Monthly Traffic Safety Analysis

131 CRASHES IN
MEDFORD, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, Medford experienced 131 total crashes, a 25.96% increase compared to the 104 crashes recorded in November 2024. The most notable shift was this overall increase in crash volume. Fatalities remained at zero for both periods.

131

26.0%was 104

Total Crash Events

0

Persons Killed

35

2.9%was 34

Persons Injured

29

38.1%was 21

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. 14 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a rise in crashes year-over-year, with total crashes increasing from 104 in the prior period to 131 in the current period. This represents an increase of 27 crashes, or 25.96%.

29

Hit-and-Run Crashes — November 2025

38.1% vs prior (21)

Hit-and-run crashes increased from 21 in the prior period to 29 in the current period. The hit-and-run rate also saw an upward trend, rising from 20.2% of total crashes to 22.1%.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 6-50.0%

2

Cyclists Injured

Prior: 0%

30

Motorists Injured

Prior: 2711.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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 Friday (21 crashes) in the prior period to Tuesday (28 crashes) in the current period. The peak hour also changed, moving from 11 AM (11 crashes) in the prior period to 6 PM (10 crashes) in the current period. Notably, Sunday crashes more than doubled, increasing from 8 to 22.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero for both periods. Serious injury crashes (severity A) decreased from 4 in the prior period to 1 in the current period, while minor injury crashes (severity B) increased from 13 to 18. The proportion of crashes resulting in no injury increased from 61.5% to 70.2%.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes0.8%
-75.0%prior 4
Minor Injury18minor injury crashes13.7%
38.5%prior 13
Possible Injury6possible injury crashes4.6%
-33.3%prior 9
No Injury92no injury crashes70.2%
43.8%prior 64

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Followed too closely' saw a 100% increase in count, rising from 7 crashes in the prior period to 14 crashes in the current period. Conversely, 'Failed to yield right of way' decreased from 11 crashes to 4 crashes. 'No improper driving' remained the most frequent factor, increasing slightly from 33 to 35 crashes.

Officer-Reported Primary Contributing Cause

No improper driving35 (26.7%)6.1%prior 33
Followed too closely14 (10.7%)100.0%prior 7
Failure to keep in proper lane or running off road9 (6.9%)
Inattention8 (6.1%)60.0%prior 5
Disregarded traffic signs, signals, road markings4 (3.1%)
Failed to yield right of way4 (3.1%)-63.6%prior 11
Other improper action3 (2.3%)
Exceeded authorized speed limit3 (2.3%)
Fatigued/asleep3 (2.3%)
Distracted2 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' or 'Clear/Clear' weather conditions collectively increased from 74 to 97. Crashes during 'Daylight' conditions increased from 59 to 70, and those in 'Dark - lighted roadway' increased from 33 to 44. The number of crashes on 'Wet' road surfaces slightly decreased from 16 to 15.

Weather

Clear72 (58.1%)
16.1%prior 62
Clear/Clear25 (20.2%)
108.3%prior 12
Cloudy7 (5.6%)
-12.5%prior 8
Rain5 (4.0%)
-54.5%prior 11
Rain/Rain3 (2.4%)
Cloudy/Cloudy3 (2.4%)
Cloudy/Rain3 (2.4%)
Rain/Cloudy3 (2.4%)
Cloudy/Unknown2 (1.6%)
Unknown/Unknown1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash

Lighting

Daylight70 (56.5%)
18.6%prior 59
Dark - lighted roadway44 (35.5%)
33.3%prior 33
Dusk4 (3.2%)
Dark - unknown roadway lighting2 (1.6%)
Dark - roadway not lighted2 (1.6%)
Dawn1 (0.8%)
Other1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field

Road Surface

Dry109 (87.9%)
28.2%prior 85
Wet15 (12.1%)
-6.3%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 196 to 261. Honda became the top vehicle make involved, increasing from 31 to 43, while Toyota, the top make in the prior period, decreased from 42 to 38. The 21-25 age group saw a significant increase in persons involved, from 17 to 35, and the 26-34 age group increased from 33 to 52 persons.

Top Vehicle Makes (261 vehicles)

1
HONDA43 (16.5%)
38.7%prior 31
2
TOYOTA38 (14.6%)
-9.5%prior 42
3
FORD29 (11.1%)
52.6%prior 19
4
SUBARU17 (6.5%)
88.9%prior 9
5
NISSAN10 (3.8%)
42.9%prior 7
6
VOLKSWAGEN9 (3.4%)
7
CHEVROLET9 (3.4%)
-43.8%prior 16
8
MAZDA9 (3.4%)
9
KIA7 (2.7%)
16.7%prior 6
10
LEXUS7 (2.7%)
40.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records

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

Sex Distribution (231 persons with recorded sex)

Male138 (59.7%)
26.6%prior 109
Female93 (40.3%)
22.4%prior 76

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone increased from 80 to 85, and those in the 10 mph zone increased from 2 to 8. A notable increase occurred in the 55 mph zone, with crashes rising from 3 to 16. Fatal rates by speed zone remained at zero for both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-11-01 through 2025-11-30 (30 days)
  • Geographic scope: MEDFORD, MA
  • Total crash records analyzed: 131
  • Total persons involved: 301
  • Total vehicles involved: 261

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). "MEDFORD, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/medford/november-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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Medford, MA Crash Report — November 2025 | ThatCarHitMe.com