Monthly Traffic Safety Analysis

45 CRASHES IN
BRAINTREE, MA
MARCH 2025

All metrics benchmarked againstMarch 2024

BRAINTREE experienced a significant decrease in overall crash activity in March 2025 compared to March 2024. Total crashes fell from 74 to 45, representing a 39.2% reduction. Additionally, total injuries decreased by 64.5%, from 31 to 11, making the reduction in injuries the most notable shift year-over-year.

45

-39.2%was 74

Total Crash Events

0

Persons Killed

11

-64.5%was 31

Persons Injured

5

150.0%was 2

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a substantial decrease in crash incidents year-over-year. Total crashes decreased from 74 in March 2024 to 45 in March 2025, a reduction of 39.2%. Concurrently, total injuries dropped from 31 to 11, marking a 64.5% decrease.

5

Hit-and-Run Crashes — March 2025

150.0% vs prior (2)

Hit-and-run crashes increased year-over-year, rising from 2 incidents in March 2024 to 5 incidents in March 2025. This change resulted in the hit-and-run rate more than quadrupling, increasing from 2.7% of all crashes to 11.1% of all crashes.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

10

Motorists Injured

Prior: 31-67.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted between the two periods. In March 2024, the peak day for crashes was Thursday with 17 incidents, while in March 2025, Monday became the peak day with 13 crashes. The peak hour also changed, moving from 3 PM with 11 crashes in March 2024 to 5 PM with 6 crashes in March 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes reported in either March 2024 or March 2025. The total number of injuries decreased from 31 to 11. The proportion of crashes resulting in a 'Possible Injury' decreased from 13.5% to 6.7%, while the share of crashes with 'No Injury' increased from 70.3% to 73.3%.

Outcome by Severity (Crash Events)

Minor Injury7minor injury crashes15.6%
-41.7%prior 12
Possible Injury3possible injury crashes6.7%
-70.0%prior 10
No Injury33no injury crashes73.3%
-36.5%prior 52

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw notable changes year-over-year. Crashes attributed to 'Followed too closely' decreased by 15 incidents, from 20 to 5, representing a 75% reduction in count and falling from the most frequent factor to the second most frequent. Conversely, 'No improper driving' crashes increased by 2 incidents, from 12 to 14, a 16.7% change in count, becoming the most frequent factor in March 2025. 'Inattention' crashes decreased by 3 incidents, from 7 to 4, a 42.9% change in count.

Officer-Reported Primary Contributing Cause

No improper driving14 (31.1%)16.7%prior 12
Followed too closely5 (11.1%)-75.0%prior 20
Inattention4 (8.9%)-42.9%prior 7
Failed to yield right of way3 (6.7%)-62.5%prior 8
Driving too fast for conditions2 (4.4%)
Other improper action2 (4.4%)
Fatigued/asleep1 (2.2%)
Over-correcting/over-steering1 (2.2%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on 'Dry' road surfaces decreased from 45 in March 2024 to 35 in March 2025. Crashes on 'Wet' road surfaces also saw a significant reduction, falling from 29 to 9. The number of crashes occurring during 'Daylight' conditions decreased from 45 to 29, while those in 'Dark - lighted roadway' conditions decreased from 14 to 12.

Weather

Clear26 (59.1%)
-27.8%prior 36
Clear/Clear5 (11.4%)
Cloudy4 (9.1%)
-63.6%prior 11
Rain/Cloudy4 (9.1%)
Rain/Rain2 (4.5%)
Cloudy/Cloudy2 (4.5%)
Rain1 (2.3%)
-93.8%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash

Lighting

Daylight29 (64.4%)
-35.6%prior 45
Dark - lighted roadway12 (26.7%)
-14.3%prior 14
Dark - roadway not lighted3 (6.7%)
-62.5%prior 8
Dawn1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field

Road Surface

Dry35 (79.5%)
-22.2%prior 45
Wet9 (20.5%)
-69.0%prior 29

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 145 in March 2024 to 80 in March 2025. The top three vehicle makes involved in crashes remained Honda, Toyota, and Ford, though their individual counts decreased in line with the overall reduction in crashes. For persons involved, the 55-64 age group continued to represent the highest count in both periods, decreasing from 47 to 19, while the 26-34 age group remained the second highest, decreasing from 39 to 18.

Top Vehicle Makes (80 vehicles)

1
HONDA16 (20%)
-15.8%prior 19
2
TOYOTA12 (15%)
-33.3%prior 18
3
FORD10 (12.5%)
-33.3%prior 15
4
NISSAN5 (6.3%)
-54.5%prior 11
5
JEEP5 (6.3%)
0.0%prior 5
6
CHEVROLET5 (6.3%)
-54.5%prior 11
7
KIA3 (3.8%)
8
SUBARU3 (3.8%)
-40.0%prior 5
9
MERCEDES-BENZ2 (2.5%)
10
RAM1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records

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

Sex Distribution (86 persons with recorded sex)

Male55 (64.0%)
-55.6%prior 124
Female31 (36.0%)
-47.5%prior 59

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 55 mph speed zones saw a substantial decrease, falling from 30 incidents in March 2024 to 7 in March 2025. Crashes in 30 mph zones also decreased from 20 to 16. The number of crashes in 35 mph zones remained consistent at 7 incidents in both periods, and no fatal crashes were recorded in any speed zone during either month.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-03-01 through 2025-03-31 (31 days)
  • Geographic scope: BRAINTREE, MA
  • Total crash records analyzed: 45
  • Total persons involved: 98
  • Total vehicles involved: 80

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). "BRAINTREE, MA Crash Intelligence Report: March 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/braintree/march-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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Braintree, MA Crash Report — March 2025 | ThatCarHitMe.com