Monthly Traffic Safety Analysis

37 CRASHES IN
DEDHAM, MA
FEBRUARY 2025

All metrics benchmarked againstFebruary 2024

Total crashes in DEDHAM, MA increased from 31 in February 2024 to 37 in February 2025, representing a 19.35% rise. The most notable change was a 200% increase in speeding-related crashes, which rose from 1 to 3 incidents year-over-year. Additionally, DUI crashes increased from 0 to 1 during this period.

37

19.4%was 31

Total Crash Events

0

Persons Killed

12

50.0%was 8

Persons Injured

0

-100.0%was 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 · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a rise in crash activity in DEDHAM, MA, with total crashes increasing by 19.35% from 31 to 37. Concurrently, the number of injured persons saw a 50% increase, rising from 8 to 12 year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

12

Motorists Injured

Prior: 4200.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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 with 6 crashes in February 2024 to Tuesday with 8 crashes in February 2025. The peak hour also changed, moving from 2 PM with 4 crashes in the prior period to 7 AM with 6 crashes in the current period, indicating a shift towards morning commute times.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While both periods reported no fatal crashes, the distribution of injuries shifted. Serious injuries (Severity A) decreased from 2 crashes in February 2024 to 0 in February 2025. However, possible injury crashes (Severity C) increased substantially from 2 incidents (6.5% of crashes) to 6 incidents (16.2% of crashes) year-over-year.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes8.1%
0.0%prior 3
Possible Injury6possible injury crashes16.2%
200.0%prior 2
No Injury28no injury crashes75.7%
21.7%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record

Top Contributing Factors

The count of crashes where 'Failed to yield right of way' was a contributing factor increased from 1 to 7, representing a significant rise of 6 crashes. 'Driving too fast for conditions' also saw an increase, going from 1 crash in the prior period to 3 crashes in the current period. Conversely, 'Inattention' as a contributing factor decreased from 3 crashes to 1 crash.

Officer-Reported Primary Contributing Cause

No improper driving11 (29.7%)0.0%prior 11
Failed to yield right of way7 (18.9%)
Failure to keep in proper lane or running off road3 (8.1%)
Followed too closely3 (8.1%)
Other improper action3 (8.1%)
Driving too fast for conditions3 (8.1%)
Glare1 (2.7%)
Fatigued/asleep1 (2.7%)
Distracted1 (2.7%)
Inattention1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift in road conditions, with crashes on dry roads decreasing from 28 to 24, while crashes on snow-covered roads increased from 0 to 8. Similarly, crashes during daylight conditions increased from 20 to 24, and crashes during dark-lighted roadway conditions rose from 8 to 11. Crashes under clear weather conditions decreased from 25 to 19.

Weather

Clear/Clear19 (51.4%)
-24.0%prior 25
Clear4 (10.8%)
Snow/Snow3 (8.1%)
Clear/Cloudy3 (8.1%)
Cloudy/Cloudy2 (5.4%)
Snow/Cloudy2 (5.4%)
Cloudy/Rain1 (2.7%)
Snow1 (2.7%)
Snow/Sleet, hail (freezing rain or drizzle)1 (2.7%)
Cloudy1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash

Lighting

Daylight24 (64.9%)
20.0%prior 20
Dark - lighted roadway11 (29.7%)
37.5%prior 8
Dark - roadway not lighted1 (2.7%)
Dawn1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field

Road Surface

Dry24 (64.9%)
-14.3%prior 28
Snow8 (21.6%)
Wet5 (13.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes increased from 64 to 76 year-over-year. Significant shifts were observed in age distribution, with persons aged 16-20 increasing from 3 to 11, and those aged 35-44 increasing from 10 to 18. Conversely, persons aged 65 and over involved in crashes decreased from 14 to 8.

Top Vehicle Makes (64 vehicles)

1
TOYOTA15 (23.4%)
7.1%prior 14
2
HONDA9 (14.1%)
12.5%prior 8
3
KIA5 (7.8%)
4
JEEP5 (7.8%)
5
CHEVROLET4 (6.3%)
6
HYUNDAI3 (4.7%)
7
LEXUS3 (4.7%)
8
NISSAN2 (3.1%)
9
VOLVO2 (3.1%)
10
MERCEDES-BENZ2 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records

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

Sex Distribution (72 persons with recorded sex)

Female42 (58.3%)
35.5%prior 31
Male30 (41.7%)
0.0%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 MPH speed zones doubled from 3 to 6, and crashes in 35 MPH zones tripled from 1 to 3. Crashes in 55 MPH speed zones also increased from 4 to 6, while 45 MPH zones saw a decrease from 1 to 0 crashes. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-02-01 through 2025-02-28 (28 days)
  • Geographic scope: DEDHAM, MA
  • Total crash records analyzed: 37
  • Total persons involved: 76
  • Total vehicles involved: 64

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). "DEDHAM, MA Crash Intelligence Report: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/dedham/february-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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Dedham, MA Crash Report — February 2025 | ThatCarHitMe.com