Monthly Traffic Safety Analysis

134 CRASHES IN
NEWTON, MA
NOVEMBER 2022

All metrics benchmarked againstNovember 2021

In November 2022, the city of NEWTON experienced a decrease in total crashes, with 134 incidents compared to 161 in November 2021, marking a 16.8% reduction. This period saw a notable increase in bicycle crashes, which rose from 2 to 7 year-over-year.

134

-16.8%was 161

Total Crash Events

0

Persons Killed

35

-27.1%was 48

Persons Injured

14

-17.6%was 17

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 6 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for total crashes in November is falling, with a decrease from 161 crashes in November 2021 to 134 crashes in November 2022. This represents a 16.8% reduction in total crash incidents year-over-year.

14

Hit-and-Run Crashes — November 2022

-17.6% vs prior (17)

Hit-and-run crashes decreased from 17 in November 2021 to 14 in November 2022. The hit-and-run crash rate also saw a slight decrease from 10.6% in the prior period to 10.4% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 20.0%

7

Cyclists Injured

Prior: 2250.0%

25

Motorists Injured

Prior: 44-43.2%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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 Wednesday, with 34 incidents in the prior period, to Thursday, with 30 incidents in the current period. Similarly, the peak hour for crashes moved from 2 PM, which had 20 crashes in November 2021, to 5 PM, with 17 crashes in November 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either November 2021 or November 2022. Serious injury crashes increased from 2 (1.2% of total crashes) to 3 (2.2% of total crashes) year-over-year. Possible injury crashes saw a significant decrease, dropping from 14 (8.7% of total crashes) to 5 (3.7% of total crashes).

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes2.2%
50.0%prior 2
Minor Injury22minor injury crashes16.4%
-4.3%prior 23
Possible Injury5possible injury crashes3.7%
-64.3%prior 14
No Injury98no injury crashes73.1%
-14.0%prior 114

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "No improper driving" saw a slight increase from 32 to 33 incidents. "Followed too closely" decreased substantially from 18 crashes in the prior period to 7 crashes in the current period, a 61.1% reduction in count. Conversely, crashes due to "Failed to yield right of way" increased from 4 to 7, representing a 75% rise in count.

Officer-Reported Primary Contributing Cause

No improper driving33 (24.6%)3.1%prior 32
Inattention27 (20.1%)-3.6%prior 28
Followed too closely7 (5.2%)-61.1%prior 18
Failed to yield right of way7 (5.2%)
Failure to keep in proper lane or running off road6 (4.5%)-14.3%prior 7
Driving too fast for conditions4 (3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (3%)-20.0%prior 5
Over-correcting/over-steering3 (2.2%)
Disregarded traffic signs, signals, road markings2 (1.5%)
Distracted2 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under clear weather conditions decreased from 120 in the prior period to 95 in the current period. Incidents on dry road surfaces also saw a reduction, from 141 to 122 crashes. Crashes during daylight hours decreased from 93 to 79 year-over-year.

Weather

Clear95 (70.9%)
-20.8%prior 120
Cloudy15 (11.2%)
-25.0%prior 20
Clear/Clear13 (9.7%)
85.7%prior 7
Rain4 (3.0%)
-20.0%prior 5
Cloudy/Cloudy3 (2.2%)
Rain/Fog, smog, smoke2 (1.5%)
Rain/Sleet, hail (freezing rain or drizzle)1 (0.7%)
Cloudy/Rain1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash

Lighting

Daylight79 (59.4%)
-15.1%prior 93
Dark - lighted roadway43 (32.3%)
-8.5%prior 47
Dusk8 (6.0%)
Dark - roadway not lighted2 (1.5%)
-83.3%prior 12
Dawn1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field

Road Surface

Dry122 (91.0%)
-13.5%prior 141
Wet12 (9.0%)
-33.3%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field

Vehicles & Demographics

Honda moved from the second most involved vehicle make with 41 incidents to the first with 36, while Toyota dropped from first (42 incidents) to second (30 incidents). The 0-15 age group experienced a notable increase in persons involved in crashes, rising from 11 to 26. Conversely, the 26-34 age group saw a significant decrease from 65 to 36 persons involved.

Top Vehicle Makes (243 vehicles)

1
HONDA36 (14.8%)
-12.2%prior 41
2
TOYOTA30 (12.3%)
-28.6%prior 42
3
FORD21 (8.6%)
-44.7%prior 38
4
NISSAN16 (6.6%)
14.3%prior 14
5
SUBARU16 (6.6%)
23.1%prior 13
6
JEEP14 (5.8%)
7.7%prior 13
7
BMW12 (4.9%)
100.0%prior 6
8
VOLVO10 (4.1%)
9
CHEVROLET10 (4.1%)
-50.0%prior 20
10
LEXUS9 (3.7%)
50.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records

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

Sex Distribution (291 persons with recorded sex)

Female153 (52.6%)
14.2%prior 134
Male138 (47.4%)
-25.4%prior 185

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone decreased from 65 to 56 incidents. Conversely, crashes in the 30 mph zone increased from 30 to 45 incidents. The 55 mph speed zone experienced a significant reduction in crashes, dropping from 31 to 13 incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-11-01 through 2022-11-30 (30 days)
  • Geographic scope: NEWTON, MA
  • Total crash records analyzed: 134
  • Total persons involved: 317
  • Total vehicles involved: 243

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). "NEWTON, MA Crash Intelligence Report: November 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/newton/november-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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Newton, MA Crash Report — November 2022 | ThatCarHitMe.com