Yearly Traffic Safety Analysis

347 CRASHES IN
SANDWICH, MA
2022

All metrics benchmarked against2021

In Sandwich, total traffic crashes increased by 9.8%, from 316 in 2021 to 347 in 2022. Total injuries rose slightly from 82 to 86, while fatalities remained constant at one death in each period. The most notable year-over-year shift was in contributing factors, where crashes attributed to 'Inattention' decreased by 23.3% in count, while those with 'No improper driving' cited increased by 26.8%, becoming the new leading factor.

347

9.8%was 316

Total Crash Events

1

Persons Killed

86

4.9%was 82

Persons Injured

13

8.3%was 12

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. 4 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 crashes in Sandwich trended upward year-over-year. The total number of incidents rose from 316 in 2021 to 347 in 2022, representing a 9.8% increase. While the number of fatalities was unchanged at one, the total number of persons injured increased from 82 to 86.

13

Hit-and-Run Crashes — 2022

8.3% vs prior (12)

Hit-and-run incidents remained relatively stable, with the total count increasing by one from 12 crashes in 2021 to 13 in 2022. Despite the minor increase in the number of events, the hit-and-run rate as a percentage of all crashes saw a slight decrease from 3.8% to 3.7% year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 10.0%

3

Pedestrians Injured

Prior: 1200.0%

3

Cyclists Injured

Prior: 30.0%

80

Motorists Injured

Prior: 782.6%

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 timing of crashes shifted between the two periods. The peak day for crashes moved from Wednesday (52 incidents) in 2021 to Friday (55 incidents) in 2022. A more pronounced change occurred in the peak hour, which shifted from 11 a.m. (30 crashes) in the prior year to the 4 p.m. hour (33 crashes) in the current year.

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

The number of fatal crashes remained stable at one in both 2021 and 2022. However, the distribution of injury severity changed, with serious injury crashes decreasing from 13 to 9. The proportion of collisions resulting in no injuries increased from 75.0% of all crashes in 2021 to 79.5% in 2022.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
0.0%prior 1
Serious Injury9serious injury crashes2.6%
-30.8%prior 13
Minor Injury40minor injury crashes11.5%
17.6%prior 34
Possible Injury17possible injury crashes4.9%
-34.6%prior 26
No Injury276no injury crashes79.5%
16.5%prior 237

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 ranking of top contributing factors changed significantly year-over-year. 'No improper driving' became the most cited factor in 2022, with its count increasing from 56 to 71 incidents. In contrast, 'Inattention' dropped from the leading cause in 2021 to the third-ranked factor in 2022, as its count fell from 60 to 46. Crashes involving 'Failed to yield right of way' also increased in count from 42 to 48.

Officer-Reported Primary Contributing Cause

No improper driving71 (20.5%)26.8%prior 56
Failed to yield right of way48 (13.8%)14.3%prior 42
Inattention46 (13.3%)-23.3%prior 60
Followed too closely40 (11.5%)-2.4%prior 41
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner20 (5.8%)-9.1%prior 22
Failure to keep in proper lane or running off road15 (4.3%)15.4%prior 13
Other improper action13 (3.7%)85.7%prior 7
Driving too fast for conditions10 (2.9%)-9.1%prior 11
Distracted10 (2.9%)-9.1%prior 11
Fatigued/asleep9 (2.6%)

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 in clear weather and on dry roads compared to the prior year. The share of crashes in clear weather increased from 68.7% to 74.4%, while the share on dry roads grew from 79.4% to 82.1%. Conversely, the proportion of crashes occurring in dark, unlit roadway conditions rose from 15.8% in 2021 to 18.2% in 2022.

Weather

Clear258 (75.2%)
18.9%prior 217
Cloudy36 (10.5%)
-18.2%prior 44
Rain15 (4.4%)
-34.8%prior 23
Snow9 (2.6%)
80.0%prior 5
Cloudy/Rain9 (2.6%)
50.0%prior 6
Clear/Unknown3 (0.9%)
Snow/Sleet, hail (freezing rain or drizzle)2 (0.6%)
Snow/Blowing sand, snow2 (0.6%)
Other1 (0.3%)
Cloudy/Snow1 (0.3%)

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

Lighting

Daylight242 (69.7%)
6.6%prior 227
Dark - roadway not lighted63 (18.2%)
26.0%prior 50
Dark - lighted roadway25 (7.2%)
-19.4%prior 31
Dusk15 (4.3%)
114.3%prior 7
Dawn1 (0.3%)
Other1 (0.3%)

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

Road Surface

Dry285 (82.1%)
13.5%prior 251
Wet39 (11.2%)
-26.4%prior 53
Snow12 (3.5%)
71.4%prior 7
Ice10 (2.9%)
Slush1 (0.3%)

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—Toyota, Ford, and Honda—retained their rankings, with the number of Toyotas involved increasing from 94 to 112. A notable demographic shift occurred among persons involved in crashes, as the count of individuals in the 0-15 age group nearly doubled from 66 in 2021 to 124 in 2022. The number of people in the 21-25 age group also increased from 72 to 99.

Top Vehicle Makes (615 vehicles)

1
TOYOTA112 (18.2%)
19.1%prior 94
2
FORD72 (11.7%)
0.0%prior 72
3
HONDA58 (9.4%)
0.0%prior 58
4
CHEVROLET42 (6.8%)
5.0%prior 40
5
JEEP41 (6.7%)
7.9%prior 38
6
NISSAN30 (4.9%)
-25.0%prior 40
7
SUBARU27 (4.4%)
-3.6%prior 28
8
GMC23 (3.7%)
4.5%prior 22
9
BMW16 (2.6%)
100.0%prior 8
10
HYUNDAI14 (2.3%)
0.0%prior 14

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

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

Sex Distribution (818 persons with recorded sex)

Male461 (56.4%)
23.3%prior 374
Female357 (43.6%)
10.2%prior 324

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

The location of crashes shifted to higher speed zones in 2022. The 40 mph zone became the most frequent site for crashes with 99 incidents, up from 62 in the prior year. Concurrently, crashes in 30 mph zones decreased from 102 to 74. The single fatal crash of 2022 occurred in a 45 mph zone, whereas the 2021 fatality was in a 55 mph zone.

Fatal crashes by zone: 45 mph: 1 of 43 (2.326%)

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: SANDWICH, MA
  • Total crash records analyzed: 347
  • Total persons involved: 873
  • Total vehicles involved: 615

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). "SANDWICH, 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/sandwich/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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Sandwich, MA Crash Report — 2022 | ThatCarHitMe.com