ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BURLINGTON, MA · JUNE 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/burlington/june-2023-report
Monthly Traffic Safety Analysis
51 CRASHES IN
BURLINGTON, MA
JUNE 2023
Total crashes in Burlington, MA increased significantly by 37.8%, rising from 37 in June 2022 to 51 in June 2023. This notable increase in overall crash volume was accompanied by a decrease in total injuries, which fell from 17 to 10. The proportion of crashes attributed to "No improper driving" also saw a substantial increase, becoming the leading factor in the current period.
51
▲ 37.8%was 37
Total Crash Events
0
Persons Killed
10
▼ -41.2%was 17
Persons Injured
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a notable increase in crashes, with total incidents rising by 37.8% year-over-year, from 37 crashes in June 2022 to 51 crashes in June 2023. Despite this increase in crash volume, the total number of injuries decreased by 41.2%, from 17 to 10. Fatalities remained at zero for both periods.
2
Hit-and-Run Crashes — June 2023
▼ 0.0% vs prior (2)
The number of hit-and-run crashes remained constant at 2 for both June 2022 and June 2023. However, due to the overall increase in total crashes, the hit-and-run rate decreased from 5.4% in the prior period to 3.9% in the current period. This indicates a relative decrease in the proportion of crashes involving a hit-and-run.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
9
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted year-over-year. In June 2023, Friday became the peak day for crashes with 13 incidents, compared to Thursday with 8 incidents in June 2022. The peak hour for crashes also moved from 3 PM with 5 incidents in the prior period to 6 PM with 6 incidents in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes increased, the severity distribution showed a decrease in injuries. Total injuries declined from 17 in June 2022 to 10 in June 2023, a decrease of 41.2%. The current period recorded one serious injury, four minor injuries, and three possible injuries, whereas the prior period had eight minor injuries and six possible injuries. Fatal crashes and fatalities remained at zero in both periods.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record
Top Contributing Factors
Contributing factors saw shifts in both counts and rankings. Crashes attributed to "No improper driving" increased by 200%, from 4 in June 2022 to 12 in June 2023, making it the top factor with a 23.5% share of crashes. "Inattention" also saw a 125% increase in count, rising from 4 to 9 crashes, and its share grew from 10.8% to 17.6%. Conversely, "Followed too closely" decreased by 10% in count, from 10 to 9 crashes, and its share dropped from 27% to 17.6%.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes under "Clear" weather conditions increased by 5, from 27 in June 2022 to 32 in June 2023. Incidents during "Dark - lighted roadway" conditions also rose significantly by 7, from 3 to 10. Crashes on "Wet" road surfaces increased by 7, from 3 in the prior period to 10 in the current period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased by 38.5%, from 91 to 126, and vehicles involved rose by 32.5%, from 77 to 102. The age groups 35-44 and 45-54 saw the largest increases in persons involved, each rising by 15. Toyota remained the most common vehicle make involved, with its count increasing from 14 to 30, a 114% rise.
Top Vehicle Makes (102 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records
9 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 · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone doubled, increasing from 7 in June 2022 to 14 in June 2023. Similarly, crashes in the 35 mph zone increased by 40%, from 10 to 14. There was a decrease of 2 crashes in the 55 mph zone, falling from 17 to 15. Neither period recorded any fatal crashes in any speed zone.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-06-01 through 2023-06-30 (30 days)
- Geographic scope: BURLINGTON, MA
- Total crash records analyzed: 51
- Total persons involved: 126
- Total vehicles involved: 102
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). "BURLINGTON, MA Crash Intelligence Report: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/burlington/june-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: 2023-06-01 – 2023-06-30
Generated: June 21, 2026 · All rights reserved