Monthly Traffic Safety Analysis

37 CRASHES IN
SHARON, MA
OCTOBER 2022

All metrics benchmarked againstOctober 2021

Total crashes in Sharon, MA, decreased slightly from 38 in October 2021 to 37 in October 2022, representing a 2.63% reduction. Despite this minor decrease in overall incidents, the number of total injuries rose significantly by 61.54%, from 13 to 21 individuals injured year-over-year.

37

-2.6%was 38

Total Crash Events

0

Persons Killed

21

61.5%was 13

Persons Injured

1

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. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend shows a slight decrease in total crashes, falling from 38 in October 2021 to 37 in October 2022. This represents a 2.63% reduction in crash events year-over-year, indicating a relatively stable crash volume.

1

Hit-and-Run Crashes — October 2022

2.7% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

21

Motorists Injured

Prior: 1361.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Sunday in October 2021, with 10 incidents, to Friday in October 2022, also with 10 incidents. The peak crash hour remained consistent at 4 PM for both periods, recording 4 crashes in October 2021 and 5 crashes in October 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

No fatalities were reported in either October 2021 or October 2022. However, total injuries increased from 13 in October 2021 to 21 in October 2022, a 61.54% rise. Notably, serious injuries, which accounted for 2 incidents in the prior period, were absent in the current period, while minor injuries increased from 4 to 10.

Outcome by Severity (Crash Events)

Minor Injury10minor injury crashes27%
150.0%prior 4
Possible Injury4possible injury crashes10.8%
0.0%prior 4
No Injury20no injury crashes54.1%
-28.6%prior 28

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Followed too closely' increased significantly by 80% in count, from 5 crashes in October 2021 to 9 in October 2022. Conversely, 'Failed to yield right of way' crashes decreased by 50% in count, from 4 to 2, and 'Driving too fast for conditions' crashes decreased by 66.7% in count, from 3 to 1. Additionally, 'Failure to keep in proper lane or running off road' crashes increased by 200% in count, from 1 to 3.

Officer-Reported Primary Contributing Cause

Followed too closely9 (24.3%)80.0%prior 5
No improper driving9 (24.3%)28.6%prior 7
Failure to keep in proper lane or running off road3 (8.1%)
Other improper action3 (8.1%)
Fatigued/asleep2 (5.4%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (5.4%)
Failed to yield right of way2 (5.4%)
Inattention2 (5.4%)
Driving too fast for conditions1 (2.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring during daylight hours increased from 18 in October 2021 to 25 in October 2022. Conversely, incidents in dark conditions (lighted or unlighted roadways combined) decreased from 18 to 10 year-over-year. Crashes on wet road surfaces also decreased from 14 to 8, while those on dry road surfaces increased from 24 to 29.

Weather

Clear21 (56.8%)
5.0%prior 20
Cloudy5 (13.5%)
-16.7%prior 6
Clear/Other3 (8.1%)
Rain3 (8.1%)
-40.0%prior 5
Clear/Unknown2 (5.4%)
Rain/Cloudy2 (5.4%)
Cloudy/Rain1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Weather condition at time of crash

Lighting

Daylight25 (67.6%)
38.9%prior 18
Dark - roadway not lighted7 (18.9%)
-22.2%prior 9
Dark - lighted roadway3 (8.1%)
-66.7%prior 9
Dawn1 (2.7%)
Dusk1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Lighting condition field

Road Surface

Dry29 (78.4%)
20.8%prior 24
Wet8 (21.6%)
-42.9%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes remained stable, with 65 in October 2021 and 64 in October 2022. Toyota and Honda maintained their positions as the top two vehicle makes involved in crashes for both periods. A notable shift in persons involved in crashes was observed in younger age groups, with those aged 0-15 increasing from 2 to 8, and 16-20 increasing from 6 to 13.

Top Vehicle Makes (64 vehicles)

1
TOYOTA9 (14.1%)
0.0%prior 9
2
HONDA9 (14.1%)
12.5%prior 8
3
FORD6 (9.4%)
0.0%prior 6
4
NISSAN6 (9.4%)
20.0%prior 5
5
MAZDA4 (6.3%)
6
KIA4 (6.3%)
7
JEEP4 (6.3%)
-33.3%prior 6
8
CHEVROLET3 (4.7%)
-40.0%prior 5
9
SUBARU3 (4.7%)
10
AUDI2 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Vehicle unit records

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

Sex Distribution (79 persons with recorded sex)

Male49 (62.0%)
0.0%prior 49
Female30 (38.0%)
36.4%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 mph zones decreased from 13 in October 2021 to 10 in October 2022. Crashes occurring in 65 mph zones also saw a slight decrease from 10 to 9. Conversely, crashes in 25 mph zones increased from 6 to 7. No fatal crashes were reported across any speed zones in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · 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: 2022-10-01 through 2022-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-10-01 through 2022-10-31 (31 days)
  • Geographic scope: SHARON, MA
  • Total crash records analyzed: 37
  • Total persons involved: 85
  • Total vehicles involved: 64

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). "SHARON, MA Crash Intelligence Report: October 2022." Published June 21, 2026. Reporting period: 2022-10-01 to 2022-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/sharon/october-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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Sharon, MA Crash Report — October 2022 | ThatCarHitMe.com