ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WELLESLEY, 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/wellesley/2024-annual-report
Yearly Traffic Safety Analysis
687 CRASHES IN
WELLESLEY, MA
2024
In 2024, Wellesley recorded 687 total crashes, a 6.5% increase from the 645 crashes reported in 2023. While total crashes and injuries both rose, the most notable change was the elimination of traffic fatalities, which dropped from one in the prior year to zero in the current period. Overall injuries increased by 20.5% year-over-year, from 122 to 147.
687
▲ 6.5%was 645
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
147
▲ 20.5%was 122
Persons Injured
48
▲ 20.0%was 40
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. 20 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
Crash data for Wellesley indicates an upward trend in traffic incidents year-over-year. Total crashes increased by 6.5%, rising from 645 in 2023 to 687 in 2024. This was accompanied by a more substantial 20.5% increase in total injuries, which grew from 122 to 147.
48
Hit-and-Run Crashes — 2024
▲ 20.0% vs prior (40)
Hit-and-run incidents increased in both absolute numbers and as a percentage of total crashes. The count of hit-and-run crashes rose by 20%, from 40 in 2023 to 48 in 2024. This corresponds to an increase in the hit-and-run rate, which climbed from 6.2% to 7.0% of all crashes, indicating a rising trend for this type of incident.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
7
Pedestrians Injured
10
Cyclists Injured
128
Motorists Injured
2
Other 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 temporal patterns of crashes in Wellesley showed some shifts between the two periods. While Tuesday remained the peak day for crashes in both 2023 (122 crashes) and 2024 (138 crashes), the peak hour for incidents changed. In 2023, the highest volume occurred at 5 PM with 64 crashes, whereas in 2024, the peak shifted to 12 PM, also with 64 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
Crash severity improved with the elimination of fatalities, as the count of fatal crashes dropped from one in 2023 to zero in 2024. However, the number of serious injury crashes doubled from 5 to 10. The count of minor injury crashes also rose from 57 to 78, while possible injury crashes decreased from 42 to 25. The overall share of crashes resulting in no injury remained largely unchanged, at 80.6% in 2024 compared to 81.7% in the prior year.
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
While 'Inattention' remained a leading contributing factor in both years, its count decreased from 150 incidents in 2023 to 139 in 2024. The most significant shift was in crashes attributed to 'Followed too closely,' which saw a 52.3% increase in count, rising from 86 to 131 incidents and becoming the second most common factor. Crashes involving 'Failed to yield right of way' also increased in count from 61 to 68.
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
The vast majority of crashes in both periods occurred in clear and dry conditions during daylight hours. In 2024, 78.7% of crashes happened in daylight, up from 74.6% in 2023. Similarly, crashes on dry road surfaces accounted for 83.7% of incidents in 2024, a slight increase from 82.8% in the prior year. The number of crashes during rain increased slightly from 35 to 40, while crashes in snow conditions increased from 8 to 15.
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 three vehicle makes involved in crashes remained consistent year-over-year, with Toyota, Honda, and Ford leading in both periods and seeing an increase in their total counts. Analysis of persons involved in crashes shows a shift in age demographics. The representation of individuals aged 16-20 decreased from a 11.3% share of all persons in 2023 to an 8.8% share in 2024. Conversely, the share of persons aged 21-25 increased from 8.8% to 10.8%.
Top Vehicle Makes (1,298 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
106 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,362 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
The distribution of crashes across speed zones shifted, with a notable increase in incidents occurring in higher speed zones. Crashes in 50 mph zones rose from 171 in 2023 to 204 in 2024, and those in 55 mph zones increased from 46 to 53. Conversely, crashes in 30 mph zones saw a slight decrease from 323 to 313. The single fatality in 2023 occurred in a 50 mph zone, while no fatalities were recorded in any speed zone in 2024.
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: WELLESLEY, MA
- Total crash records analyzed: 687
- Total persons involved: 1,504
- Total vehicles involved: 1,298
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: 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/wellesley/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