ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BRAINTREE, MA · 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/braintree/2024-annual-report
Yearly Traffic Safety Analysis
920 CRASHES IN
BRAINTREE, MA
2024
In 2024, Braintree recorded 920 total vehicle crashes, an increase from the 819 crashes reported in 2023, representing a 12.3% year-over-year rise. The most notable shift was the increase in total fatalities from 1 in the prior year to 3 in the current year. The total number of people injured also rose from 356 to 375.
920
▲ 12.3%was 819
Total Crash Events
3
▲ 200.0%was 1
Persons Killed
375
▲ 5.3%was 356
Persons Injured
54
▼ -6.9%was 58
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 22 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Braintree show an increase year-over-year. Total crashes rose by 12.3%, from 819 in 2023 to 920 in 2024. This period also saw a rise in total injuries from 356 to 375 and an increase in fatalities from 1 to 3.
54
Hit-and-Run Crashes — 2024
▼ -6.9% vs prior (58)
The number of hit-and-run incidents in Braintree decreased year-over-year. The total count of hit-and-run crashes fell from 58 in 2023 to 54 in 2024. Correspondingly, the hit-and-run rate, as a percentage of total crashes, also trended downward, declining from 7.1% to 5.9%.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
6
Pedestrians Injured
1
Cyclists Injured
366
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed a shift in the peak day of the week between the two periods. In 2024, Tuesday was the day with the most crashes (156), a change from 2023 when Friday saw the highest volume (138). The peak hour for collisions remained consistent, occurring at 5 PM in both years, with crash counts in that hour increasing from 90 to 97.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes shifted year-over-year, with a notable increase in fatal incidents. The number of fatal crashes rose from 1 in 2023 to 3 in 2024, and the corresponding fatal crash rate increased from 0.12% to 0.33%. While fatal crashes increased, the count of serious injury crashes decreased from 15 to 12. The proportions of minor, possible, and no-injury crashes remained relatively stable as a share of all crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes remained consistent, though their counts shifted. 'Followed too closely' remained the second-leading factor, with its count increasing from 158 in 2023 to 188 in 2024, a 19.0% rise. Conversely, crashes attributed to 'Failed to yield right of way' decreased in count from 96 to 83. Notably, 'Failure to keep in proper lane or running off road' saw its crash count increase from 43 to 68.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Analysis of crash conditions shows a higher proportion of incidents occurred during daylight hours in 2024 (66.0%) compared to 2023 (60.3%). While the majority of crashes in both years happened on dry roads under clear skies, the count of crashes on wet roads decreased from 170 to 154. Similarly, crashes reported during rainy weather also saw a decrease from 95 incidents in 2023 to 68 in 2024.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes were Toyota, Honda, and Ford in both 2023 and 2024, with each make seeing an increase in crash involvement counts. Toyota involvement rose from 300 to 339 vehicles. Analysis of persons involved shows a notable increase in the 35-44 age group (from 355 to 459 people) and the 55-64 age group (from 228 to 353 people) compared to the prior year.
Top Vehicle Makes (1,846 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
123 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,284 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones saw some shifts. The number of crashes in 55 MPH zones increased from 238 to 270 year-over-year, with one fatal crash recorded in this zone in both periods. Crashes in 30 MPH zones decreased slightly from 285 to 276, but this zone recorded one fatality in 2024 after having none in 2023. A new fatal crash was also recorded in a 40 MPH zone in 2024.
Fatal crashes by zone: 30 mph: 1 of 276 (0.362%) · 40 mph: 1 of 46 (2.174%) · 55 mph: 1 of 270 (0.37%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: BRAINTREE, MA
- Total crash records analyzed: 920
- Total persons involved: 2,446
- Total vehicles involved: 1,846
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/braintree/2024-annual-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved