Monthly Traffic Safety Analysis

49 CRASHES IN
TEWKSBURY, MA
JUNE 2025

All metrics benchmarked againstJune 2024

Total crashes in TEWKSBURY, MA decreased by 5.77% from 52 incidents in June 2024 to 49 incidents in June 2025. Despite this decrease in overall crashes, total injuries significantly increased from 6 to 16, representing a 166.7% rise year-over-year. Fatalities remained at zero in both periods.

49

-5.8%was 52

Total Crash Events

0

Persons Killed

16

166.7%was 6

Persons Injured

3

-70.0%was 10

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 · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in TEWKSBURY experienced a slight downward trend, decreasing by 5.77% from 52 total crashes in June 2024 to 49 in June 2025. While total crashes saw a minor reduction, the number of injured persons substantially increased by 166.7%, rising from 6 to 16.

3

Hit-and-Run Crashes — June 2025

-70.0% vs prior (10)

Hit-and-run crashes decreased substantially from 10 incidents in June 2024 to 3 incidents in June 2025, representing a 70% reduction. The hit-and-run rate also saw a significant decrease, falling from 19.2% of all crashes in June 2024 to 6.1% in June 2025.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

16

Motorists Injured

Prior: 5220.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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 Saturday in June 2024 (11 crashes) to Friday in June 2025 (11 crashes). The peak crash hour also shifted, with 7 crashes occurring at 3 p.m. in June 2024, while 7 crashes occurred at 5 p.m. in June 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The total number of injuries rose significantly from 6 in June 2024 to 16 in June 2025. This increase included the emergence of serious injuries, with 1 serious injury reported in June 2025 compared to 0 in the prior period. Crashes resulting in minor injuries increased from 6 to 8, and possible injuries increased from 0 to 2.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2%
Minor Injury8minor injury crashes16.3%
33.3%prior 6
Possible Injury2possible injury crashes4.1%
No Injury37no injury crashes75.5%
-19.6%prior 46

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

Crashes where 'No improper driving' was cited increased by 1, from 11 in June 2024 to 12 in June 2025. 'Inattention' as a contributing factor increased from 8 crashes to 10 crashes, while 'Followed too closely' decreased from 7 crashes to 6 crashes. 'Failed to yield right of way' remained consistent with 6 crashes in both periods.

Officer-Reported Primary Contributing Cause

No improper driving12 (24.5%)9.1%prior 11
Inattention10 (20.4%)25.0%prior 8
Followed too closely6 (12.2%)-14.3%prior 7
Failed to yield right of way6 (12.2%)0.0%prior 6
Distracted3 (6.1%)
Failure to keep in proper lane or running off road3 (6.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (4.1%)
Illness1 (2%)
Over-correcting/over-steering1 (2%)
Wrong side or wrong way1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 43 in June 2024 to 39 in June 2025. Crashes in 'Daylight' conditions also decreased from 47 to 43. Conversely, crashes in 'Dark - lighted roadway' conditions increased from 1 in June 2024 to 5 in June 2025.

Weather

Clear39 (79.6%)
-9.3%prior 43
Rain/Cloudy2 (4.1%)
Clear/Unknown2 (4.1%)
Cloudy2 (4.1%)
-66.7%prior 6
Clear/Clear1 (2.0%)
Cloudy/Rain1 (2.0%)
Clear/Cloudy1 (2.0%)
Rain1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Lighting

Daylight43 (87.8%)
-8.5%prior 47
Dark - lighted roadway5 (10.2%)
Dark - roadway not lighted1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field

Road Surface

Dry45 (91.8%)
-4.3%prior 47
Wet4 (8.2%)
-20.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes slightly increased from 96 in June 2024 to 98 in June 2025. Crashes involving Ford vehicles increased from 11 to 19, while Honda-involved crashes decreased from 16 to 15. The age group 0-15 saw a decrease in persons involved from 14 to 5, while the 21-25 age group increased from 10 to 17 persons. The number of females involved in crashes rose from 27 to 41, while males remained at 64.

Top Vehicle Makes (98 vehicles)

1
FORD19 (19.4%)
72.7%prior 11
2
HONDA15 (15.3%)
-6.3%prior 16
3
TOYOTA14 (14.3%)
16.7%prior 12
4
CHEVROLET7 (7.1%)
16.7%prior 6
5
NISSAN6 (6.1%)
6
JEEP5 (5.1%)
7
LEXUS4 (4.1%)
8
HYUNDAI3 (3.1%)
9
DODGE2 (2%)
10
MK2 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

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

Sex Distribution (105 persons with recorded sex)

Male64 (61.0%)
0.0%prior 64
Female41 (39.0%)
51.9%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 mph zones increased from 16 in June 2024 to 20 in June 2025, while crashes in 65 mph zones decreased from 11 to 5. Crashes in 40 mph zones also decreased from 5 to 2. Crashes in 30 mph zones remained stable at 13 in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: TEWKSBURY, MA
  • Total crash records analyzed: 49
  • Total persons involved: 117
  • Total vehicles involved: 98

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). "TEWKSBURY, MA Crash Intelligence Report: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/tewksbury/june-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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Tewksbury, MA Crash Report — June 2025 | ThatCarHitMe.com