Yearly Traffic Safety Analysis

113 CRASHES IN
SOUTHWICK, MA
2022

All metrics benchmarked against2021

In 2022, Southwick recorded 113 total crashes, a 19.3% decrease from the 140 crashes reported in 2021. Despite this overall reduction in collisions, the most significant year-over-year change was the occurrence of 3 fatalities in 2022, whereas none were recorded in the prior year.

113

-19.3%was 140

Total Crash Events

3

Persons Killed

31

-29.5%was 44

Persons Injured

10

42.9%was 7

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 7 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

Overall traffic collisions in Southwick saw a downward trend, with total crashes decreasing by 19.3% from 140 in 2021 to 113 in 2022. The number of reported injuries also declined by 29.5%, from 44 to 31. However, this trend did not extend to crash severity, as the city recorded 3 fatalities in 2022 after having zero in the previous year.

10

Hit-and-Run Crashes — 2022

42.9% vs prior (7)

The number of hit-and-run incidents increased in 2022 compared to the previous year. There were 10 hit-and-run crashes recorded, up from 7 in 2021, which is a 42.9% increase in count. Consequently, the hit-and-run rate as a percentage of total crashes rose from 5.0% in 2021 to 8.8% in 2022.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 0%

1

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 0%

29

Motorists Injured

Prior: 44-34.1%

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 years. While Saturday was a peak day in both 2021 (26 crashes) and 2022 (25 crashes), the daily distribution changed, with crashes on Tuesdays falling from 26 to 7. The peak hour for collisions moved from 2 p.m. in 2021 (18 crashes) to 12 p.m. in 2022 (13 crashes), indicating a shift from the afternoon to the midday period.

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 worsened in 2022 despite a lower overall crash volume. The city recorded 3 fatal crashes, accounting for 2.7% of all collisions, a significant increase from zero fatal crashes in 2021. While the share of crashes resulting in minor or possible injuries decreased from 23.6% to 21.2%, 2022 saw the addition of 2 serious injury crashes, a category not present in the 2021 data.

Outcome by Severity (Crash Events)

Fatal3fatal crashes2.7%
Serious Injury2serious injury crashes1.8%
Minor Injury17minor injury crashes15%
-34.6%prior 26
Possible Injury5possible injury crashes4.4%
-28.6%prior 7
No Injury79no injury crashes69.9%
-21.8%prior 101

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 for crashes shifted between 2021 and 2022. 'Inattention,' the top factor in 2021 with 25 incidents, saw its count drop by 56% to 11 incidents in 2022. Conversely, the count of crashes attributed to 'Driving too fast for conditions' increased by 71.4%, from 7 incidents in 2021 to 12 in 2022. 'Failed to yield right of way' remained a top factor in both years, though its count decreased from 17 to 14.

Officer-Reported Primary Contributing Cause

No improper driving24 (21.2%)4.3%prior 23
Failed to yield right of way14 (12.4%)-17.6%prior 17
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner12 (10.6%)-14.3%prior 14
Driving too fast for conditions12 (10.6%)71.4%prior 7
Inattention11 (9.7%)-56.0%prior 25
Followed too closely10 (8.8%)-9.1%prior 11
Failure to keep in proper lane or running off road9 (8%)0.0%prior 9
Distracted6 (5.3%)
Visibility obstructed3 (2.7%)
Over-correcting/over-steering2 (1.8%)

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

Crashes in 2022 were more likely to occur on non-dry road surfaces compared to the prior year. The proportion of collisions on wet, snow, or ice-covered roads increased from 22.1% of crashes in 2021 to 31.9% in 2022. While most crashes in both years occurred in daylight, there was a notable increase in crashes on dark, unlighted roadways, which rose from 6 incidents in 2021 to 15 in 2022.

Weather

Clear71 (64.0%)
-27.6%prior 98
Cloudy10 (9.0%)
-37.5%prior 16
Sleet, hail (freezing rain or drizzle)8 (7.2%)
Rain6 (5.4%)
0.0%prior 6
Snow5 (4.5%)
-28.6%prior 7
Cloudy/Rain3 (2.7%)
Clear/Cloudy2 (1.8%)
Snow/Sleet, hail (freezing rain or drizzle)2 (1.8%)
Rain/Fog, smog, smoke1 (0.9%)
Snow/Cloudy1 (0.9%)

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

Lighting

Daylight74 (67.3%)
-25.3%prior 99
Dark - roadway not lighted15 (13.6%)
150.0%prior 6
Dark - lighted roadway14 (12.7%)
-48.1%prior 27
Dusk7 (6.4%)
0.0%prior 7

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

Road Surface

Dry74 (67.3%)
-32.1%prior 109
Wet16 (14.5%)
0.0%prior 16
Snow10 (9.1%)
-9.1%prior 11
Ice8 (7.3%)
Slush2 (1.8%)

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 vehicle makes involved in crashes remained consistent, with Ford, Toyota, Honda, and Chevrolet leading in both periods, though involvement counts for each decreased in 2022. An analysis of persons involved shows a demographic shift, with a lower proportion of individuals in the 16-20 age group (13.2% in 2022 vs. 17.5% in 2021) and the 65+ age group (12.3% vs. 16.0%). The 55-64 age group's representation increased from 10.4% of persons involved in 2021 to 14.1% in 2022.

Top Vehicle Makes (184 vehicles)

1
FORD25 (13.6%)
-26.5%prior 34
2
TOYOTA17 (9.2%)
-41.4%prior 29
3
HONDA13 (7.1%)
-45.8%prior 24
4
CHEVROLET13 (7.1%)
-56.7%prior 30
5
SUBARU12 (6.5%)
20.0%prior 10
6
NISSAN12 (6.5%)
-20.0%prior 15
7
HYUNDAI12 (6.5%)
50.0%prior 8
8
JP9 (4.9%)
80.0%prior 5
9
DODGE7 (3.8%)
40.0%prior 5
10
MERCEDES-BENZ6 (3.3%)

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

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

Sex Distribution (201 persons with recorded sex)

Male107 (53.2%)
-32.7%prior 159
Female94 (46.8%)
3.3%prior 91

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

While the 35 MPH speed zone accounted for the most crashes in both years, its share of collisions decreased from 64.2% in 2021 to 51.4% in 2022. There was a corresponding increase in the number of crashes in higher speed zones, with collisions in 45 MPH zones more than doubling from 5 to 11. Notably, 2022 saw two fatal crashes in posted speed zones—one in a 30 MPH zone and one in a 45 MPH zone—whereas no fatal crashes were recorded in any speed zone in 2021.

Fatal crashes by zone: 30 mph: 1 of 8 (12.5%) · 45 mph: 1 of 11 (9.091%)

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: SOUTHWICK, MA
  • Total crash records analyzed: 113
  • Total persons involved: 220
  • Total vehicles involved: 184

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). "SOUTHWICK, 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/southwick/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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Southwick, MA Crash Report — 2022 | ThatCarHitMe.com