ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SHARON, MA · 2025
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/2025-annual-report
Yearly Traffic Safety Analysis
428 CRASHES IN
SHARON, MA
2025
In Sharon, total traffic crashes decreased by 9.9% from 475 in 2024 to 428 in 2025. While the number of fatalities remained constant at one, total injuries increased by 5.2% from 154 to 162. One of the most notable shifts was a 38.7% increase in crashes where speeding was a factor, rising from 31 to 43 incidents year-over-year.
428
▼ -9.9%was 475
Total Crash Events
1
Persons Killed
162
▲ 5.2%was 154
Persons Injured
28
▼ -22.2%was 36
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. 11 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash trends in Sharon show a decrease in overall volume but a slight increase in injury outcomes. Total crashes fell by 9.9% from 475 in the prior year to 428 in the current year. Despite this reduction, the number of people injured in these incidents rose from 154 to 162, while fatalities held steady at one.
28
Hit-and-Run Crashes — 2025
▼ -22.2% vs prior (36)
Hit-and-run incidents showed a downward trend year-over-year. The total count of hit-and-run crashes decreased from 36 in 2024 to 28 in 2025. This decline was also reflected in the hit-and-run rate, which fell from 7.6% of all crashes in the prior year to 6.5% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
1
Pedestrians Injured
3
Cyclists Injured
156
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak hour for crashes remained consistent year-over-year, occurring at 8 a.m. in both 2025 (41 crashes) and 2024 (42 crashes). However, the peak day of the week changed; while Friday was the clear peak in 2024 with 92 crashes, 2025 saw a shared peak between Wednesday and Friday, each with 69 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Year-over-year data indicates that while total crashes decreased, the proportion of crashes resulting in some form of harm increased. In 2025, 27.0% of crashes involved an injury or fatality, compared to 23.8% in 2024. The number of serious injury crashes rose from 7 to 8, and minor injury crashes increased from 59 to 63, while the count of fatal crashes was unchanged at one.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
A significant year-over-year shift occurred in contributing factors, with the count of crashes attributed to "Failure to keep in proper lane or running off road" increasing by 83.3%, from 24 incidents in 2024 to 44 in 2025. Crashes related to "Driving too fast for conditions" also rose by 33.3% from 21 to 28. In contrast, incidents citing "Failed to yield right of way" as a factor decreased by 30%, from 40 crashes in the prior year to 28 in the current year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Compared to the prior year, a larger proportion of crashes in 2025 occurred in favorable conditions. Crashes on dry roads accounted for 79.2% of the total in 2025, up from a 72.2% share in 2024. Concurrently, the absolute number of crashes during adverse conditions decreased, with incidents on snowy or icy roads falling from 46 in 2024 to 21 in 2025.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes were Toyota, Honda, and Ford in both periods, though their rankings shifted, with Toyota and Ford involvement increasing while Honda's decreased. Analysis of persons involved shows a demographic shift, with the 35-44 age group's share increasing from 14.8% to 17.0% year-over-year. Conversely, the share for the 26-34 age group decreased from 19.0% in 2024 to 16.5% in 2025.
Top Vehicle Makes (796 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
79 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (897 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes by speed zone shifted between the two periods. Crashes in 25 mph zones increased from 68 to 82, while those in 35 mph zones saw a notable decrease from 121 to 91. The single fatal crash recorded in 2025 occurred in a 65 mph zone; no fatalities were recorded within specific speed zones in the 2024 data.
Fatal crashes by zone: 65 mph: 1 of 107 (0.935%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: SHARON, MA
- Total crash records analyzed: 428
- Total persons involved: 980
- Total vehicles involved: 796
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/sharon/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved