ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BROCKTON, MA · NOVEMBER 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/brockton/november-2024-report
Monthly Traffic Safety Analysis
231 CRASHES IN
BROCKTON, MA
NOVEMBER 2024
In November 2024, Brockton experienced 231 total crashes, a slight increase from the 230 crashes reported in November 2023, representing a 0.43% rise. A notable shift is the absence of fatalities in November 2024, compared to one fatality in the prior year. Additionally, hit-and-run crashes saw a substantial increase, rising from 5 incidents to 14.
231
▲ 0.4%was 230
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
115
▼ -5.7%was 122
Persons Injured
14
▲ 180.0%was 5
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. 31 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in Brockton remained relatively stable year-over-year, with a minor 0.43% increase in total crashes from 230 in November 2023 to 231 in November 2024. However, total fatalities decreased from 1 to 0, and total injuries saw a 5.74% reduction, falling from 122 to 115.
14
Hit-and-Run Crashes — November 2024
▲ 180.0% vs prior (5)
Hit-and-run crashes saw a substantial increase, rising from 5 incidents in November 2023 to 14 incidents in November 2024. This represents a significant increase in the hit-and-run rate, from 2.2% of total crashes in the prior year to 6.1% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
8
Pedestrians Injured
1
Cyclists Injured
105
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Monday in November 2023 (41 crashes) to Friday in November 2024 (42 crashes). The peak hour for crashes remained consistently at 5 PM in both periods, with 23 crashes in November 2023 and 24 crashes in November 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes decreased from 1 in November 2023 to 0 in November 2024. Serious injury crashes (severity A) slightly decreased from 8 (3.5% share) to 7 (3% share), while minor injury crashes (severity B) increased from 37 (16.1% share) to 43 (18.6% share). Possible injury crashes (severity C) decreased from 36 (15.7% share) to 27 (11.7% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'Failed to yield right of way' increased by 10 incidents, rising from 40 in November 2023 to 50 in November 2024. Conversely, 'Failure to keep in proper lane or running off road' incidents decreased significantly by 9 crashes, from 20 to 11, representing a 45% reduction. 'Followed too closely' also saw a decrease of 6 crashes, from 19 to 13.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in rainy conditions increased by 12 incidents, from 14 in November 2023 to 26 in November 2024. Concurrently, crashes on wet road surfaces also rose by 13 incidents, from 28 to 41. Crashes in daylight conditions increased by 16, from 96 to 112, while those in dark-lighted roadway conditions slightly decreased from 96 to 91.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes remained stable, increasing slightly from 445 to 448. Toyota became the most frequently involved vehicle make in November 2024 with 82 incidents, while Honda, which was tied with Toyota at 83 incidents in the prior year, saw a decrease to 70 incidents. The 35-44 age group continued to represent the largest demographic in crashes, increasing from 111 to 114 persons involved.
Top Vehicle Makes (448 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records
56 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (554 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events
Speed Limit Zones
The majority of crashes in both periods occurred in 30 mph zones, increasing from 185 crashes in November 2023 to 193 crashes in November 2024. Notably, the single fatal crash in November 2023 occurred in a 30 mph zone, while no fatalities were recorded in any speed zone in November 2024. Crashes in 65 mph zones decreased from 17 to 11.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-11-01 through 2024-11-30 (30 days)
- Geographic scope: BROCKTON, MA
- Total crash records analyzed: 231
- Total persons involved: 612
- Total vehicles involved: 448
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). "BROCKTON, MA Crash Intelligence Report: November 2024." Published June 21, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brockton/november-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-11-01 – 2024-11-30
Generated: June 21, 2026 · All rights reserved