ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BROCKTON, MA · 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/2023-annual-report
Yearly Traffic Safety Analysis
2,338 CRASHES IN
BROCKTON, MA
2023
In 2023, Brockton recorded 2,338 traffic crashes, a 5.8% decrease from the 2,483 crashes reported in 2022. While overall crashes, injuries, and fatalities declined, the number of crashes resulting in serious injuries increased from 61 to 85, a year-over-year rise of 39.3%.
2,338
▼ -5.8%was 2,483
Total Crash Events
6
▼ -14.3%was 7
Persons Killed
1,226
▼ -6.3%was 1,308
Persons Injured
78
▲ 5.4%was 74
Hit-and-Run Crashes
Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 380 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic collisions in Brockton showed a downward trend from 2022 to 2023. The total number of crashes decreased by 5.8%, from 2,483 to 2,338. Similarly, the number of people injured fell by 6.3% from 1,308 to 1,226, and fatalities decreased from 7 to 6.
78
Hit-and-Run Crashes — 2023
▲ 5.4% vs prior (74)
Hit-and-run incidents showed a slight increase from 2022 to 2023. The total number of hit-and-run crashes rose from 74 to 78. As a proportion of all crashes, the hit-and-run rate also trended upward, increasing from 3.0% in 2022 to 3.3% in 2023.
Vulnerable Road User Casualties
3
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
46
Pedestrians Injured
13
Cyclists Injured
1,165
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes saw a slight shift between the two periods. In 2023, the peak day for crashes was Monday with 384 incidents, a change from 2022 when Friday was the peak day with 389 incidents. The peak hour for crashes remained consistent at 4 PM in both years, though the number of crashes during that hour decreased from 194 in 2022 to 178 in 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the total number of crashes declined, the severity profile shifted year-over-year. The fatal crash rate decreased slightly from 0.28 to 0.26 per 100 crashes. However, the number of crashes involving serious injuries rose from 61 to 85, and their share of all crashes increased from 2.5% in 2022 to 3.6% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes shifted between 2022 and 2023. In 2023, 'No improper driving' was the most cited factor with 505 crashes, taking the top spot from 'Failed to yield right of way' which had 481 crashes in 2022. The count for 'Failed to yield right of way' decreased slightly to 471 in 2023. Notably, crashes attributed to 'Followed too closely' saw a significant 27.6% decrease in count, from 225 in 2022 to 163 in 2023.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in clear weather and daylight decreased from 2022 to 2023. Crashes during rainy conditions increased from 7.3% to 9.4% of all incidents, and collisions on wet roads rose from 17.4% to 19.2%. Similarly, the share of crashes happening in darkness on lighted roadways grew from 28.8% in 2022 to 31.8% in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The demographic profile of vehicles and persons involved in crashes remained largely stable year-over-year. Toyota, Honda, Nissan, and Ford were the top four most frequently involved vehicle makes in both 2022 and 2023, with only minor fluctuations in their counts. The age distribution of all persons involved in crashes also saw no significant shifts, with the 26-34 and 35-44 age groups consistently representing the largest cohorts in both periods.
Top Vehicle Makes (4,568 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
567 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (5,533 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The vast majority of crashes in both years occurred in 30 MPH zones, though the count in this zone decreased from 2,065 in 2022 to 1,935 in 2023. Fatalities within the 30 MPH zone were halved, dropping from 6 to 3. Conversely, crashes in 65 MPH zones remained stable at 137, but the number of fatalities in this zone doubled from 1 to 2, increasing the fatal crash rate for that zone from 0.74% to 1.46%.
Fatal crashes by zone: 30 mph: 3 of 1,935 (0.155%) · 65 mph: 2 of 137 (1.46%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: BROCKTON, MA
- Total crash records analyzed: 2,338
- Total persons involved: 6,087
- Total vehicles involved: 4,568
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brockton/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved