Monthly Traffic Safety Analysis

17 CRASHES IN
BELCHERTOWN, MA
SEPTEMBER 2022

All metrics benchmarked againstSeptember 2021

In September 2022, BELCHERTOWN experienced 17 crashes, marking a 41.7% increase from the 12 crashes recorded in September 2021. A notable year-over-year shift is the emergence of DUI-related crashes, which increased from 0 to 4, and speeding-related crashes, which increased from 0 to 2.

17

41.7%was 12

Total Crash Events

0

Persons Killed

6

200.0%was 2

Persons Injured

1

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.

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 rise in crash activity year-over-year, with total crashes increasing from 12 in September 2021 to 17 in September 2022. Total injuries also saw a significant increase, rising from 2 to 6 over the same period.

1

Hit-and-Run Crashes — September 2022

5.9% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

5

Motorists Injured

Prior: 2150.0%

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 shifted from Monday (5 crashes) in September 2021 to Sunday (5 crashes) in September 2022. The peak hour remained 5p in both periods, although the crash count at this hour decreased from 4 in the prior year to 3 in the current year, despite an overall increase in crashes.

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

There were no fatalities reported in either September 2021 or September 2022. However, total injuries increased from 2 to 6 year-over-year, with serious injuries (code 'A') appearing in September 2022 with 2 crashes, representing 11.8% of all crashes. The proportion of crashes with no injuries decreased from 83.3% in September 2021 to 64.7% in September 2022.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes11.8%
Minor Injury3minor injury crashes17.6%
50.0%prior 2
Possible Injury1possible injury crashes5.9%
No Injury11no injury crashes64.7%
10.0%prior 10

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 contributing factor 'No improper driving' decreased significantly from 6 crashes in September 2021 to 1 crash in September 2022. 'Inattention' also saw a decrease in count, from 4 crashes to 2 crashes. New contributing factors, such as 'Distracted' (2 crashes) and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' (2 crashes), were observed in September 2022 but not in the prior period's top factors.

Officer-Reported Primary Contributing Cause

Distracted2 (11.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (11.8%)
Inattention2 (11.8%)
Disregarded traffic signs, signals, road markings1 (5.9%)
No improper driving1 (5.9%)-83.3%prior 6
Physical impairment1 (5.9%)
Illness1 (5.9%)
Driving too fast for conditions1 (5.9%)
Failed to yield right of way1 (5.9%)
Failure to keep in proper lane or running off road1 (5.9%)

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 on 'Wet' road surfaces increased from 1 in September 2021 to 5 in September 2022. Similarly, crashes under 'Rain' weather conditions increased from 1 to 3. Crashes during 'Daylight' conditions increased from 8 to 11, while crashes in 'Dark - roadway not lighted' conditions increased from 1 to 3 year-over-year.

Weather

Clear10 (62.5%)
-9.1%prior 11
Rain3 (18.8%)
Cloudy2 (12.5%)
Cloudy/Rain1 (6.3%)

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

Lighting

Daylight11 (64.7%)
37.5%prior 8
Dark - roadway not lighted3 (17.6%)
Dark - lighted roadway2 (11.8%)
Dusk1 (5.9%)

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

Road Surface

Dry12 (70.6%)
9.1%prior 11
Wet5 (29.4%)

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 (20 vehicles)

1
VOLKSWAGEN3 (15%)
2
DODGE2 (10%)
3
JEEP2 (10%)
4
HONDA2 (10%)
-75.0%prior 8
5
HYUNDAI2 (10%)
6
MAZDA2 (10%)
7
TOYOTA2 (10%)
8
FRHT1 (5%)
9
HD1 (5%)
10
MITS1 (5%)

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

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

Sex Distribution (29 persons with recorded sex)

Male15 (51.7%)
7.1%prior 14
Female13 (44.8%)
-7.1%prior 14
X / Unspecified1 (3.4%)

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

No fatal crashes were reported in any speed zone for either period. Crashes in the 20 mph zone increased from 1 to 3, and crashes in the 30 mph zone increased from 4 to 5. The 45 mph zone also saw an increase from 1 to 2 crashes, with a new crash reported in a 15 mph zone in September 2022.

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: BELCHERTOWN, MA
  • Total crash records analyzed: 17
  • Total persons involved: 29
  • Total vehicles involved: 20

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). "BELCHERTOWN, 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/belchertown/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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Belchertown, MA Crash Report — September 2022 | ThatCarHitMe.com