ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SHARON, MA · 2023
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/sharon/2023-annual-report
Yearly Traffic Safety Analysis
387 CRASHES IN
SHARON, MA
2023
In 2023, Sharon recorded 387 total traffic crashes, a 1.3% decrease from the 392 crashes reported in 2022. While the overall number of collisions remained relatively stable, there was a notable year-over-year reduction in crash severity. The number of fatalities fell from 5 to 2, and total injuries decreased from 177 to 137.
387
▼ -1.3%was 392
Total Crash Events
2
▼ -60.0%was 5
Persons Killed
137
▼ -22.6%was 177
Persons Injured
17
▼ -10.5%was 19
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. 16 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crash incidents in Sharon showed a slight decline year-over-year, with 387 crashes in 2023 compared to 392 in 2022, a 1.3% decrease. This downward trend was more pronounced in crash outcomes, as total fatalities dropped by 60% (from 5 to 2) and total injuries decreased by 22.6% (from 177 to 137).
17
Hit-and-Run Crashes — 2023
▼ -10.5% vs prior (19)
Hit-and-run incidents saw a slight decrease in both count and rate in 2023 compared to the previous year. The number of hit-and-run crashes fell from 19 in 2022 to 17 in 2023. This corresponds to a decline in the hit-and-run rate, which dropped from 4.8% of all crashes in 2022 to 4.4% in 2023, indicating a slight downward trend for this crash type.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
3
Pedestrians Injured
1
Cyclists Injured
133
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 shift in the peak day of the week between the two periods. In 2023, Monday was the day with the most crashes (72), whereas in 2022, Friday saw the highest frequency (66). However, the peak hour for crashes remained consistent, with the 3 p.m. hour having the highest number of incidents in both 2023 (33 crashes) and 2022 (32 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity decreased in 2023 compared to the prior year. The number of fatal crashes dropped from 5 to 2, reducing their share of total crashes from 1.3% to 0.5%. The proportion of crashes resulting in any level of injury also declined, from 30.4% in 2022 to 27.2% in 2023. Correspondingly, crashes with no reported injuries increased as a share of the total, rising from 64.0% to 68.2%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors cited in crashes remained consistent between 2022 and 2023, with 'No improper driving,' 'Inattention,' and 'Followed too closely' as the top three in both years. However, the count for crashes attributed to 'Failed to yield right of way' increased significantly, rising from 23 incidents in 2022 to 39 in 2023, a 69.6% increase in count. Crashes involving 'Inattention' also saw a 12.2% increase in count, from 49 to 55.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
While the majority of crashes in both years occurred in daylight on dry roads, there was a notable shift in the prevalence of adverse conditions. In 2023, crashes on wet road surfaces increased from 69 to 96 incidents, representing 24.8% of all crashes compared to 17.6% in 2022. Similarly, crashes during rain more than doubled, increasing from 22 in 2022 to 52 in 2023. Lighting conditions remained largely consistent year-over-year, with about two-thirds of crashes in both periods occurring during daylight.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The vehicle makes most frequently involved in crashes saw a shift in rankings between the two years. In 2023, Toyota was the most common make with 123 vehicles, up from 104 in 2022 when it was second to Honda, whose involvement decreased from 106 vehicles to 70. Analysis of persons involved shows a demographic shift, with a smaller proportion of individuals in the 16-20 and 21-25 age groups and a larger proportion in the 65+ age group in 2023 compared to 2022.
Top Vehicle Makes (679 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
43 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (762 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones shifted, with more incidents occurring in lower speed zones in 2023. Crashes in 25 mph and 30 mph zones increased from 61 to 71 and 49 to 62, respectively, while crashes in the 35 mph zone decreased from 106 to 89. Fatal crashes also saw a reduction in higher speed zones; the 65 mph zone had one fatal crash in 2023, down from two in 2022, and the 35 mph zone also saw a drop from two fatal crashes to one.
Fatal crashes by zone: 35 mph: 1 of 89 (1.124%) · 65 mph: 1 of 104 (0.962%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: SHARON, MA
- Total crash records analyzed: 387
- Total persons involved: 835
- Total vehicles involved: 679
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/sharon/2023-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved