ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BROCKTON, MA · NOVEMBER 2023
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-2023-report
Monthly Traffic Safety Analysis
230 CRASHES IN
BROCKTON, MA
NOVEMBER 2023
In November 2023, Brockton experienced 230 total crashes, a 5.5% increase compared to the 218 crashes reported in November 2022. Despite the rise in overall incidents, total fatalities saw a significant decrease, dropping by 66.7% from 3 in the prior year to 1 in the current period. Total injuries also slightly decreased by 1.6%, from 124 to 122.
230
▲ 5.5%was 218
Total Crash Events
1
▼ -66.7%was 3
Persons Killed
122
▼ -1.6%was 124
Persons Injured
5
▼ -50.0%was 10
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes in Brockton saw a slight increase year-over-year, rising from 218 to 230, which represents a 5.5% increase. However, total fatalities decreased substantially by 66.7%, from 3 to 1. Total injuries remained relatively stable, with a minor decrease of 1.6% from 124 to 122.
5
Hit-and-Run Crashes — November 2023
▼ -50.0% vs prior (10)
Hit-and-run crashes decreased significantly year-over-year, dropping from 10 incidents in November 2022 to 5 incidents in November 2023. This represents a 50% reduction in the count of hit-and-run crashes. Consequently, the hit-and-run rate decreased from 4.6% to 2.2%.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
4
Pedestrians Injured
1
Cyclists Injured
117
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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 Tuesday in November 2022 (38 crashes) to Monday in November 2023 (41 crashes). Similarly, the peak crash hour moved from 4 p.m. in the prior period (18 crashes) to 5 p.m. in the current period (23 crashes). This indicates a shift in the busiest times for crash incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate decreased significantly from 1.4% (3 fatal crashes) in November 2022 to 0.4% (1 fatal crash) in November 2023. Serious injury crashes (severity A) increased from 6 to 8, while minor injury crashes (severity B) rose from 34 to 37. Overall, crashes resulting in any injury (A, B, or C) increased from 75 to 81.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor shifted from 'Failed to yield right of way' (64 crashes) in the prior period to 'No improper driving' (61 crashes) in the current period. 'Failed to yield right of way' crashes decreased by 24, from 64 to 40. Conversely, 'No improper driving' crashes increased by 26, from 35 to 61. 'Failure to keep in proper lane or running off road' crashes also increased, from 14 to 20.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased by 12, from 163 to 175, while those in 'Rain' conditions increased by 4, from 10 to 14. For lighting, crashes during 'Daylight' decreased by 14, from 110 to 96, while crashes in 'Dark - lighted roadway' increased by 18, from 78 to 96. Road surface conditions remained largely consistent, with 'Dry' conditions accounting for the vast majority of crashes in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 560 to 579 year-over-year. The 35-44 age group saw the largest increase in persons involved, rising by 18 from 93 to 111. In terms of vehicle makes, Honda saw an increase of 15 vehicles involved (from 68 to 83), while Toyota remained relatively stable, decreasing by 1 (from 84 to 83). Ford vehicles involved increased by 17, from 43 to 60.
Top Vehicle Makes (445 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records
53 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (525 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph speed zones increased slightly from 183 to 185. Notably, fatal crashes in 30 mph zones decreased from 3 to 1, leading to a reduction in the fatal rate for this zone from 1.639% to 0.541%. Crashes in 65 mph zones increased from 14 to 17, with no fatalities reported in either period for this speed limit.
Fatal crashes by zone: 30 mph: 1 of 185 (0.541%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-11-01 through 2023-11-30 (30 days)
- Geographic scope: BROCKTON, MA
- Total crash records analyzed: 230
- Total persons involved: 579
- Total vehicles involved: 445
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 2023." Published June 21, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brockton/november-2023-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: 2023-11-01 – 2023-11-30
Generated: June 21, 2026 · All rights reserved