ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BROCKTON, MA · APRIL 2026
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/april-2026-report
Monthly Traffic Safety Analysis
132 CRASHES IN
BROCKTON, MA
APRIL 2026
Total crashes in Brockton for April 2026 were 132, representing a 37.7% decrease compared to the 212 crashes recorded in April 2025. Despite this overall reduction in incidents, fatalities increased from 0 in the prior period to 2 in the current period. The most notable year-over-year shift is the significant decrease in total crashes.
132
▼ -37.7%was 212
Total Crash Events
2
Persons Killed
83
▼ -21.7%was 106
Persons Injured
3
▼ -66.7%was 9
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Brockton show a notable decrease, with total crashes falling by 80, or 37.7%, from 212 in April 2025 to 132 in April 2026. Despite this reduction in total incidents, fatalities increased from 0 to 2 during the same period. Total injuries also decreased by 23, a 21.7% reduction, from 106 to 83.
3
Hit-and-Run Crashes — April 2026
▼ -66.7% vs prior (9)
Hit-and-run crashes decreased by 6, from 9 incidents in April 2025 to 3 in April 2026. The hit-and-run crash rate also declined from 4.2% of all crashes in April 2025 to 2.3% in April 2026. This represents a decrease of 1.9 percentage points year-over-year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
7
Pedestrians Injured
2
Cyclists Injured
74
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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 Saturday in April 2025 (36 crashes) to Wednesday in April 2026 (25 crashes). Similarly, the peak crash hour moved from 6 p.m. (19 crashes) in April 2025 to 3 p.m. (11 crashes) in April 2026. This indicates a shift in when the highest number of crashes occurred during the week and day.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes increased from 0 in April 2025 to 2 in April 2026, raising the fatal crash rate from 0% to 1.5% of all crashes. Serious injury crashes decreased from 7 (3.3% share) to 4 (3% share) year-over-year. Minor injury crashes saw a decrease in count from 46 to 37, but an increase in share from 21.7% to 28%. Crashes with no injuries decreased significantly in count from 122 to 73, though their share remained relatively stable at 57.5% and 55.3% respectively.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Most severe injury per crash record
Top Contributing Factors
The contributing factor 'Failed to yield right of way' saw a significant decrease of 24 crashes, a 57.1% reduction in count, from 42 in April 2025 to 18 in April 2026. 'Failure to keep in proper lane or running off road' also decreased substantially, dropping by 16 crashes, an 84.2% reduction in count, from 19 to 3. Conversely, 'Other improper action' increased by 2 crashes, a 25% increase in count, from 8 to 10.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions decreased by 54, from 126 in April 2025 to 72 in April 2026, while crashes during 'Rain' decreased by 15, from 26 to 11. The number of crashes occurring in 'Daylight' decreased by 63, from 151 to 88. Crashes on 'Dry' road surfaces also decreased by 60, from 164 to 104.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 171, a 39.6% reduction, from 432 in April 2025 to 261 in April 2026. Toyota remained the top vehicle make involved, though its count decreased from 84 to 46. The age group with the largest decrease in persons involved was 35-44, falling by 34 persons from 98 to 64.
Top Vehicle Makes (261 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Vehicle unit records
31 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (327 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph speed zones decreased by 64, from 177 in April 2025 to 113 in April 2026. Notably, this speed zone accounted for 2 fatal crashes in April 2026, whereas no fatal crashes were reported in any speed zone in April 2025. Crashes in 65 mph zones also decreased, from 12 to 9.
Fatal crashes by zone: 30 mph: 2 of 113 (1.77%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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: 2026-04-01 through 2026-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-04-01 through 2026-04-30 (30 days)
- Geographic scope: BROCKTON, MA
- Total crash records analyzed: 132
- Total persons involved: 354
- Total vehicles involved: 261
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: April 2026." Published June 21, 2026. Reporting period: 2026-04-01 to 2026-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brockton/april-2026-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: 2026-04-01 – 2026-04-30
Generated: June 21, 2026 · All rights reserved