Monthly Traffic Safety Analysis

59 CRASHES IN
BRAINTREE, MA
JULY 2024

All metrics benchmarked againstJuly 2023

Total crashes in Braintree, MA decreased by 10.6% from 66 in July 2023 to 59 in July 2024. Despite this reduction in crash events, the total number of injuries nearly doubled, increasing by 93.8% from 16 to 31 persons over the same period.

59

▼ -10.6%was 66

Total Crash Events

0

Persons Killed

31

▲ 93.8%was 16

Persons Injured

2

▼ -71.4%was 7

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 · 2024-07-01 to 2024-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes in Braintree, MA saw a decrease of 10.6%, falling from 66 crashes in July 2023 to 59 crashes in July 2024. However, the total number of injured persons experienced a substantial increase of 93.8%, rising from 16 to 31 year-over-year.

2

Hit-and-Run Crashes — July 2024

▼ -71.4% vs prior (7)

Hit-and-run crashes decreased significantly from 7 in July 2023 to 2 in July 2024, a 71.4% reduction in count. Consequently, the hit-and-run rate fell from 10.6% to 3.4% year-over-year, indicating a positive trend.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 0→%

30

Motorists Injured

Prior: 16↑87.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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 Monday and Wednesday (12 crashes each) in July 2023 to Monday (15 crashes) in July 2024. The peak hour also changed significantly, moving from 5 p.m. with 11 crashes in July 2023 to 11 a.m. with 6 crashes in July 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities in either July 2023 or July 2024. Crashes involving serious injuries increased from 1 (1.5% share) to 3 (5.1% share), while crashes with possible injuries rose from 3 (4.5% share) to 9 (15.3% share). Crashes with minor injuries slightly decreased in count from 12 to 11.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes5.1%
↑200.0%prior 1
Minor Injury11minor injury crashes18.6%
↓-8.3%prior 12
Possible Injury9possible injury crashes15.3%
↑200.0%prior 3
No Injury35no injury crashes59.3%
↓-23.9%prior 46

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'No improper driving' decreased significantly by 10 crashes, from 19 in July 2023 to 9 in July 2024. Conversely, 'Disregarded traffic signs, signals, road markings' increased from 1 crash to 4 crashes, representing a 300% increase in count. 'Failed to yield right of way' also saw an increase, rising from 8 crashes to 10 crashes, a 25% change in count.

Officer-Reported Primary Contributing Cause

Followed too closely10 (16.9%)→0.0%prior 10
Failed to yield right of way10 (16.9%)↑25.0%prior 8
No improper driving9 (15.3%)↓-52.6%prior 19
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway5 (8.5%)
Failure to keep in proper lane or running off road5 (8.5%)
Disregarded traffic signs, signals, road markings4 (6.8%)
Inattention3 (5.1%)↓-70.0%prior 10
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (5.1%)
Exceeded authorized speed limit1 (1.7%)
Visibility obstructed1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 45 to 51, while those in 'Cloudy' conditions decreased from 9 to 2. The number of crashes on 'Wet' road surfaces decreased from 7 to 3. The proportion of crashes occurring during 'Dawn' hours increased from 1 to 5.

Weather

Clear51 (86.4%)
↑13.3%prior 45
Clear/Clear4 (6.8%)
↓-20.0%prior 5
Cloudy2 (3.4%)
↓-77.8%prior 9
Cloudy/Rain1 (1.7%)
Rain/Cloudy1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Weather condition at time of crash

Lighting

Daylight49 (83.1%)
↓-5.8%prior 52
Dawn5 (8.5%)
Dark - lighted roadway4 (6.8%)
↓-50.0%prior 8
Dusk1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Lighting condition field

Road Surface

Dry56 (94.9%)
↓-1.8%prior 57
Wet3 (5.1%)
↓-57.1%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Road surface condition field

Vehicles & Demographics

Toyota remained the most common vehicle make involved in crashes, though its count decreased from 23 to 21. Ford increased its involvement from 10 to 14 crashes, moving into the second position, while Honda's involvement decreased from 12 to 10. In terms of persons involved, the 45-54 age group saw a notable increase from 13 to 28 individuals, whereas the 21-25 and 26-34 age groups experienced decreases in involvement.

Top Vehicle Makes (124 vehicles)

1
TOYOTA21 (16.9%)
↓-8.7%prior 23
2
FORD14 (11.3%)
↑40.0%prior 10
3
HONDA10 (8.1%)
↓-16.7%prior 12
4
NISSAN9 (7.3%)
↑12.5%prior 8
5
CHEVROLET8 (6.5%)
↑33.3%prior 6
6
JEEP7 (5.6%)
7
HYUNDAI7 (5.6%)
8
SUBARU6 (4.8%)
↑20.0%prior 5
9
ACURA5 (4%)
10
BMW4 (3.2%)
↓-20.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Vehicle unit records

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

Sex Distribution (152 persons with recorded sex)

Male92 (60.5%)
↑22.7%prior 75
Female60 (39.5%)
↓-4.8%prior 63

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 23 to 19, and in 35 mph zones from 9 to 5. Conversely, crashes in 40 mph zones increased from 1 to 6. No fatalities were recorded in any speed limit zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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: 2024-07-01 through 2024-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-07-01 through 2024-07-31 (31 days)
  • Geographic scope: BRAINTREE, MA
  • Total crash records analyzed: 59
  • Total persons involved: 160
  • Total vehicles involved: 124

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: July 2024." Published June 21, 2026. Reporting period: 2024-07-01 to 2024-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/braintree/july-2024-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 — July 2024 | ThatCarHitMe.com