Yearly Traffic Safety Analysis

2,483 CRASHES IN
BROCKTON, MA
2022

All metrics benchmarked against2021

In 2022, Brockton recorded 2,483 total traffic crashes, a 3.9% increase from the 2,389 crashes reported in 2021. While overall crashes saw a modest rise, the most notable year-over-year change was a 71.8% increase in crashes involving pedestrians, which rose from 39 in 2021 to 67 in 2022.

2,483

3.9%was 2,389

Total Crash Events

7

Persons Killed

1,308

-12.2%was 1,490

Persons Injured

74

15.6%was 64

Hit-and-Run Crashes

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (7) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 542 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes in Brockton increased by 3.9% from 2,389 in 2021 to 2,483 in 2022. Despite the rise in total crashes, the number of reported injuries decreased by 12.2%, from 1,490 to 1,308. The number of fatalities remained unchanged at 7 for both years.

74

Hit-and-Run Crashes — 2022

15.6% vs prior (64)

The number of hit-and-run crashes increased from 64 in 2021 to 74 in 2022, representing a 15.6% rise in count. The hit-and-run rate, which measures the number of such incidents per 100 total crashes, also trended upwards, increasing from 2.7 to 3.0. This indicates that hit-and-run incidents grew both in absolute numbers and as a proportion of all crashes.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 30.0%

0

Cyclists Killed

Prior: 00.0%

4

Motorists Killed

Prior: 40.0%

0

Other Killed

Prior: 00.0%

56

Pedestrians Injured

Prior: 3180.6%

14

Cyclists Injured

Prior: 1216.7%

1,235

Motorists Injured

Prior: 1,447-14.7%

3

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between 2021 and 2022. The peak day for crashes moved from Sunday (364 crashes) in 2021 to Friday (389 crashes) in 2022. The peak hour for collisions remained consistent at 4 p.m. in both years, with a slight increase in incidents from 184 to 194. Crashes on Mondays and Wednesdays also saw notable increases from the prior year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes remained stable at 7 in both 2021 and 2022, with the fatal crash rate per 100 crashes slightly decreasing from 0.29 to 0.28. While total crashes increased, the proportion of crashes resulting in injury declined. Crashes categorized as Minor Injury dropped from representing 19.3% of all crashes in 2021 to 14.5% in 2022, while the share of crashes with no reported injuries increased from 44.8% to 46.2%.

Outcome by Severity (Crash Events)

Fatal7fatal crashes0.3%
0.0%prior 7
Serious Injury61serious injury crashes2.5%
-1.6%prior 62
Minor Injury359minor injury crashes14.5%
-22.0%prior 460
Possible Injury368possible injury crashes14.8%
-5.9%prior 391
No Injury1,146no injury crashes46.2%
7.0%prior 1,071

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

The ranking of top contributing factors shifted between 2021 and 2022. 'Failed to yield right of way' became the most cited factor in 2022, with its count increasing by 10.8% from 434 to 481 incidents, overtaking 'No improper driving'. The count for crashes attributed to 'Followed too closely' also grew, rising 16.6% from 193 to 225. 'Failure to keep in proper lane' increased by 11.2% from 143 to 159 crashes.

Officer-Reported Primary Contributing Cause

Failed to yield right of way481 (19.4%)10.8%prior 434
No improper driving474 (19.1%)1.5%prior 467
Followed too closely225 (9.1%)16.6%prior 193
Failure to keep in proper lane or running off road159 (6.4%)11.2%prior 143
Inattention125 (5%)1.6%prior 123
Disregarded traffic signs, signals, road markings103 (4.1%)12.0%prior 92
Other improper action89 (3.6%)23.6%prior 72
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner53 (2.1%)-14.5%prior 62
Distracted45 (1.8%)-2.2%prior 46
Driving too fast for conditions31 (1.2%)3.3%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with the majority of incidents in both periods occurring during daylight (61.7% in 2022 vs. 60.4% in 2021) and on dry roads (78.9% vs. 79.3%). There was a decrease in crashes on dark but lighted roadways, from 745 incidents in 2021 to 714 in 2022. Conversely, crashes occurring on snowy or icy road surfaces increased from 55 in 2021 to 77 in 2022.

Weather

Clear1,778 (71.8%)
10.2%prior 1,614
Rain181 (7.3%)
-9.0%prior 199
Cloudy153 (6.2%)
15.9%prior 132
Clear/Cloudy69 (2.8%)
-39.5%prior 114
Clear/Unknown65 (2.6%)
-21.7%prior 83
Cloudy/Rain55 (2.2%)
-12.7%prior 63
Snow52 (2.1%)
30.0%prior 40
Clear/Other25 (1.0%)
-28.6%prior 35
Rain/Cloudy24 (1.0%)
20.0%prior 20
Sleet, hail (freezing rain or drizzle)11 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight1,531 (61.7%)
6.2%prior 1,442
Dark - lighted roadway714 (28.8%)
-4.2%prior 745
Dark - roadway not lighted86 (3.5%)
13.2%prior 76
Dusk70 (2.8%)
11.1%prior 63
Dawn59 (2.4%)
40.5%prior 42
Dark - unknown roadway lighting17 (0.7%)
30.8%prior 13
Other4 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry1,960 (79.1%)
3.4%prior 1,895
Wet433 (17.5%)
0.7%prior 430
Snow50 (2.0%)
16.3%prior 43
Ice27 (1.1%)
125.0%prior 12
Slush4 (0.2%)
Sand, mud, dirt, oil, gravel2 (0.1%)
Other1 (0.0%)
Water (standing, moving)1 (0.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top five vehicle makes involved in crashes—Toyota, Honda, Nissan, Ford, and Chevrolet—remained consistent between 2021 and 2022. Most of these top makes saw an increase in crash involvement, though Nissan-involved crashes decreased from 560 to 494. Analysis of persons involved in crashes shows a notable 20.3% increase in the 65+ age group, from 354 individuals in 2021 to 426 in 2022.

Top Vehicle Makes (4,816 vehicles)

1
TOYOTA894 (18.6%)
8.0%prior 828
2
HONDA718 (14.9%)
3.3%prior 695
3
NISSAN494 (10.3%)
-11.8%prior 560
4
FORD489 (10.2%)
4.5%prior 468
5
CHEVROLET351 (7.3%)
12.1%prior 313
6
HYUNDAI177 (3.7%)
-6.3%prior 189
7
JEEP173 (3.6%)
9.5%prior 158
8
DODGE123 (2.6%)
4.2%prior 118
9
BMW105 (2.2%)
7.1%prior 98
10
INFI100 (2.1%)
4.2%prior 96

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (5,767 persons with recorded sex)

Male3,343 (58.0%)
4.1%prior 3,210
Female2,422 (42.0%)
-0.9%prior 2,445
X / Unspecified2 (0.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

The vast majority of crashes in both years occurred in 30 mph speed zones, with counts remaining stable at 2,052 in 2021 and 2,065 in 2022. However, the number of fatal crashes within this zone increased from 5 to 6. Crashes in the 65 mph zone increased from 118 in 2021 to 136 in 2022, and this zone recorded one fatal crash in 2022 where there were none the prior year.

Fatal crashes by zone: 30 mph: 6 of 2,065 (0.291%) · 65 mph: 1 of 136 (0.735%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: BROCKTON, MA
  • Total crash records analyzed: 2,483
  • Total persons involved: 6,314
  • Total vehicles involved: 4,816

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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brockton/2022-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

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Brockton, MA Crash Report — 2022 | ThatCarHitMe.com