Yearly Traffic Safety Analysis

794 CRASHES IN
BRAINTREE, MA
2022

All metrics benchmarked against2021

In Braintree, total vehicle crashes increased by 21.8% from 652 in 2021 to 794 in 2022. This rise was accompanied by a 28.8% increase in injuries, from 288 to 371. The most notable year-over-year shift was the number of fatalities, which grew from 2 in 2021 to 5 in 2022, a 150% increase.

794

21.8%was 652

Total Crash Events

5

150.0%was 2

Persons Killed

371

28.8%was 288

Persons Injured

28

7.7%was 26

Hit-and-Run Crashes

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 54 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

Traffic collisions in Braintree showed a rising trend from 2021 to 2022. The total number of crashes increased by 142 incidents, or 21.8%. Concurrently, the number of people injured rose from 288 to 371, and fatalities increased from 2 to 5.

28

Hit-and-Run Crashes — 2022

7.7% vs prior (26)

The absolute number of hit-and-run crashes saw a minor increase from 26 in 2021 to 28 in 2022. However, relative to the overall increase in total collisions, the hit-and-run rate trended downward. These incidents constituted 4.0% of all crashes in 2021, a share that fell to 3.5% in 2022.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

5

Motorists Killed

Prior: 1400.0%

0

Other Killed

Prior: 00.0%

4

Pedestrians Injured

Prior: 40.0%

2

Cyclists Injured

Prior: 20.0%

364

Motorists Injured

Prior: 28229.1%

1

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 shifted slightly between the two periods. The peak day for collisions moved from Thursday in 2021 (116 crashes) to Friday in 2022 (132 crashes). The peak hour also shifted an hour later, from 3 PM in the prior year (69 crashes) to 4 PM in the current year (84 crashes).

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 severity of crashes worsened from 2021 to 2022. The number of fatal crashes increased from 2 to 5, raising the fatal crash rate from 0.31% to 0.63% of all incidents. The share of crashes resulting in serious injuries also grew from 1.5% to 2.0%. While the proportion of minor injury crashes decreased, the share of possible injury crashes increased from 12.6% to 15.2%.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.6%
150.0%prior 2
Serious Injury16serious injury crashes2%
60.0%prior 10
Minor Injury114minor injury crashes14.4%
7.5%prior 106
Possible Injury121possible injury crashes15.2%
47.6%prior 82
No Injury484no injury crashes61%
13.3%prior 427

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 top contributing factors remained consistent, but their counts shifted year-over-year. "Followed too closely" was the leading factor in both periods, with its count increasing by 28.7% from 108 incidents in 2021 to 139 in 2022. Speed-related factors saw significant growth; crashes attributed to "Driving too fast for conditions" more than doubled from 12 to 25 incidents, and those from "Exceeded authorized speed limit" rose from 9 to 15.

Officer-Reported Primary Contributing Cause

No improper driving165 (20.8%)16.2%prior 142
Followed too closely139 (17.5%)28.7%prior 108
Inattention95 (12%)-8.7%prior 104
Failed to yield right of way62 (7.8%)-4.6%prior 65
Failure to keep in proper lane or running off road32 (4%)28.0%prior 25
Other improper action29 (3.7%)81.3%prior 16
Disregarded traffic signs, signals, road markings26 (3.3%)100.0%prior 13
Driving too fast for conditions25 (3.1%)108.3%prior 12
Distracted22 (2.8%)57.1%prior 14
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner22 (2.8%)-37.1%prior 35

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

The distribution of crashes across environmental conditions remained largely stable year-over-year. In both 2021 and 2022, approximately 80% of crashes occurred on dry roads and a majority happened in daylight (64.4% in 2021 and 61.7% in 2022). The proportion of crashes occurring in clear weather conditions was also consistent, accounting for 67.3% of crashes in 2021 and 70.4% in 2022.

Weather

Clear454 (60.5%)
29.7%prior 350
Clear/Clear105 (14.0%)
18.0%prior 89
Cloudy57 (7.6%)
-36.7%prior 90
Rain53 (7.1%)
6.0%prior 50
Cloudy/Rain21 (2.8%)
61.5%prior 13
Snow18 (2.4%)
157.1%prior 7
Rain/Cloudy7 (0.9%)
-12.5%prior 8
Snow/Sleet, hail (freezing rain or drizzle)4 (0.5%)
Clear/Cloudy4 (0.5%)
-20.0%prior 5
Rain/Rain3 (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

Daylight490 (61.9%)
16.7%prior 420
Dark - lighted roadway180 (22.7%)
25.9%prior 143
Dark - roadway not lighted65 (8.2%)
35.4%prior 48
Dusk30 (3.8%)
36.4%prior 22
Dawn22 (2.8%)
46.7%prior 15
Dark - unknown roadway lighting4 (0.5%)
Other1 (0.1%)

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

Road Surface

Dry626 (79.0%)
19.9%prior 522
Wet129 (16.3%)
14.2%prior 113
Snow20 (2.5%)
100.0%prior 10
Ice10 (1.3%)
Slush6 (0.8%)
Water (standing, moving)1 (0.1%)

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 three vehicle makes involved in crashes—Toyota, Honda, and Ford—were identical in both 2021 and 2022, with counts for each increasing in line with the overall crash trend. An analysis of persons involved in crashes shows the share of individuals from the 26-34 age group grew from 19.2% in 2021 to 21.4% in 2022. In contrast, the proportion of persons aged 0-15 decreased from 4.5% to 2.4% of the total.

Top Vehicle Makes (1,563 vehicles)

1
TOYOTA279 (17.9%)
19.7%prior 233
2
HONDA199 (12.7%)
15.7%prior 172
3
FORD157 (10%)
7.5%prior 146
4
NISSAN109 (7%)
12.4%prior 97
5
CHEVROLET107 (6.8%)
4.9%prior 102
6
JEEP84 (5.4%)
7.7%prior 78
7
HYUNDAI54 (3.5%)
25.6%prior 43
8
SUBARU46 (2.9%)
100.0%prior 23
9
VOLKSWAGEN43 (2.8%)
7.5%prior 40
10
LEXUS41 (2.6%)
95.2%prior 21

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

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

Sex Distribution (1,779 persons with recorded sex)

Male1,024 (57.6%)
18.5%prior 864
Female755 (42.4%)
10.4%prior 684

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

Crash distribution by speed limit showed a similar pattern in both years, with 55 mph and 30 mph zones experiencing the highest crash volumes. In 2022, crashes in 55 mph zones increased from 251 to 276, and those in 30 mph zones rose from 194 to 233. Fatal crashes were recorded across a wider range of speed limits in 2022, occurring in 25, 30, 40, and 55 mph zones, whereas in 2021 they were limited to 30 and 55 mph zones.

Fatal crashes by zone: 25 mph: 1 of 57 (1.754%) · 30 mph: 2 of 233 (0.858%) · 40 mph: 1 of 45 (2.222%) · 55 mph: 1 of 276 (0.362%)

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: BRAINTREE, MA
  • Total crash records analyzed: 794
  • Total persons involved: 1,952
  • Total vehicles involved: 1,563

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). "BRAINTREE, 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/braintree/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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Braintree, MA Crash Report — 2022 | ThatCarHitMe.com