from 5 crashes in May 2022 to 8 crashes in May 2023. This suggests a consistent rush hour risk, but a shift in the busiest weekday for incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes reported in either May 2022 or May 2023. Total injuries decreased significantly from 17 in May 2022 to 7 in May 2023, including a reduction from 2 serious injuries to zero. The proportion of crashes resulting in no injury increased from 70% in May 2022 to 84.5% in May 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record
Top Contributing Factors
Inattention became the leading contributing factor in May 2023, increasing from 8 crashes in May 2022 to 17 crashes. While 'No improper driving' remained constant at 12 crashes, 'Followed too closely' saw a 300% increase in count, rising from 1 crash to 4 crashes. Factors such as 'Distracted,' 'Failed to yield right of way,' and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' each increased by 2 crashes year-over-year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 30 in May 2022 to 43 in May 2023, while those in 'Rain' conditions rose from 1 to 4 crashes. The number of crashes on 'Dry' road surfaces increased from 36 to 52, and on 'Wet' surfaces from 4 to 5. The majority of crashes in both periods continued to occur during 'Daylight,' with an increase from 31 to 51 incidents.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field
Vehicles & Demographics
Toyota vehicles were involved in 23 crashes in May 2023, a significant increase from 9 in May 2022, maintaining its top position. Honda also saw a notable rise in involvement, from 5 crashes to 14 crashes year-over-year. Jeep and Ford vehicle involvement remained stable, with 9 and 7 crashes respectively in both periods.
Top Vehicle Makes (110 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records
16 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (112 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone increased from 24 in May 2022 to 33 in May 2023, continuing to be the most common zone for incidents. Crashes in the 50 mph zone also rose notably from 4 to 11. Conversely, crashes in the 55 mph zone decreased from 7 to 3, indicating a shift away from higher speed roadways for incidents. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-05-01 through 2023-05-31 (31 days)
- Geographic scope: WELLESLEY, MA
- Total crash records analyzed: 58
- Total persons involved: 129
- Total vehicles involved: 110
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: May 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wellesley/may-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: 2023-05-01 – 2023-05-31
Generated: June 21, 2026 · All rights reserved