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YEAR-OVER-YEAR CRASH REPORT · BROCKTON, MA · NOVEMBER 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
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GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/brockton/november-2022-report
Monthly Traffic Safety Analysis
218 CRASHES IN
BROCKTON, MA
NOVEMBER 2022
In November 2022, BROCKTON experienced 218 total crashes, an increase of 10.66% compared to the 197 crashes recorded in November 2021. The number of serious injury crashes notably doubled, rising from 3 in the prior period to 6 in the current period. Total fatalities remained stable at 3 for both periods.
218
▲ 10.7%was 197
Total Crash Events
3
Persons Killed
124
▲ 9.7%was 113
Persons Injured
10
▲ 66.7%was 6
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. 54 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for BROCKTON indicates an upward trend year-over-year, with total crashes increasing by 10.66% from 197 to 218. Total injuries also saw an increase of 9.73%, rising from 113 to 124, while total fatalities remained unchanged at 3.
10
Hit-and-Run Crashes — November 2022
▲ 66.7% vs prior (6)
Hit-and-run crashes increased significantly year-over-year, rising by 66.67% from 6 crashes in November 2021 to 10 crashes in November 2022. Consequently, the hit-and-run rate also increased from 3.0% to 4.6% of all crashes, indicating an upward trend.
Vulnerable Road User Casualties
1
Pedestrians Killed
2
Motorists Killed
4
Pedestrians Injured
120
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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 Friday with 33 crashes in November 2021 to Tuesday with 38 crashes in November 2022. The peak hour for crashes remained consistent at 4 p.m. in both periods, although the count slightly decreased from 19 to 18 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate remained relatively stable, with 3 fatal crashes in both periods, representing 1.5% of total crashes in the prior period and 1.4% in the current period. Serious injury crashes (severity 'A') increased from 3 (1.5% share) to 6 (2.8% share), indicating a rise in the proportion of more severe outcomes. Conversely, possible injury crashes (severity 'C') decreased from 38 (19.3% share) to 35 (16.1% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor shifted from 'No improper driving' in the prior period to 'Failed to yield right of way' in the current period. Crashes attributed to 'Failed to yield right of way' increased by 106.45%, from 31 to 64. Meanwhile, 'No improper driving' crashes decreased by 20.45%, from 44 to 35. 'Followed too closely' crashes increased by 23.53%, from 17 to 21, maintaining its position as the third most frequent factor.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in clear weather conditions slightly decreased from 81.2% in the prior period to 74.8% in the current period. Crashes on dry road surfaces saw a slight increase in their proportion, from 90.3% to 91.3%. The proportion of crashes occurring in daylight conditions increased from 47.2% to 50.5%, while those in 'Dark - lighted roadway' conditions decreased from 43.7% to 35.8%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 513 to 560 year-over-year. There was a notable decrease in persons aged 45-54, from 77 to 46, while the 65+ age group saw a significant increase from 25 to 48. Toyota surpassed Honda as the top vehicle make involved in crashes, with its count increasing from 47 to 84, while Honda's count rose from 64 to 68.
Top Vehicle Makes (436 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records
54 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (500 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone increased from 165 to 183 year-over-year, and fatalities in this zone also increased from 2 to 3. The fatal crash rate for the 30 mph zone slightly increased from 1.212% to 1.639%. While the prior period recorded 1 fatality in the 35 mph zone, the current period reported no fatalities in this zone.
Fatal crashes by zone: 30 mph: 3 of 183 (1.639%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-11-01 through 2022-11-30 (30 days)
- Geographic scope: BROCKTON, MA
- Total crash records analyzed: 218
- Total persons involved: 560
- Total vehicles involved: 436
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 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brockton/november-2022-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: 2022-11-01 – 2022-11-30
Generated: June 21, 2026 · All rights reserved