Monthly Traffic Safety Analysis

369 CRASHES IN
BOSTON, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, BOSTON, MA recorded 369 total crashes, a decrease of 20.47% compared to 464 crashes in November 2024. A notable shift was the reduction in total fatalities from 2 in the prior year to 0 in the current period.

369

-20.5%was 464

Total Crash Events

0

-100.0%was 2

Persons Killed

138

-28.1%was 192

Persons Injured

69

6.2%was 65

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. 11 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

Overall crash incidents in BOSTON, MA showed a downward trend year-over-year, with total crashes decreasing by 95, from 464 in November 2024 to 369 in November 2025. This represents a 20.47% reduction in crashes.

69

Hit-and-Run Crashes — November 2025

6.2% vs prior (65)

Hit-and-run crashes increased from 65 in November 2024 to 69 in November 2025. The hit-and-run rate also saw an increase, rising from 14% in the prior period to 18.7% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

0

Other Killed

Prior: 1-100.0%

12

Pedestrians Injured

Prior: 17-29.4%

2

Cyclists Injured

Prior: 9-77.8%

122

Motorists Injured

Prior: 163-25.2%

2

Other Injured

Prior: 3-33.3%

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 remained Saturday in both periods, with 79 crashes in November 2025 compared to 91 crashes in November 2024. The peak crash hour shifted from 12p (34 crashes) in the prior year to 10a (29 crashes) in the current period.

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

Total fatalities decreased from 2 in November 2024 to 0 in November 2025, resulting in a fatal crash rate reduction from 0.43% to 0%. Serious injuries (A) decreased from 20 to 7, while minor injuries (B) decreased from 88 to 72, and possible injuries (C) decreased from 37 to 26. The proportion of crashes resulting in no injury increased from 62.1% to 68.6%.

Outcome by Severity (Crash Events)

Serious Injury7serious injury crashes1.9%
-65.0%prior 20
Minor Injury72minor injury crashes19.5%
-18.2%prior 88
Possible Injury26possible injury crashes7%
-29.7%prior 37
No Injury253no injury crashes68.6%
-12.2%prior 288

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 leading contributing factor, 'No improper driving,' decreased from 76 crashes in November 2024 to 64 crashes in November 2025. 'Followed too closely' increased slightly from 53 to 56 crashes, while 'Failed to yield right of way' also saw a minor increase from 35 to 37 crashes. Notably, 'Exceeded authorized speed limit' crashes increased from 9 to 15, and 'Inattention' crashes rose from 13 to 19.

Officer-Reported Primary Contributing Cause

No improper driving64 (17.3%)-15.8%prior 76
Followed too closely56 (15.2%)5.7%prior 53
Failed to yield right of way37 (10%)5.7%prior 35
Disregarded traffic signs, signals, road markings23 (6.2%)0.0%prior 23
Failure to keep in proper lane or running off road22 (6%)-18.5%prior 27
Inattention19 (5.1%)46.2%prior 13
Driving too fast for conditions18 (4.9%)-10.0%prior 20
Exceeded authorized speed limit15 (4.1%)66.7%prior 9
Made an improper turn8 (2.2%)-46.7%prior 15
Other improper action7 (1.9%)-36.4%prior 11

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 weather conditions decreased from 334 in November 2024 to 240 in November 2025, while crashes in rainy conditions remained stable at 58 in the prior period and 57 in the current. The proportion of crashes on dry road surfaces remained consistent at approximately 69.6% year-over-year, but the share of crashes on wet surfaces increased from 14.7% to 19.2%. In the current period, crashes during daylight and dark-lighted roadway conditions were equal at 161 each, a shift from the prior period where daylight crashes (197) were more frequent than dark-lighted roadway crashes (190).

Weather

Clear/Clear123 (35.4%)
10.8%prior 111
Clear117 (33.7%)
-47.5%prior 223
Rain35 (10.1%)
-22.2%prior 45
Rain/Rain22 (6.3%)
69.2%prior 13
Cloudy20 (5.8%)
33.3%prior 15
Cloudy/Cloudy12 (3.5%)
Clear/Cloudy6 (1.7%)
Rain/Cloudy6 (1.7%)
-33.3%prior 9
Unknown/Unknown2 (0.6%)
Cloudy/Clear2 (0.6%)

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

Lighting

Dark - lighted roadway161 (46.0%)
-15.3%prior 190
Daylight161 (46.0%)
-18.3%prior 197
Dawn10 (2.9%)
-9.1%prior 11
Dusk9 (2.6%)
-35.7%prior 14
Dark - roadway not lighted6 (1.7%)
-25.0%prior 8
Dark - unknown roadway lighting3 (0.9%)

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

Road Surface

Dry257 (77.9%)
-20.4%prior 323
Wet71 (21.5%)
4.4%prior 68
Water (standing, moving)2 (0.6%)

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 decreased from 916 in November 2024 to 749 in November 2025. Toyota, Honda, and Ford remained the top three most common vehicle makes involved in crashes, though their counts decreased by 39, 19, and 38 respectively. Subaru saw a slight increase in involvement, rising from 33 vehicles to 34, and moved up in ranking from eighth to fifth.

Top Vehicle Makes (749 vehicles)

1
TOYOTA121 (16.2%)
-24.4%prior 160
2
HONDA118 (15.8%)
-13.9%prior 137
3
FORD56 (7.5%)
-40.4%prior 94
4
CHEVROLET40 (5.3%)
-16.7%prior 48
5
SUBARU34 (4.5%)
3.0%prior 33
6
NISSAN30 (4%)
-44.4%prior 54
7
JEEP24 (3.2%)
-31.4%prior 35
8
BMW22 (2.9%)
46.7%prior 15
9
VOLKSWAGEN19 (2.5%)
171.4%prior 7
10
HYUNDAI18 (2.4%)
-55.0%prior 40

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

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

Sex Distribution (730 persons with recorded sex)

Male466 (63.8%)
-19.4%prior 578
Female264 (36.2%)
-17.0%prior 318

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 limit zone decreased from 149 in November 2024 to 111 in November 2025, with fatalities in this zone reducing from 2 to 0. Conversely, crashes in the 45 mph zone increased from 25 to 35, and crashes in the 55 mph zone increased from 34 to 48. This indicates a shift in crash distribution towards higher speed zones.

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: BOSTON, MA
  • Total crash records analyzed: 369
  • Total persons involved: 904
  • Total vehicles involved: 749

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). "BOSTON, 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/boston/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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Boston, MA Crash Report — November 2025 | ThatCarHitMe.com