Monthly Traffic Safety Analysis

231 CRASHES IN
BROCKTON, MA
MAY 2023

All metrics benchmarked againstMay 2022

In May 2023, BROCKTON experienced 231 total crashes, a slight decrease from 235 crashes in May 2022, representing a 1.7% reduction. Total fatalities remained stable at 1 in both periods, while total injuries increased by 17.3% from 104 to 122. The most notable shift was a 71.4% decrease in DUI-related crashes, falling from 7 to 2.

231

-1.7%was 235

Total Crash Events

1

Persons Killed

122

17.3%was 104

Persons Injured

9

80.0%was 5

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 34 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend shows a slight decrease in total crashes, with 231 in May 2023 compared to 235 in May 2022. Fatalities remained constant at 1 in both periods. However, total injuries increased by 17.3%, rising from 104 in May 2022 to 122 in May 2023.

9

Hit-and-Run Crashes — May 2023

80.0% vs prior (5)

Hit-and-run crashes increased significantly, rising by 4 incidents from 5 in May 2022 to 9 in May 2023, an 80% increase. This change resulted in the hit-and-run crash rate increasing from 2.1% in May 2022 to 3.9% in May 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

5

Pedestrians Injured

Prior: 366.7%

2

Cyclists Injured

Prior: 20.0%

115

Motorists Injured

Prior: 9916.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Monday in both periods, with 46 crashes in May 2023 compared to 43 in May 2022. Similarly, the peak hour for crashes remained 4 PM, with 24 crashes in May 2023, an increase from 21 crashes at 4 PM in May 2022. No significant shifts in the overall temporal patterns were observed, though Monday saw a slight increase in crash count.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained constant at 1 in both May 2023 and May 2022, maintaining a fatal crash rate of 0.4%. Serious injury crashes (severity A) increased by 60%, from 5 in May 2022 to 8 in May 2023, while minor injury crashes (severity B) rose by 41.4%, from 29 to 41. Conversely, possible injury crashes (severity C) decreased by 24.3%, from 37 to 28.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
0.0%prior 1
Serious Injury8serious injury crashes3.5%
60.0%prior 5
Minor Injury41minor injury crashes17.7%
41.4%prior 29
Possible Injury28possible injury crashes12.1%
-24.3%prior 37
No Injury119no injury crashes51.5%
5.3%prior 113

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record

Top Contributing Factors

The most frequent contributing factor in May 2023 was 'No improper driving' with 52 crashes, an increase of 6 crashes (13.0%) from May 2022. 'Failed to yield right of way' decreased slightly by 2 crashes (3.8%), from 53 to 51. 'Followed too closely' saw a significant decrease of 8 crashes (34.8%), falling from 23 to 15, while 'Other improper action' decreased by 10 crashes (58.8%), from 17 to 7.

Officer-Reported Primary Contributing Cause

No improper driving52 (22.5%)13.0%prior 46
Failed to yield right of way51 (22.1%)-3.8%prior 53
Followed too closely15 (6.5%)-34.8%prior 23
Failure to keep in proper lane or running off road13 (5.6%)8.3%prior 12
Inattention9 (3.9%)-25.0%prior 12
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway8 (3.5%)60.0%prior 5
Other improper action7 (3%)-58.8%prior 17
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner5 (2.2%)-16.7%prior 6
Fatigued/asleep3 (1.3%)
Disregarded traffic signs, signals, road markings3 (1.3%)-50.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased by 12, from 195 in May 2022 to 183 in May 2023, while crashes in 'Rain' conditions increased by 9, from 5 to 14. Crashes on 'Dry' road surfaces decreased by 11, from 221 to 210, whereas crashes on 'Wet' road surfaces increased by 7, from 14 to 21. Crashes during 'Daylight' decreased by 11, from 174 to 163, but crashes in 'Dark - lighted roadway' increased by 4, from 45 to 49.

Weather

Clear183 (79.9%)
-6.2%prior 195
Rain14 (6.1%)
180.0%prior 5
Clear/Unknown9 (3.9%)
50.0%prior 6
Cloudy9 (3.9%)
-10.0%prior 10
Clear/Cloudy7 (3.1%)
40.0%prior 5
Cloudy/Rain3 (1.3%)
Rain/Unknown3 (1.3%)
Clear/Other1 (0.4%)
-88.9%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight163 (70.6%)
-6.3%prior 174
Dark - lighted roadway49 (21.2%)
8.9%prior 45
Dusk9 (3.9%)
28.6%prior 7
Dark - roadway not lighted5 (2.2%)
0.0%prior 5
Dawn5 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry210 (90.9%)
-5.0%prior 221
Wet21 (9.1%)
50.0%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved decreased slightly from 456 in May 2022 to 451 in May 2023. Toyota became the most frequently involved vehicle make in May 2023 with 83 vehicles, surpassing Honda which decreased from 74 to 67. The 26-34 age group remained the most represented among persons involved in crashes, with a slight increase from 107 to 109, and female persons involved increased from 228 to 255.

Top Vehicle Makes (451 vehicles)

1
TOYOTA83 (18.4%)
16.9%prior 71
2
HONDA67 (14.9%)
-9.5%prior 74
3
FORD51 (11.3%)
4.1%prior 49
4
NISSAN44 (9.8%)
-8.3%prior 48
5
CHEVROLET29 (6.4%)
7.4%prior 27
6
JEEP25 (5.5%)
38.9%prior 18
7
HYUNDAI15 (3.3%)
-31.8%prior 22
8
VOLKSWAGEN12 (2.7%)
20.0%prior 10
9
DODGE11 (2.4%)
22.2%prior 9
10
MERCEDES-BENZ10 (2.2%)
11.1%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

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

Sex Distribution (550 persons with recorded sex)

Male295 (53.6%)
-0.3%prior 296
Female255 (46.4%)
11.8%prior 228

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph speed zones decreased by 8, from 198 in May 2022 to 190 in May 2023, with both periods recording 1 fatal crash in this zone. Conversely, crashes in 65 mph speed zones increased by 5, from 10 in May 2022 to 15 in May 2023, with no fatal crashes reported in this zone during either period. The fatal crash rate in 30 mph zones slightly increased from 0.505% to 0.526%.

Fatal crashes by zone: 30 mph: 1 of 190 (0.526%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-05-01 through 2023-05-31 (31 days)
  • Geographic scope: BROCKTON, MA
  • Total crash records analyzed: 231
  • Total persons involved: 600
  • Total vehicles involved: 451

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: May 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brockton/may-2023-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 — May 2023 | ThatCarHitMe.com