Yearly Traffic Safety Analysis

16 CRASHES IN
NEW BRAINTREE, MA
2022

All metrics benchmarked against2021

In 2022, New Braintree recorded 16 total crashes, a 27.3% decrease from the 22 crashes reported in 2021. Despite the overall reduction in collisions, the most significant change was the occurrence of one fatal crash in 2022, whereas there were none in the prior year. This resulted in one fatality and 11 total injuries in 2022, compared to zero fatalities and 10 injuries in 2021.

16

-27.3%was 22

Total Crash Events

1

Persons Killed

11

10.0%was 10

Persons Injured

1

Fatal Crash Events

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.

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 collisions in New Braintree saw a year-over-year decrease, falling 27.3% from 22 crashes in 2021 to 16 in 2022. However, the severity of these incidents increased. Total injuries rose from 10 to 11, and one fatality was recorded in 2022 compared to none the previous year.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

11

Motorists Injured

Prior: 1010.0%

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 timing of crashes shifted between the two periods. In 2022, collisions peaked on Fridays and Sundays with 4 incidents each, a change from 2021 when Wednesdays and Thursdays were the most frequent days with 4 incidents each. The peak hours also changed, moving from several two-crash peaks during morning and midday hours in 2021 to afternoon and evening peaks at 3 p.m. and 6 p.m. in 2022, each with 3 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

Crash severity increased in 2022, with one fatal crash accounting for 6.3% of all incidents, compared to zero fatal crashes in 2021. The share of minor injury crashes decreased from 31.8% in 2021 to 25% in 2022, while the proportion of serious injury crashes increased from 4.5% to 6.3%. Crashes resulting in no injuries represented 62.5% of incidents in 2022, a slight increase from 59.1% in the prior year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes6.3%
Serious Injury1serious injury crashes6.3%
0.0%prior 1
Minor Injury4minor injury crashes25%
-42.9%prior 7
No Injury10no injury crashes62.5%
-23.1%prior 13

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 leading contributing factors for crashes shifted significantly year-over-year. In 2021, 'No improper driving' was the most cited factor with a count of 9 crashes, but this count dropped to 2 in 2022. Conversely, crashes attributed to 'Swerving or avoiding' increased from a count of 1 to 3, becoming the top factor in 2022. 'Fatigued/asleep' was cited in 2 crashes in 2022 after not being a factor in the prior year's data.

Officer-Reported Primary Contributing Cause

Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (18.8%)
No improper driving2 (12.5%)-77.8%prior 9
Failed to yield right of way2 (12.5%)
Driving too fast for conditions2 (12.5%)
Fatigued/asleep2 (12.5%)
Failure to keep in proper lane or running off road1 (6.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (6.3%)
Physical impairment1 (6.3%)
Disregarded traffic signs, signals, road markings1 (6.3%)

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

While clear weather and dry roads were the most common conditions in both periods, the proportion of crashes in adverse conditions increased in 2022. Crashes on wet, icy, slushy, or snowy roads accounted for 37.5% of the total in 2022, up from 27.3% in 2021. Similarly, collisions in dark conditions rose from a 27.3% share in 2021 to a 37.5% share in 2022.

Weather

Clear9 (56.3%)
-43.8%prior 16
Sleet, hail (freezing rain or drizzle)2 (12.5%)
Cloudy/Rain1 (6.3%)
Rain1 (6.3%)
Snow/Blowing sand, snow1 (6.3%)
Fog, smog, smoke/Clear1 (6.3%)
Cloudy1 (6.3%)

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

Lighting

Daylight9 (56.3%)
-35.7%prior 14
Dark - roadway not lighted5 (31.3%)
-16.7%prior 6
Dark - lighted roadway1 (6.3%)
Dusk1 (6.3%)

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

Road Surface

Dry10 (62.5%)
-37.5%prior 16
Wet3 (18.8%)
Ice1 (6.3%)
Slush1 (6.3%)
Snow1 (6.3%)

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

Vehicles & Demographics

Top Vehicle Makes (22 vehicles)

1
FORD4 (18.2%)
2
HONDA3 (13.6%)
3
SUBARU3 (13.6%)
4
JEEP3 (13.6%)
5
TOYOTA2 (9.1%)
6
CHEVROLET2 (9.1%)
-60.0%prior 5
7
GMC1 (4.5%)
8
MACK1 (4.5%)
9
MAZDA1 (4.5%)
10
DODGE1 (4.5%)

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

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

Sex Distribution (30 persons with recorded sex)

Male17 (56.7%)
-5.6%prior 18
Female13 (43.3%)
-18.8%prior 16

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 distribution of crashes across speed zones changed between the two years. In 2021, the majority of crashes (13 of 22) occurred in 40 mph zones. In 2022, the focus shifted to higher speed zones, with 8 of 15 recorded-speed crashes happening in 45 mph zones. The single fatal crash in 2022 occurred in a 35 mph zone, a speed limit that accounted for only one crash in each period.

Fatal crashes by zone: 35 mph: 1 of 1 (100%)

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: NEW BRAINTREE, MA
  • Total crash records analyzed: 16
  • Total persons involved: 30
  • Total vehicles involved: 22

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). "NEW 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/new-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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New Braintree, MA Crash Report — 2022 | ThatCarHitMe.com