Monthly Traffic Safety Analysis

21 CRASHES IN
WINCHENDON, MA
JUNE 2023

All metrics benchmarked againstJune 2022

Total crashes decreased from 25 in June 2022 to 21 in June 2023, representing a 16% reduction. The most notable year-over-year shift was the increase in total fatalities from 0 in June 2022 to 1 in June 2023.

21

-16.0%was 25

Total Crash Events

1

Persons Killed

7

-36.4%was 11

Persons Injured

1

Hit-and-Run Crashes

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 · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes decreased by 16%, from 25 in June 2022 to 21 in June 2023. While total injuries decreased by 36.4% from 11 to 7, total fatalities increased from 0 to 1 during the same period.

1

Hit-and-Run Crashes — June 2023

0.0% vs prior (1)

The number of hit-and-run crashes remained stable at 1 for both June 2022 and June 2023. However, due to a decrease in total crashes, the hit-and-run rate slightly increased from 4% in June 2022 to 4.8% in June 2023.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

6

Motorists Injured

Prior: 11-45.5%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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 6 crashes in June 2022 to Saturday, Sunday, Tuesday, and Thursday, each with 4 crashes in June 2023. The peak hour also changed, moving from 5 p.m. with 4 crashes in June 2022 to 6 a.m. with 3 crashes in June 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes increased from 0 in June 2022 to 1 in June 2023, resulting in a fatal rate increase from 0% to 4.76%. Total injuries decreased by 36.4%, from 11 persons injured in June 2022 to 7 persons injured in June 2023. Crashes classified as "Serious Injury" decreased from 2 (8% share) to 0, while "Minor Injury" crashes increased from 2 (8% share) to 5 (23.8% share).

Outcome by Severity (Crash Events)

Fatal1fatal crashes4.8%
Minor Injury5minor injury crashes23.8%
150.0%prior 2
Possible Injury1possible injury crashes4.8%
0.0%prior 1
No Injury14no injury crashes66.7%
-30.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "No improper driving" decreased from 9 in June 2022 to 7 in June 2023, a 22.2% reduction in count. "Failed to yield right of way" crashes decreased from 4 to 3, a 25% reduction in count. Notably, "Inattention" was a factor in 5 crashes (20% share) in June 2022 but was not present in June 2023, while "Driving too fast for conditions" and "Exceeded authorized speed limit" each appeared as factors in 1 crash (4.8% share) in June 2023 but not in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving7 (33.3%)-22.2%prior 9
Failed to yield right of way3 (14.3%)
Disregarded traffic signs, signals, road markings1 (4.8%)
Followed too closely1 (4.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.8%)
Fatigued/asleep1 (4.8%)
Driving too fast for conditions1 (4.8%)
Exceeded authorized speed limit1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Clear" weather decreased from 22 in June 2022 to 11 in June 2023. Conversely, crashes in "Cloudy" weather increased from 1 to 5, and "Wet" road surface crashes increased from 2 to 7. Crashes during "Daylight" decreased from 20 to 15, while those in "Dark - roadway not lighted" increased from 2 to 3.

Weather

Clear11 (52.4%)
-50.0%prior 22
Cloudy5 (23.8%)
Cloudy/Rain2 (9.5%)
Rain2 (9.5%)
Fog, smog, smoke1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash

Lighting

Daylight15 (71.4%)
-25.0%prior 20
Dark - roadway not lighted3 (14.3%)
Dawn2 (9.5%)
Dark - lighted roadway1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field

Road Surface

Dry14 (66.7%)
-39.1%prior 23
Wet7 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (32 vehicles)

1
FORD6 (18.8%)
20.0%prior 5
2
TOYOTA6 (18.8%)
-14.3%prior 7
3
SUBARU5 (15.6%)
4
NISSAN3 (9.4%)
-40.0%prior 5
5
GMC2 (6.3%)
6
HONDA2 (6.3%)
7
VOLKSWAGEN1 (3.1%)
8
FIAT1 (3.1%)
9
WEST1 (3.1%)
10
JEEP1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records

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

Sex Distribution (36 persons with recorded sex)

Female21 (58.3%)
-19.2%prior 26
Male15 (41.7%)
-40.0%prior 25

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes at 15 mph increased from 1 in June 2022 to 3 in June 2023, and crashes at 40 mph increased from 3 to 4. Crashes at 50 mph decreased significantly from 5 to 1. A fatal crash occurred in June 2023 at a 45 mph speed limit, where no crashes were recorded in the prior period.

Fatal crashes by zone: 45 mph: 1 of 2 (50%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-06-01 through 2023-06-30 (30 days)
  • Geographic scope: WINCHENDON, MA
  • Total crash records analyzed: 21
  • Total persons involved: 37
  • Total vehicles involved: 32

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). "WINCHENDON, MA Crash Intelligence Report: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/winchendon/june-2023-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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Winchendon, MA Crash Report — June 2023 | ThatCarHitMe.com