Monthly Traffic Safety Analysis

28 CRASHES IN
BELMONT, MA
SEPTEMBER 2022

All metrics benchmarked againstSeptember 2021

Total crashes in Belmont increased by 55.56% from 18 in September 2021 to 28 in September 2022. Despite this increase in crash volume, total injuries decreased by 55.56%, falling from 9 to 4 over the same period. Fatalities remained at zero in both months.

28

55.6%was 18

Total Crash Events

0

Persons Killed

4

-55.6%was 9

Persons Injured

5

25.0%was 4

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant increase in total crashes, rising by 55.56% from 18 in September 2021 to 28 in September 2022. Conversely, total injuries saw a substantial decrease of 55.56%, dropping from 9 to 4. There were no fatalities reported in either period.

5

Hit-and-Run Crashes — September 2022

25.0% vs prior (4)

The number of hit-and-run crashes increased from 4 in September 2021 to 5 in September 2022. Despite this increase in count, the hit-and-run crash rate decreased from 22.2% in the prior period to 17.9% in the current period, relative to the total number of crashes.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 2-50.0%

2

Motorists Injured

Prior: 7-71.4%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Wednesday in both periods, with 7 crashes in September 2022 compared to 6 in September 2021. However, the peak hour shifted from 6 p.m. with 3 crashes in September 2021 to 10 a.m. with 4 crashes in September 2022. Notably, crashes on Fridays increased from 0 to 6, and on Saturdays from 1 to 4.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity shifted, with total injuries decreasing from 9 in September 2021 to 4 in September 2022. Serious injuries, which accounted for 1 crash (5.6% share) in the prior period, were absent in the current period. Minor injuries decreased from 4 to 2, while crashes with no injuries increased from 9 to 22, changing the proportion of injury-involved crashes from 38.9% to 14.3%.

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes7.1%
-50.0%prior 4
Possible Injury2possible injury crashes7.1%
0.0%prior 2
No Injury22no injury crashes78.6%
144.4%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Most severe injury per crash record

Top Contributing Factors

The most frequent contributing factor in September 2022 was 'Failed to yield right of way,' accounting for 9 crashes (32.1% share), a 200% increase from 3 crashes (16.7% share) in the prior year. 'No improper driving' decreased by 2 crashes, from 5 (27.8% share) to 3 (10.7% share). Speeding-related crashes, which were 0 in September 2021, increased to 1 in September 2022.

Officer-Reported Primary Contributing Cause

Failed to yield right of way9 (32.1%)
Inattention3 (10.7%)
No improper driving3 (10.7%)-40.0%prior 5
Failure to keep in proper lane or running off road2 (7.1%)
Other improper action1 (3.6%)
Glare1 (3.6%)
Driving too fast for conditions1 (3.6%)
Followed too closely1 (3.6%)
Distracted1 (3.6%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Daylight' conditions increased significantly from 13 in September 2021 to 26 in September 2022. Similarly, crashes on 'Dry' road surfaces increased from 16 to 24, and those in 'Clear' weather conditions rose from 11 to 16. The number of crashes occurring at 'Dusk' decreased from 2 to 0.

Weather

Clear16 (57.1%)
45.5%prior 11
Clear/Clear5 (17.9%)
Cloudy2 (7.1%)
Rain2 (7.1%)
Cloudy/Cloudy1 (3.6%)
Cloudy/Rain1 (3.6%)
Cloudy/Unknown1 (3.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Weather condition at time of crash

Lighting

Daylight26 (92.9%)
100.0%prior 13
Dark - lighted roadway2 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Lighting condition field

Road Surface

Dry24 (85.7%)
50.0%prior 16
Wet4 (14.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (49 vehicles)

1
TOYOTA9 (18.4%)
50.0%prior 6
2
HONDA7 (14.3%)
3
FORD6 (12.2%)
4
JEEP3 (6.1%)
5
BMW3 (6.1%)
6
TESL2 (4.1%)
7
ISU2 (4.1%)
8
TESL SUV WHITE2 (4.1%)
9
MACK1 (2%)
10
MAZDA1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Vehicle unit records

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

Sex Distribution (50 persons with recorded sex)

Male27 (54.0%)
17.4%prior 23
Female23 (46.0%)
91.7%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 25 mph speed zones increased from 16 in September 2021 to 26 in September 2022. Crashes in 30 mph speed zones decreased from 2 to 1. A new speed zone, 45 mph, recorded 1 crash in September 2022, which was not present in the prior period's data. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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: 2022-09-01 through 2022-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-09-01 through 2022-09-30 (30 days)
  • Geographic scope: BELMONT, MA
  • Total crash records analyzed: 28
  • Total persons involved: 57
  • Total vehicles involved: 49

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). "BELMONT, MA Crash Intelligence Report: September 2022." Published June 21, 2026. Reporting period: 2022-09-01 to 2022-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/belmont/september-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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Belmont, MA Crash Report — September 2022 | ThatCarHitMe.com