Yearly Traffic Safety Analysis

181 CRASHES IN
WINTHROP, MA
2022

All metrics benchmarked against2021

In 2022, Winthrop recorded 181 total traffic crashes, a 17.5% increase from the 154 crashes reported in 2021. Despite the rise in total incidents, the number of people injured decreased by 28%, from 50 to 36. While there was one fatality in 2021, there were zero fatalities recorded in 2022.

181

17.5%was 154

Total Crash Events

0

-100.0%was 1

Persons Killed

36

-28.0%was 50

Persons Injured

27

42.1%was 19

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. 16 crashes with unreported severity are 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

The overall number of traffic crashes in Winthrop increased by 17.5% from 2021 to 2022, rising from 154 to 181 incidents. However, the outcomes of these crashes became less severe on average. The total number of injuries reported fell by 28%, from 50 in 2021 to 36 in 2022, and fatalities dropped from one to zero.

27

Hit-and-Run Crashes — 2022

42.1% vs prior (19)

The number of hit-and-run crashes increased from 19 in 2021 to 27 in 2022, representing a 42.1% rise in count. The hit-and-run rate, which measures the proportion of total crashes that were hit-and-runs, also trended upward. This rate increased from 12.3% in 2021 to 14.9% in 2022.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

2

Pedestrians Injured

Prior: 6-66.7%

3

Cyclists Injured

Prior: 1200.0%

31

Motorists Injured

Prior: 43-27.9%

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 shifted between the two periods. The day with the most crashes changed from Sunday (29 crashes) in 2021 to Friday (36 crashes) in 2022. The peak hour for incidents also shifted, moving from 2 PM in 2021 (15 crashes) to 12 PM in 2022 (18 crashes).

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 decreased from 2021 to 2022, with the city recording zero fatal crashes, down from one in the prior year. The proportion of crashes resulting in no injuries increased from 63.6% of all crashes in 2021 to 75.1% in 2022. Correspondingly, the share of crashes involving minor injuries fell from 16.2% to 8.8% year-over-year.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.1%
100.0%prior 1
Minor Injury16minor injury crashes8.8%
-36.0%prior 25
Possible Injury11possible injury crashes6.1%
-8.3%prior 12
No Injury136no injury crashes75.1%
38.8%prior 98

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 factor in both years was "No improper driving," for which the crash count increased from 47 in 2021 to 78 in 2022. Crashes attributed to an "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" remained a top factor, with its count holding steady at 10 incidents in 2022 compared to 11 in 2021. The count of incidents involving a "Distracted" driver increased by 50%, from 6 in 2021 to 9 in 2022.

Officer-Reported Primary Contributing Cause

No improper driving78 (43.1%)66.0%prior 47
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner10 (5.5%)-9.1%prior 11
Distracted9 (5%)50.0%prior 6
Inattention8 (4.4%)60.0%prior 5
Other improper action8 (4.4%)0.0%prior 8
Failed to yield right of way5 (2.8%)-16.7%prior 6
Driving too fast for conditions4 (2.2%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (1.7%)-40.0%prior 5
Failure to keep in proper lane or running off road3 (1.7%)
Disregarded traffic signs, signals, road markings2 (1.1%)

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

The distribution of crashes across different conditions remained largely consistent year-over-year, with most incidents in both periods occurring in "Clear" weather on "Dry" roads. In 2022, 82.3% of crashes happened on dry roads, compared to 85.1% in 2021. A notable shift occurred in lighting conditions, as the proportion of crashes during "Daylight" hours increased from 62.3% in 2021 to 66.3% in 2022, while crashes on dark but lighted roadways decreased from 31.2% to 22.6% of the total.

Weather

Clear125 (71.8%)
17.9%prior 106
Clear/Unknown9 (5.2%)
12.5%prior 8
Cloudy7 (4.0%)
40.0%prior 5
Clear/Other6 (3.4%)
Snow5 (2.9%)
Clear/Cloudy4 (2.3%)
-60.0%prior 10
Cloudy/Rain4 (2.3%)
Snow/Blowing sand, snow4 (2.3%)
Snow/Cloudy2 (1.1%)
Rain2 (1.1%)
-66.7%prior 6

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

Lighting

Daylight120 (68.6%)
25.0%prior 96
Dark - lighted roadway41 (23.4%)
-14.6%prior 48
Dusk7 (4.0%)
Dark - roadway not lighted4 (2.3%)
Dawn3 (1.7%)

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

Road Surface

Dry149 (85.1%)
13.7%prior 131
Wet13 (7.4%)
0.0%prior 13
Snow10 (5.7%)
Ice2 (1.1%)
Sand, mud, dirt, oil, gravel1 (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 consistent, with Toyota, Honda, and Ford leading in both 2021 and 2022. There were shifts in the age demographics of persons involved in crashes. While the 26-34 age group was the largest in 2021 with 61 individuals, its count decreased to 46 in 2022. Conversely, involvement for the 45-54 age group increased from 36 to 46 persons, and for the 55-64 group from 32 to 43 persons.

Top Vehicle Makes (333 vehicles)

1
TOYOTA51 (15.3%)
4.1%prior 49
2
HONDA38 (11.4%)
15.2%prior 33
3
FORD32 (9.6%)
-15.8%prior 38
4
NISSAN23 (6.9%)
64.3%prior 14
5
CHEVROLET21 (6.3%)
40.0%prior 15
6
JEEP16 (4.8%)
-15.8%prior 19
7
HYUNDAI15 (4.5%)
15.4%prior 13
8
SUBARU12 (3.6%)
50.0%prior 8
9
GMC10 (3%)
66.7%prior 6
10
KIA7 (2.1%)
-22.2%prior 9

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

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

Sex Distribution (286 persons with recorded sex)

Male177 (61.9%)
16.4%prior 152
Female109 (38.1%)
0.0%prior 109

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

A significant shift occurred in the speed zones where crashes were most frequent. In 2021, the 30 mph zone saw the highest number of crashes at 75, but this number fell to 38 in 2022. Conversely, crashes in the 25 mph zone doubled, increasing from 62 in 2021 to 124 in 2022, making it the most common zone for incidents. The single fatality in 2021 occurred in a 25 mph zone, while 2022 had no fatalities in any speed zone.

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: WINTHROP, MA
  • Total crash records analyzed: 181
  • Total persons involved: 390
  • Total vehicles involved: 333

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). "WINTHROP, 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/winthrop/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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Winthrop, MA Crash Report — 2022 | ThatCarHitMe.com