ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BROCKTON, MA · 2025
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/2025-annual-report
Yearly Traffic Safety Analysis
2,492 CRASHES IN
BROCKTON, MA
2025
In the current period, there were 2,492 total crashes in Brockton, representing a 2.6% decrease from the 2,559 crashes recorded in the prior period. Despite the overall reduction in collisions, the most significant year-over-year change was a 142.9% increase in total fatalities, which rose from 7 to 17. The number of fatal crashes also increased from 7 to 12.
2,492
▼ -2.6%was 2,559
Total Crash Events
17
▲ 142.9%was 7
Persons Killed
1,325
▲ 7.6%was 1,231
Persons Injured
113
▲ 9.7%was 103
Hit-and-Run Crashes
Note: "Persons Killed" (17) counts individual fatalities across all crash events. "Fatal" in the severity table below (12) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 234 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The total number of crashes in Brockton showed a slight downward trend, decreasing by 2.6% from 2,559 in the prior year to 2,492 in the current year. While the overall volume of crashes fell, the outcomes became more severe. Total injuries rose by 7.6% from 1,231 to 1,325, and total fatalities increased significantly from 7 to 17.
113
Hit-and-Run Crashes — 2025
▲ 9.7% vs prior (103)
The number and rate of hit-and-run crashes both increased in the current period. The count of hit-and-run incidents rose from 103 to 113, a 9.7% year-over-year increase. Consequently, the hit-and-run rate, which measures the proportion of all crashes that are hit-and-runs, ticked up from 4.0% to 4.5%.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
15
Motorists Killed
0
Other Killed
60
Pedestrians Injured
19
Cyclists Injured
1,238
Motorists Injured
8
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal crash patterns shifted slightly between the two periods. The peak day for crashes moved from Friday (402 crashes) in the prior year to Sunday (381 crashes) in the current year. The peak hour for collisions remained consistent at 4 p.m. in both periods, although the number of crashes during this hour decreased from 202 to 193.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity worsened in the current period compared to the prior year. The number of fatal crashes increased from 7 to 12, raising their share of total crashes from 0.3% to 0.5%. While the proportion of 'Serious Injury' crashes remained stable (2.4% vs. 2.6%), the share of 'Minor Injury' crashes grew from 15.7% to 19.5% of all crashes. Conversely, the share of 'Possible Injury' crashes decreased from 14.4% to 12.0%.
Severity is per crash event (most severe injury). 12 fatal crash events resulted in 17 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors, 'No improper driving' and 'Failed to yield right of way,' maintained their rankings in both periods. The count of crashes attributed to 'Failed to yield right of way' decreased slightly from 458 to 448. Notably, crashes involving 'Followed too closely' decreased by 19.4% in count, from 186 to 150 incidents. Similarly, crashes attributed to 'Failure to keep in proper lane or running off road' dropped from 161 to 137, a 14.9% decrease in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The environmental conditions at the time of crashes remained highly consistent year-over-year. In both periods, the majority of collisions occurred during 'Daylight' hours (61.8% in the current period vs. 61.7% in the prior). Crashes on 'Dry' road surfaces accounted for over 79% of the total in both years (79.1% vs. 79.8%), and there were no notable shifts in the proportion of crashes occurring during adverse weather.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes were consistent across both periods, with Toyota, Honda, Nissan, and Ford remaining the top four. The age distribution of persons involved in crashes also showed general stability, with the 26-34 and 35-44 age groups being the most represented in both years. However, the number of persons in the 65+ age group involved in crashes increased from 460 to 538.
Top Vehicle Makes (4,865 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
557 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (5,791 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes by speed limit was nearly identical year-over-year, with approximately 87% of all incidents in both periods occurring in 30 mph zones. The number of crashes in these 30 mph zones remained stable, changing from 2,182 to 2,168. However, the number of fatalities recorded in 30 mph zones increased from 7 to 11, and the current year saw one fatality in a 65 mph zone, which had zero fatalities in the prior year.
Fatal crashes by zone: 30 mph: 11 of 2,168 (0.507%) · 65 mph: 1 of 83 (1.205%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: BROCKTON, MA
- Total crash records analyzed: 2,492
- Total persons involved: 6,382
- Total vehicles involved: 4,865
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brockton/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved