Monthly Traffic Safety Analysis

65 CRASHES IN
BURLINGTON, MA
DECEMBER 2025

All metrics benchmarked againstDecember 2024

In December 2025, Burlington experienced 65 crashes, a decrease from the 72 crashes reported in December 2024. This represents a 9.7% reduction in total crashes year-over-year. The most notable shift was a 27.3% decrease in total injuries, from 22 in the prior year to 16 in the current period.

65

▼ -9.7%was 72

Total Crash Events

0

Persons Killed

16

▼ -27.3%was 22

Persons Injured

3

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 · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for December 2025 shows a declining trend compared to December 2024, with total crashes decreasing by 9.7% from 72 to 65. Total injuries also saw a significant reduction, falling by 27.3% from 22 to 16. Fatalities remained at zero in both periods.

3

Hit-and-Run Crashes — December 2025

▼ 0.0% vs prior (3)

The number of hit-and-run crashes remained constant at 3 in both December 2024 and December 2025. The hit-and-run rate saw a slight increase, rising from 4.2% in the prior period to 4.6% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 0→%

15

Motorists Injured

Prior: 22↓-31.8%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · 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 in December 2024, with 14 crashes, to Sunday in December 2025, which recorded 16 crashes. However, the peak hour for crashes remained consistent at 5 PM in both periods, with 8 crashes recorded at this time in both December 2024 and December 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities in either December 2024 or December 2025. Total injuries decreased from 22 in the prior period to 16 in the current period, representing a 27.3% reduction. Specifically, minor injuries decreased from 14 to 8, while serious injuries decreased from 1 to 0.

Outcome by Severity (Crash Events)

Minor Injury8minor injury crashes12.3%
↓-42.9%prior 14
Possible Injury4possible injury crashes6.2%
↑33.3%prior 3
No Injury53no injury crashes81.5%
→0.0%prior 53

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'Followed too closely,' decreased by 3 crashes, from 21 in December 2024 to 18 in December 2025. 'Failed to yield right of way' increased by 1 crash, from 10 to 11, while 'No improper driving' decreased by 1 crash, from 9 to 8. 'Exceeded authorized speed limit' decreased by 2 crashes, from 3 to 1.

Officer-Reported Primary Contributing Cause

Followed too closely18 (27.7%)↓-14.3%prior 21
Failed to yield right of way11 (16.9%)↑10.0%prior 10
No improper driving8 (12.3%)↓-11.1%prior 9
Inattention5 (7.7%)→0.0%prior 5
Failure to keep in proper lane or running off road5 (7.7%)↓-28.6%prior 7
Driving too fast for conditions4 (6.2%)
Visibility obstructed2 (3.1%)
Other improper action2 (3.1%)
Glare1 (1.5%)
Distracted1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear/Clear' weather conditions increased from 21 in December 2024 to 33 in December 2025. There was a notable decrease in crashes on 'Wet' road surfaces, falling from 17 to 9 year-over-year. Conversely, crashes on 'Ice' road surfaces increased from 1 in the prior period to 7 in the current period.

Weather

Clear/Clear33 (50.8%)
↑57.1%prior 21
Clear17 (26.2%)
↓-19.0%prior 21
Cloudy/Cloudy2 (3.1%)
Snow/Sleet, hail (freezing rain or drizzle)2 (3.1%)
Cloudy2 (3.1%)
↓-60.0%prior 5
Rain/Rain2 (3.1%)
Snow/Cloudy2 (3.1%)
Rain/Snow1 (1.5%)
Sleet, hail (freezing rain or drizzle)/Cloudy1 (1.5%)
Sleet, hail (freezing rain or drizzle)/Sleet, hail (freezing rain or drizzle)1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight30 (46.2%)
→0.0%prior 30
Dark - lighted roadway25 (38.5%)
↑8.7%prior 23
Dark - roadway not lighted5 (7.7%)
↓-16.7%prior 6
Dusk4 (6.2%)
Dawn1 (1.5%)
↓-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry47 (72.3%)
↓-2.1%prior 48
Wet9 (13.8%)
↓-47.1%prior 17
Ice7 (10.8%)
Snow2 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 142 in December 2024 to 131 in December 2025. Toyota remained the top make involved, though its count decreased from 34 to 25. Honda saw an increase in involvement, from 12 vehicles in December 2024 to 20 in December 2025.

Top Vehicle Makes (131 vehicles)

1
TOYOTA25 (19.1%)
↓-26.5%prior 34
2
HONDA20 (15.3%)
↑66.7%prior 12
3
FORD10 (7.6%)
↓-28.6%prior 14
4
NISSAN9 (6.9%)
↑12.5%prior 8
5
HYUNDAI8 (6.1%)
↑14.3%prior 7
6
SUBARU7 (5.3%)
↑16.7%prior 6
7
AUDI7 (5.3%)
8
TESL5 (3.8%)
9
JEEP5 (3.8%)
10
KIA5 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (135 persons with recorded sex)

Male69 (51.1%)
↓-14.8%prior 81
Female63 (46.7%)
↑3.3%prior 61
X / Unspecified3 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 mph speed zones increased from 8 in December 2024 to 18 in December 2025, marking a rise of 10 crashes. Conversely, crashes in 55 mph speed zones decreased by 7, from 25 to 18. Crashes in 30 mph zones also decreased by 7, from 11 to 4.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · 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: 2025-12-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-12-01 through 2025-12-31 (31 days)
  • Geographic scope: BURLINGTON, MA
  • Total crash records analyzed: 65
  • Total persons involved: 147
  • Total vehicles involved: 131

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: December 2025." Published June 21, 2026. Reporting period: 2025-12-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/burlington/december-2025-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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Burlington, MA Crash Report — December 2025 | ThatCarHitMe.com