Monthly Traffic Safety Analysis

176 CRASHES IN
BROCKTON, MA
MARCH 2022

All metrics benchmarked againstMarch 2021

In March 2022, Brockton experienced 176 total crashes, a slight increase from the 172 crashes recorded in March 2021, representing a 2.33% rise. The most significant year-over-year shift was the increase in fatalities, with 1 fatality reported in March 2022 compared to 0 in March 2021.

176

2.3%was 172

Total Crash Events

1

Persons Killed

119

60.8%was 74

Persons Injured

6

200.0%was 2

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. 39 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Brockton showed a slight upward trend year-over-year, with total crashes increasing from 172 in March 2021 to 176 in March 2022. This represents a modest 2.33% increase in total crash volume. Fatalities also increased from 0 to 1 during this period.

6

Hit-and-Run Crashes — March 2022

200.0% vs prior (2)

Hit-and-run crashes increased significantly year-over-year, rising from 2 incidents in March 2021 to 6 incidents in March 2022. Consequently, the hit-and-run rate more than doubled, increasing from 1.2% of total crashes in March 2021 to 3.4% in March 2022, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

5

Pedestrians Injured

Prior: 2150.0%

112

Motorists Injured

Prior: 7060.0%

2

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Monday (34 crashes) in March 2021 to Wednesday (31 crashes) in March 2022. While 4 PM remained a peak hour for crashes in both periods, the number of crashes at this hour decreased from 17 in March 2021 to 15 in March 2022. Overall, crash distribution across days of the week and hours of the day showed minor shifts.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The most significant change in crash severity was the occurrence of 1 fatal crash in March 2022, compared to 0 fatal crashes in March 2021. Serious injury crashes increased from 3 (1.7% of total crashes) in March 2021 to 5 (2.8% of total crashes) in March 2022. Minor injury crashes remained stable at 26 in both periods, though their proportion slightly decreased from 15.1% to 14.8% of total crashes.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
Serious Injury5serious injury crashes2.8%
66.7%prior 3
Minor Injury26minor injury crashes14.8%
0.0%prior 26
Possible Injury34possible injury crashes19.3%
30.8%prior 26
No Injury71no injury crashes40.3%
-13.4%prior 82

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'Failed to yield right of way,' decreased in count from 33 in March 2021 to 26 in March 2022. 'No improper driving' increased from 31 crashes in March 2021 to 36 crashes in March 2022, becoming the most frequent factor. 'Followed too closely' saw a decrease from 17 crashes to 8 crashes, while 'Failure to keep in proper lane or running off road' increased from 12 crashes to 17 crashes year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving36 (20.5%)16.1%prior 31
Failed to yield right of way26 (14.8%)-21.2%prior 33
Failure to keep in proper lane or running off road17 (9.7%)41.7%prior 12
Inattention14 (8%)55.6%prior 9
Disregarded traffic signs, signals, road markings9 (5.1%)80.0%prior 5
Followed too closely8 (4.5%)-52.9%prior 17
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner7 (4%)
Over-correcting/over-steering4 (2.3%)
Other improper action4 (2.3%)-50.0%prior 8
Fatigued/asleep2 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions slightly decreased from 122 in March 2021 to 119 in March 2022. Conversely, crashes in 'Rain' conditions significantly increased from 6 to 17, and 'Wet' road surface crashes rose from 18 to 45. Crashes during 'Daylight' decreased from 115 to 101, while crashes in 'Dark - lighted roadway' increased from 45 to 53.

Weather

Clear119 (68.0%)
-2.5%prior 122
Rain17 (9.7%)
183.3%prior 6
Cloudy16 (9.1%)
60.0%prior 10
Rain/Cloudy4 (2.3%)
Clear/Cloudy3 (1.7%)
-75.0%prior 12
Clear/Unknown3 (1.7%)
-70.0%prior 10
Snow2 (1.1%)
Clear/Other2 (1.1%)
Sleet, hail (freezing rain or drizzle)2 (1.1%)
Cloudy/Snow1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash

Lighting

Daylight101 (57.4%)
-12.2%prior 115
Dark - lighted roadway53 (30.1%)
17.8%prior 45
Dusk8 (4.5%)
Dark - roadway not lighted7 (4.0%)
40.0%prior 5
Dawn5 (2.8%)
Dark - unknown roadway lighting2 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field

Road Surface

Dry128 (72.7%)
-16.9%prior 154
Wet45 (25.6%)
150.0%prior 18
Ice2 (1.1%)
Water (standing, moving)1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 319 in March 2021 to 337 in March 2022. Toyota remained the top make involved, though its count decreased from 64 to 59. The 35-44 age group saw the highest number of persons involved in crashes in March 2022 with 85, a notable increase from the 60 in the prior period, while the 26-34 age group had the highest count in March 2021 with 76 persons.

Top Vehicle Makes (337 vehicles)

1
TOYOTA59 (17.5%)
-7.8%prior 64
2
HONDA48 (14.2%)
14.3%prior 42
3
NISSAN33 (9.8%)
-5.7%prior 35
4
CHEVROLET32 (9.5%)
33.3%prior 24
5
FORD28 (8.3%)
3.7%prior 27
6
JEEP12 (3.6%)
20.0%prior 10
7
HYUNDAI11 (3.3%)
-45.0%prior 20
8
BMW10 (3%)
9
DODGE10 (3%)
42.9%prior 7
10
GMC9 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records

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

Sex Distribution (433 persons with recorded sex)

Male258 (59.6%)
16.7%prior 221
Female175 (40.4%)
1.7%prior 172

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events

Speed Limit Zones

The majority of crashes in both periods occurred in 30 mph zones, with 149 crashes in March 2021 decreasing to 143 crashes in March 2022. Crashes in 65 mph zones increased from 10 to 12 year-over-year. Notably, the 65 mph zone recorded 1 fatal crash in March 2022, resulting in an 8.333% fatal rate for that zone, compared to 0 fatal crashes in the same zone in March 2021.

Fatal crashes by zone: 65 mph: 1 of 12 (8.333%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-03-01 through 2022-03-31 (31 days)
  • Geographic scope: BROCKTON, MA
  • Total crash records analyzed: 176
  • Total persons involved: 464
  • Total vehicles involved: 337

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: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brockton/march-2022-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 — March 2022 | ThatCarHitMe.com