ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WHITMAN, 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/whitman/2025-annual-report
Yearly Traffic Safety Analysis
194 CRASHES IN
WHITMAN, MA
2025
In 2025, Whitman recorded 194 total crashes, a 4.9% decrease from the 204 crashes reported in 2024. Total injuries also saw a decrease, falling from 56 to 50, while fatalities remained at zero for both periods. The most notable year-over-year change was in the type of collisions, with angle crashes increasing by 68% to become the most frequent type, while rear-end collisions decreased by 34%.
194
▼ -4.9%was 204
Total Crash Events
0
Persons Killed
50
▼ -10.7%was 56
Persons Injured
9
▼ -35.7%was 14
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. 7 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
Overall, traffic crashes in Whitman showed a downward trend year-over-year. Total reported crashes decreased by 4.9%, from 204 in 2024 to 194 in 2025. This trend was accompanied by a 10.7% reduction in total injuries, which fell from 56 to 50, while the number of fatalities remained zero in both years.
9
Hit-and-Run Crashes — 2025
▼ -35.7% vs prior (14)
Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. The number of hit-and-run crashes fell from 14 in 2024 to 9 in 2025, a reduction of over 35%. Consequently, the hit-and-run rate, which measures the proportion of total crashes that are hit-and-runs, declined from 6.9% to 4.6% year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
2
Pedestrians Injured
2
Cyclists Injured
45
Motorists Injured
1
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 temporal patterns of crashes shifted between the two periods. The peak day for crashes moved from Friday (40 incidents) in 2024 to Thursday (36 incidents) in 2025. While the 4 p.m. hour remained the peak time for collisions in both years, the number of crashes during that hour decreased from 24 to 19. The overall daily distribution of crashes also changed, with 2025 seeing a concentration on Wednesday and Thursday, compared to Friday and Saturday in the prior year.
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
Crash severity remained largely consistent year-over-year, with zero fatal crashes reported in both 2024 and 2025. The number of crashes resulting in a serious injury was unchanged at one incident in each period. The overall proportion of crashes involving any level of injury (serious, minor, or possible) was stable, shifting from 18.7% of crashes in 2024 to 19.1% in 2025. Crashes resulting in no injury accounted for 77.3% of all incidents in 2025, up from 75.5% in the prior year.
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
While 'No improper driving' was a significant category in both years, analysis of attributed causes shows shifts in driver behavior. Crashes attributed to 'Inattention' increased in count by 36%, from 25 incidents in 2024 to 34 in 2025, making it the leading improper driving factor. Similarly, 'Failed to yield right of way' incidents grew by 29% from 24 to 31. Conversely, crashes involving 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' were cut in half, dropping from 14 to 7 incidents.
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
Crashes in 2025 occurred more frequently under clear and dry conditions compared to the prior year. The proportion of crashes on dry roads increased from 79.4% in 2024 to 83.5% in 2025, while crashes on wet roads decreased from 40 to 26 incidents. Similarly, the share of crashes happening in clear weather rose from 66.7% to 72.7%. The proportion of crashes occurring in daylight remained stable at approximately 68% for both periods.
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 demographic profile of individuals involved in crashes shifted notably, with the 16-20 age group seeing its involvement nearly double from 45 persons in 2024 to 89 in 2025. This made it the most represented age group in the current period, surpassing the 35-44 age group which was largest in the prior year. Regarding vehicles, the top makes involved in crashes remained consistent, with Toyota, Honda, Chevrolet, and Ford leading in both years. However, Honda's involvement increased from 34 to 44 vehicles, moving it from the fifth to the second most common make.
Top Vehicle Makes (361 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
38 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (447 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 across different speed zones changed year-over-year, indicating a shift towards higher-speed roadways. Crashes in 40 mph zones increased from 29 to 41 incidents, while those in 25 mph zones decreased from 48 to 29. The 30 mph zone remained the most common location for crashes in both periods, with the count increasing from 63 to 72. There were no fatal crashes recorded in any speed zone during either year.
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: WHITMAN, MA
- Total crash records analyzed: 194
- Total persons involved: 482
- Total vehicles involved: 361
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). "WHITMAN, 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/whitman/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