Yearly Traffic Safety Analysis

181 CRASHES IN
WINCHESTER, MA
2022

All metrics benchmarked against2021

In 2022, Winchester recorded 181 total crashes, a 12.4% increase from the 161 crashes reported in 2021. The most significant year-over-year change was the occurrence of two fatal crashes resulting in two fatalities in 2022, whereas no fatalities were recorded in the prior year. Overall injuries also rose from 39 to 44.

181

12.4%was 161

Total Crash Events

2

Persons Killed

44

12.8%was 39

Persons Injured

3

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Winchester show an increase year-over-year. Total crashes rose by 12.4%, from 161 in 2021 to 181 in 2022. Similarly, the number of people injured in these incidents increased from 39 to 44, a 12.8% rise.

3

Hit-and-Run Crashes — 2022

0.0% vs prior (3)

The number of hit-and-run crashes remained unchanged, with three incidents reported in both 2022 and 2021. Due to the overall increase in total crashes in 2022, the hit-and-run rate saw a slight decrease, falling from 1.9% of all crashes in 2021 to 1.7% in 2022.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 0%

2

Pedestrians Injured

Prior: 20.0%

2

Cyclists Injured

Prior: 1100.0%

40

Motorists Injured

Prior: 3514.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed a notable shift between the two periods. In 2022, the peak day for crashes was Wednesday with 37 incidents, while 2021 had a three-way tie for its peak day with 30 crashes each. The peak hour for crashes shifted from 3 p.m. in 2021 (19 crashes) to 8 a.m. in 2022 (22 crashes), indicating a move from the afternoon to the morning commute.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased in 2022, with the city recording two fatal crashes (1.1% of total) after having none in 2021. The number of serious injury crashes also rose from two to three. While the share of minor injury crashes remained stable at around 11%, the proportion of crashes resulting in no injury decreased from 78.9% in 2021 to 77.3% in 2022.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.1%
Serious Injury3serious injury crashes1.7%
50.0%prior 2
Minor Injury20minor injury crashes11%
11.1%prior 18
Possible Injury15possible injury crashes8.3%
25.0%prior 12
No Injury140no injury crashes77.3%
10.2%prior 127

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors shifted between the two years. 'Failed to yield right of way' became the most common factor in 2022, with its incident count increasing by 93% from 14 to 27. Conversely, 'Inattention,' the top factor in 2021 with 17 incidents, decreased to 13 incidents in 2022. Crashes attributed to 'Followed too closely' also saw a significant rise, increasing from 7 to 15 incidents year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving32 (17.7%)-3.0%prior 33
Failed to yield right of way27 (14.9%)92.9%prior 14
Followed too closely15 (8.3%)114.3%prior 7
Inattention13 (7.2%)-23.5%prior 17
Disregarded traffic signs, signals, road markings12 (6.6%)50.0%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner8 (4.4%)14.3%prior 7
Failure to keep in proper lane or running off road6 (3.3%)-50.0%prior 12
Physical impairment5 (2.8%)
Exceeded authorized speed limit4 (2.2%)
Made an improper turn4 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Driving conditions remained broadly similar year-over-year, with the majority of crashes in both periods occurring in daylight and on dry roads. However, there was a notable increase in crashes on wet road surfaces, which rose from 16 incidents in 2021 to 28 in 2022. Crashes on snowy or icy roads remained relatively stable, with 13 incidents in 2021 and 14 in 2022.

Weather

Clear/Clear114 (63.0%)
10.7%prior 103
Rain/Rain12 (6.6%)
140.0%prior 5
Cloudy/Cloudy8 (4.4%)
-20.0%prior 10
Clear/Unknown7 (3.9%)
16.7%prior 6
Snow/Snow6 (3.3%)
-25.0%prior 8
Rain/Cloudy6 (3.3%)
Cloudy/Unknown4 (2.2%)
Clear/Cloudy3 (1.7%)
Unknown/Unknown2 (1.1%)
Clear/Other2 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight127 (70.2%)
11.4%prior 114
Dark - lighted roadway41 (22.7%)
24.2%prior 33
Dusk5 (2.8%)
0.0%prior 5
Dark - roadway not lighted3 (1.7%)
Dark - unknown roadway lighting3 (1.7%)
Dawn2 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry135 (75.0%)
3.8%prior 130
Wet28 (15.6%)
75.0%prior 16
Snow8 (4.4%)
-27.3%prior 11
Ice6 (3.3%)
Slush2 (1.1%)
Other1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained Toyota, Honda, and Ford, though Ford's involvement decreased from 29 vehicles in 2021 to 22 in 2022. The age demographics of persons involved in crashes shifted, with a notable increase in the 55-64 age group (from 43 to 63 people) and the 65+ age group (from 43 to 57 people). Conversely, the number of people aged 16-20 involved in crashes decreased from 50 to 44.

Top Vehicle Makes (331 vehicles)

1
TOYOTA43 (13%)
16.2%prior 37
2
HONDA35 (10.6%)
9.4%prior 32
3
FORD22 (6.6%)
-24.1%prior 29
4
JEEP16 (4.8%)
60.0%prior 10
5
SUBARU16 (4.8%)
6
CHEVROLET15 (4.5%)
0.0%prior 15
7
MERCEDES-BENZ12 (3.6%)
71.4%prior 7
8
LEXUS9 (2.7%)
28.6%prior 7
9
NISSAN9 (2.7%)
-25.0%prior 12
10
HYUNDAI8 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (374 persons with recorded sex)

Male197 (52.7%)
11.3%prior 177
Female177 (47.3%)
14.2%prior 155

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes remained most frequent in 30 mph zones, increasing from 88 incidents in 2021 to 95 in 2022. A significant increase was observed in 25 mph zones, where crashes rose from 31 to 56 year-over-year. The two fatal crashes recorded in 2022 occurred in 30 mph and 35 mph speed zones, whereas no fatal crashes were reported in any speed zone in 2021.

Fatal crashes by zone: 30 mph: 1 of 95 (1.053%) · 35 mph: 1 of 15 (6.667%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: WINCHESTER, MA
  • Total crash records analyzed: 181
  • Total persons involved: 397
  • Total vehicles involved: 331

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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/winchester/2022-annual-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 — 2022 | ThatCarHitMe.com