Monthly Traffic Safety Analysis

212 CRASHES IN
BROCKTON, MA
APRIL 2025

All metrics benchmarked againstApril 2024

April 2025 saw 212 crashes in Brockton, a 2.9% increase from 206 crashes in April 2024. The most significant year-over-year shift was a 600% increase in serious injury crashes, rising from 1 to 7. Total injuries decreased by 10.2%, from 118 to 106.

212

2.9%was 206

Total Crash Events

0

Persons Killed

106

-10.2%was 118

Persons Injured

9

125.0%was 4

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 21 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in Brockton saw a slight increase of 2.9% from 206 in April 2024 to 212 in April 2025. While total injuries decreased by 10.2% from 118 to 106, the number of fatal crashes remained stable at zero in both periods.

9

Hit-and-Run Crashes — April 2025

125.0% vs prior (4)

Hit-and-run crashes increased significantly by 5, from 4 in April 2024 to 9 in April 2025. The hit-and-run rate more than doubled, rising from 1.9% to 4.2% of total crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

4

Pedestrians Injured

Prior: 40.0%

101

Motorists Injured

Prior: 114-11.4%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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 Monday (35 crashes) in April 2024 to Saturday (36 crashes) in April 2025. The peak crash hour also shifted from 9 p.m. (15 crashes) in April 2024 to 6 p.m. (19 crashes) in April 2025, indicating a change in the timing of peak crash activity.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Serious injury crashes (severity A) increased from 1 (0.5% of total crashes) in April 2024 to 7 (3.3%) in April 2025. Minor injury crashes (severity B) increased from 38 (18.4%) to 46 (21.7%), while possible injury crashes (severity C) decreased from 34 (16.5%) to 16 (7.5%). No fatal crashes were reported in either period.

Outcome by Severity (Crash Events)

Serious Injury7serious injury crashes3.3%
600.0%prior 1
Minor Injury46minor injury crashes21.7%
21.1%prior 38
Possible Injury16possible injury crashes7.5%
-52.9%prior 34
No Injury122no injury crashes57.5%
17.3%prior 104

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Most severe injury per crash record

Top Contributing Factors

The count of 'Failure to keep in proper lane or running off road' as a contributing factor increased by 8 crashes, from 11 to 19. 'Disregarded traffic signs, signals, road markings' also saw a notable increase of 5 crashes, rising from 5 to 10. Conversely, 'Failed to yield right of way' decreased by 3 crashes, from 45 to 42.

Officer-Reported Primary Contributing Cause

No improper driving53 (25%)1.9%prior 52
Failed to yield right of way42 (19.8%)-6.7%prior 45
Failure to keep in proper lane or running off road19 (9%)72.7%prior 11
Followed too closely11 (5.2%)10.0%prior 10
Inattention11 (5.2%)57.1%prior 7
Disregarded traffic signs, signals, road markings10 (4.7%)100.0%prior 5
Other improper action8 (3.8%)33.3%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (1.4%)
Over-correcting/over-steering3 (1.4%)
Visibility obstructed3 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes on wet road surfaces increased by 10, from 37 in April 2024 to 47 in April 2025. Crashes occurring in daylight increased by 10, from 141 to 151, while those in dark-lighted roadway conditions decreased by 12, from 51 to 39. Clear weather conditions remained the most common for crashes, decreasing slightly from 130 to 126.

Weather

Clear126 (59.4%)
-3.1%prior 130
Rain26 (12.3%)
4.0%prior 25
Clear/Cloudy19 (9.0%)
216.7%prior 6
Cloudy10 (4.7%)
-52.4%prior 21
Cloudy/Rain9 (4.2%)
28.6%prior 7
Rain/Cloudy7 (3.3%)
Clear/Unknown6 (2.8%)
-50.0%prior 12
Clear/Clear4 (1.9%)
Clear/Other3 (1.4%)
Cloudy/Cloudy1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash

Lighting

Daylight151 (71.2%)
7.1%prior 141
Dark - lighted roadway39 (18.4%)
-23.5%prior 51
Dawn14 (6.6%)
75.0%prior 8
Dark - roadway not lighted5 (2.4%)
Dusk2 (0.9%)
Dark - unknown roadway lighting1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field

Road Surface

Dry164 (77.4%)
-1.2%prior 166
Wet47 (22.2%)
27.0%prior 37
Sand, mud, dirt, oil, gravel1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 14, from 418 to 432. Among top makes, HONDA and CHEVROLET vehicles involved in crashes increased by 16 each, while TOYOTA saw a decrease of 18. The 65+ age group experienced a notable increase of 15 persons involved in crashes, rising from 33 to 48, while the 26-34 age group saw a decrease of 23 persons.

Top Vehicle Makes (432 vehicles)

1
TOYOTA84 (19.4%)
-17.6%prior 102
2
HONDA74 (17.1%)
27.6%prior 58
3
NISSAN46 (10.6%)
17.9%prior 39
4
CHEVROLET38 (8.8%)
72.7%prior 22
5
FORD31 (7.2%)
-20.5%prior 39
6
HYUNDAI24 (5.6%)
-14.3%prior 28
7
JEEP17 (3.9%)
0.0%prior 17
8
SUBARU11 (2.5%)
120.0%prior 5
9
MERCEDES-BENZ11 (2.5%)
120.0%prior 5
10
ACURA10 (2.3%)
100.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records

60 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (480 persons with recorded sex)

Male270 (56.3%)
-1.8%prior 275
Female210 (43.8%)
2.4%prior 205

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 65 mph speed zones doubled, increasing by 6 from 6 in April 2024 to 12 in April 2025. Crashes in 30 mph zones, the most common speed limit, saw a slight increase of 2, from 175 to 177. No fatal crashes were reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-04-01 through 2025-04-30 (30 days)
  • Geographic scope: BROCKTON, MA
  • Total crash records analyzed: 212
  • Total persons involved: 540
  • Total vehicles involved: 432

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 2025." Published June 21, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brockton/april-2025-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

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Brockton, MA Crash Report — April 2025 | ThatCarHitMe.com