Monthly Traffic Safety Analysis

12 CRASHES IN
WINCHESTER, MA
MARCH 2022

All metrics benchmarked againstMarch 2021

In March 2022, Winchester recorded 12 crashes, marking a 20% increase compared to the 10 crashes reported in March 2021. Concurrently, total injuries rose from 3 to 4, representing a 33.3% increase year-over-year. A notable shift includes the reporting of one serious injury crash in the current period, which was not observed in the prior year.

12

20.0%was 10

Total Crash Events

0

Persons Killed

4

33.3%was 3

Persons Injured

0

Fatal Crash Events

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 · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Winchester show an upward trend year-over-year, with total crashes increasing by 20% from 10 in March 2021 to 12 in March 2022. This rise in crash frequency was accompanied by a 33.3% increase in total injuries, from 3 to 4, indicating a worsening safety trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 333.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak day moving from Saturday, which had 3 crashes in March 2021, to Monday, which recorded 4 crashes in March 2022. The peak crash hour also changed significantly, from 4 p.m. with 2 crashes in the prior period to 8 a.m. with 3 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both March 2021 and March 2022. However, the total number of injury crashes increased from 3 in the prior period to 4 in the current period. Notably, the current period reported one serious injury crash (Code A), a severity level not present in the prior year's data.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes8.3%
Minor Injury1minor injury crashes8.3%
-50.0%prior 2
Possible Injury2possible injury crashes16.7%
100.0%prior 1
No Injury8no injury crashes66.7%
14.3%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record

Top Contributing Factors

Among common contributing factors, 'No improper driving' increased from 1 crash in March 2021 to 3 crashes in March 2022. 'Inattention' also saw an increase, rising from 1 crash to 2 crashes year-over-year. Conversely, 'Failed to yield right of way' decreased from 2 crashes in the prior period to 1 crash in the current period, while 'Followed too closely' remained consistent with 2 crashes in both periods.

Officer-Reported Primary Contributing Cause

No improper driving3 (25%)
Followed too closely2 (16.7%)
Inattention2 (16.7%)
Physical impairment1 (8.3%)
Emotional1 (8.3%)
Failed to yield right of way1 (8.3%)
Failure to keep in proper lane or running off road1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear/Clear' weather decreased from 7 in March 2021 to 3 in March 2022, while crashes in 'Cloudy/Rain' conditions remained at 1 in both periods. Regarding road surface, crashes on 'Dry' surfaces decreased from 8 to 7, but crashes on 'Wet' surfaces tripled from 1 to 3 year-over-year. Both 'Daylight' and 'Dark - lighted roadway' conditions saw a slight increase in crash counts, from 9 to 10 and 1 to 2 respectively.

Weather

Clear/Clear3 (25.0%)
-57.1%prior 7
Clear/Unknown2 (16.7%)
Cloudy/Cloudy1 (8.3%)
Cloudy/Rain1 (8.3%)
Rain/Rain1 (8.3%)
Snow/Clear1 (8.3%)
Clear1 (8.3%)
Snow/Snow1 (8.3%)
Clear/Severe crosswinds1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash

Lighting

Daylight10 (83.3%)
11.1%prior 9
Dark - lighted roadway2 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field

Road Surface

Dry7 (58.3%)
-12.5%prior 8
Wet3 (25.0%)
Other1 (8.3%)
Snow1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (21 vehicles)

1
HONDA5 (23.8%)
2
TOYOTA3 (14.3%)
3
CHEVROLET2 (9.5%)
4
HONDA CIVIC1 (4.8%)
5
JEEP1 (4.8%)
6
JEEP WRANGLER1 (4.8%)
7
KIA1 (4.8%)
8
LEXUS1 (4.8%)
9
MERCEDES-BENZ1 (4.8%)
10
SUBARU1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records

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

Sex Distribution (24 persons with recorded sex)

Male14 (58.3%)
16.7%prior 12
Female10 (41.7%)
0.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones changed between the two periods, with the 30 mph zone experiencing a decrease from 7 crashes in March 2021 to 5 crashes in March 2022. The current period reported 6 crashes in 25 mph zones and 1 crash in 35 mph zones, neither of which were present in the prior year's data. Conversely, the prior period recorded 2 crashes in 20 mph zones, which were not observed in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-03-01 through 2022-03-31 (31 days)
  • Geographic scope: WINCHESTER, MA
  • Total crash records analyzed: 12
  • Total persons involved: 26
  • Total vehicles involved: 21

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). "WINCHESTER, MA Crash Intelligence Report: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/winchester/march-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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Winchester, MA Crash Report — March 2022 | ThatCarHitMe.com