Monthly Traffic Safety Analysis

57 CRASHES IN
WELLESLEY, MA
JUNE 2024

All metrics benchmarked againstJune 2023

Total crashes in Wellesley, MA increased by 9.6%, from 52 in June 2023 to 57 in June 2024. The most notable shift was a 100% increase in hit-and-run crashes, rising from 2 to 4 incidents year-over-year. Overall injuries also saw an 11.1% increase, from 9 to 10.

57

9.6%was 52

Total Crash Events

0

Persons Killed

10

11.1%was 9

Persons Injured

4

100.0%was 2

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 · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends for Wellesley show an increase in June 2024 compared to June 2023, with total crashes rising by 9.6% from 52 to 57. Total injuries also increased by 11.1%, from 9 to 10, indicating a slight worsening of safety outcomes. Fatal crashes remained at zero in both periods.

4

Hit-and-Run Crashes — June 2024

100.0% vs prior (2)

Hit-and-run crashes doubled year-over-year, increasing from 2 incidents in June 2023 to 4 incidents in June 2024. This resulted in the hit-and-run rate rising from 3.8% to 7% of all crashes. The trend for hit-and-run incidents is upward.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 10.0%

8

Motorists Injured

Prior: 80.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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 Tuesday, with 16 incidents in June 2023, to Monday, with 13 incidents in June 2024. Friday also saw a notable increase in crashes, rising from 4 in June 2023 to 11 in June 2024. The peak hour for crashes shifted from 4 PM with 7 incidents in June 2023 to 12 PM with 7 incidents in June 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of serious injury crashes remained stable at 1 in both June 2023 and June 2024. Minor injury crashes increased from 2 to 3, while possible injury crashes decreased from 5 to 3. The proportion of crashes resulting in no injury increased from 80.8% in June 2023 to 86% in June 2024.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.8%
0.0%prior 1
Minor Injury3minor injury crashes5.3%
50.0%prior 2
Possible Injury3possible injury crashes5.3%
-40.0%prior 5
No Injury49no injury crashes86%
16.7%prior 42

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the leading contributing factor, increasing from 14 crashes in June 2023 to 17 crashes in June 2024, a 21.4% increase in count. Followed too closely decreased by 2 crashes, from 12 to 10, representing a 16.7% reduction in count, but remained the second most frequent factor. Failure to keep in proper lane or running off road saw a significant increase of 3 crashes, rising from 1 to 4 incidents.

Officer-Reported Primary Contributing Cause

Inattention17 (29.8%)21.4%prior 14
Followed too closely10 (17.5%)-16.7%prior 12
No improper driving9 (15.8%)0.0%prior 9
Failed to yield right of way4 (7%)-33.3%prior 6
Failure to keep in proper lane or running off road4 (7%)
Other improper action2 (3.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.5%)
Distracted2 (3.5%)
Visibility obstructed1 (1.8%)
Over-correcting/over-steering1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 37 in June 2023 to 52 in June 2024. Crashes during cloudy conditions significantly decreased from 9 to 1 incident year-over-year. The number of crashes on dry road surfaces increased from 47 to 52, while crashes on wet surfaces remained stable at 5.

Weather

Clear52 (91.2%)
40.5%prior 37
Rain3 (5.3%)
Cloudy1 (1.8%)
-88.9%prior 9
Cloudy/Rain1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash

Lighting

Daylight53 (93.0%)
20.5%prior 44
Dark - roadway not lighted2 (3.5%)
Dark - lighted roadway1 (1.8%)
-83.3%prior 6
Dusk1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field

Road Surface

Dry52 (91.2%)
10.6%prior 47
Wet5 (8.8%)
0.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 98 in June 2023 to 107 in June 2024. TOYOTA vehicles involved in crashes more than doubled, increasing from 11 to 23, becoming the most frequently involved make. In terms of demographics, the 16-20 age group saw a decrease in representation from 17 to 9 persons involved in crashes, while the 21-25 age group increased from 8 to 11 persons.

Top Vehicle Makes (107 vehicles)

1
TOYOTA23 (21.5%)
109.1%prior 11
2
HONDA15 (14%)
36.4%prior 11
3
FORD10 (9.3%)
0.0%prior 10
4
VOLVO5 (4.7%)
0.0%prior 5
5
AUDI5 (4.7%)
-28.6%prior 7
6
BMW5 (4.7%)
7
JEEP5 (4.7%)
8
NISSAN4 (3.7%)
-20.0%prior 5
9
MAZDA4 (3.7%)
10
CHEVROLET4 (3.7%)
-42.9%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records

12 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (106 persons with recorded sex)

Male72 (67.9%)
30.9%prior 55
Female34 (32.1%)
-27.7%prior 47

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 26 in June 2023 to 20 in June 2024. Conversely, crashes in 50 mph zones increased from 14 to 22 incidents. Additionally, 4 crashes occurred in 10 mph zones in June 2024, a category not present in the June 2023 data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-06-01 through 2024-06-30 (30 days)
  • Geographic scope: WELLESLEY, MA
  • Total crash records analyzed: 57
  • Total persons involved: 124
  • Total vehicles involved: 107

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: June 2024." Published June 21, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wellesley/june-2024-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

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Wellesley, MA Crash Report — June 2024 | ThatCarHitMe.com